Sample records for network based carbonate

  1. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo


    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  2. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux (United States)

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.


    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  3. A Low-Carbon-Based Bilevel Optimization Model for Public Transit Network

    Directory of Open Access Journals (Sweden)

    Xu Sun


    Full Text Available To satisfy the demand of low-carbon transportation, this paper studies the optimization of public transit network based on the concept of low carbon. Taking travel time, operation cost, energy consumption, pollutant emission, and traffic efficiency as the optimization objectives, a bilevel model is proposed in order to maximize the benefits of both travelers and operators and minimize the environmental cost. Then the model is solved with the differential evolution (DE algorithm and applied to a real network of Baoji city. The results show that the model can not only ensure the benefits of travelers and operators, but can also reduce pollutant emission and energy consumption caused by the operations of buses, which reflects the concept of low carbon.

  4. A mathematical/physics carbon emission reduction strategy for building supply chain network based on carbon tax policy

    Directory of Open Access Journals (Sweden)

    Li Xueying


    Full Text Available Under the background of a low carbon economy, this paper examines the impact of carbon tax policy on supply chain network emission reduction. The integer linear programming method is used to establish a supply chain network emission reduction such a model considers the cost of CO2 emissions, and analyses the impact of different carbon price on cost and carbon emissions in supply chains. The results show that the implementation of a carbon tax policy can reduce CO2 emissions in building supply chain, but the increase in carbon price does not produce a reduction effect, and may bring financial burden to the enterprise. This paper presents a reasonable carbon price range and provides decision makers with strategies towards realizing a low carbon building supply chain in an economical manner.

  5. A mathematical/physics carbon emission reduction strategy for building supply chain network based on carbon tax policy (United States)

    Li, Xueying; Peng, Ying; Zhang, Jing


    Under the background of a low carbon economy, this paper examines the impact of carbon tax policy on supply chain network emission reduction. The integer linear programming method is used to establish a supply chain network emission reduction such a model considers the cost of CO2 emissions, and analyses the impact of different carbon price on cost and carbon emissions in supply chains. The results show that the implementation of a carbon tax policy can reduce CO2 emissions in building supply chain, but the increase in carbon price does not produce a reduction effect, and may bring financial burden to the enterprise. This paper presents a reasonable carbon price range and provides decision makers with strategies towards realizing a low carbon building supply chain in an economical manner.

  6. Uncertainties in neural network model based on carbon dioxide concentration for occupancy estimation

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Azimil Gani; Rahman, Haolia; Kim, Jung-Kyung; Han, Hwataik [Kookmin University, Seoul (Korea, Republic of)


    Demand control ventilation is employed to save energy by adjusting airflow rate according to the ventilation load of a building. This paper investigates a method for occupancy estimation by using a dynamic neural network model based on carbon dioxide concentration in an occupied zone. The method can be applied to most commercial and residential buildings where human effluents to be ventilated. An indoor simulation program CONTAMW is used to generate indoor CO{sub 2} data corresponding to various occupancy schedules and airflow patterns to train neural network models. Coefficients of variation are obtained depending on the complexities of the physical parameters as well as the system parameters of neural networks, such as the numbers of hidden neurons and tapped delay lines. We intend to identify the uncertainties caused by the model parameters themselves, by excluding uncertainties in input data inherent in measurement. Our results show estimation accuracy is highly influenced by the frequency of occupancy variation but not significantly influenced by fluctuation in the airflow rate. Furthermore, we discuss the applicability and validity of the present method based on passive environmental conditions for estimating occupancy in a room from the viewpoint of demand control ventilation applications.

  7. A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks. (United States)

    Yang, Jiachen; Zhou, Jianxiong; Lv, Zhihan; Wei, Wei; Song, Houbing


    Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring.

  8. City Carbon Footprint Networks

    Directory of Open Access Journals (Sweden)

    Guangwu Chen


    Full Text Available Progressive cities worldwide have demonstrated political leadership by initiating meaningful strategies and actions to tackle climate change. However, the lack of knowledge concerning embodied greenhouse gas (GHG emissions of cities has hampered effective mitigation. We analyse trans-boundary GHG emission transfers between five Australian cities and their trading partners, with embodied emission flows broken down into major economic sectors. We examine intercity carbon footprint (CF networks and disclose a hierarchy of responsibility for emissions between cities and regions. Allocations of emissions to households, businesses and government and the carbon efficiency of expenditure have been analysed to inform mitigation policies. Our findings indicate that final demand in the five largest cities in Australia accounts for more than half of the nation’s CF. City households are responsible for about two thirds of the cities’ CFs; the rest can be attributed to government and business consumption and investment. The city network flows highlight that over half of emissions embodied in imports (EEI to the five cities occur overseas. However, a hierarchy of GHG emissions reveals that overseas regions also outsource emissions to Australian cities such as Perth. We finally discuss the implications of our findings on carbon neutrality, low-carbon city concepts and strategies and allocation of subnational GHG responsibility.

  9. Organic Electrolyte Based Pulsed Nanoplating and Fabrication of Carbon Nanotube Network Transistors (United States)

    Kang, Myung Gil; Hwang, Dong Hoon; Kim, Tae Geun; Hwang, Jong Seung; Ahn, Doyeol; Whang, Dongmok; Hwang, Sung Woo


    The formation of gold nanocontacts was performed using a pulsed electrochemical plating technique. The effect of various plating variables on the surface roughness of the plated electrodes was studied in the high frequency regime where the reduction reaction of gold complex becomes the bottleneck process. We demonstrated the selective contact formation of single wall carbon nanotube network field effect transistors (FETs) with this technique. The fabricated FETs exhibit usual p-type behavior with the performance comparable to usual network FETs.

  10. Free vibration of super-graphene carbon nanotube networks via a beam element based coarse-grained method (United States)

    Gu, Ruifeng; Wang, Lifeng; He, Xiaoqiao


    A new beam element based coarse-grained model is developed to investigate efficiently the mechanical behavior of a large system of super-graphene carbon nanotube (SGCNT) networks with all boundaries clamped supported. The natural frequencies and mode shapes of the SGCNT networks made of single-walled carbon nanotubes (SWCNTs) with different diameters and lengths are obtained via the proposed coarse-grained model. The applicability of the coarse-grained model for the SGCNT networks is verified by comparison with the molecular structural mechanics model. The natural frequencies and associated mode shapes obtained via the coarse-grained model agree well with the results obtained from the molecular structural mechanics method, indicating that the coarse-grained model developed in this study can be applied for the dynamic prediction of the SGCNT networks.

  11. Impact of Different Carbon Policies on City Logistics Network

    Directory of Open Access Journals (Sweden)

    Yang Jianhua


    Full Text Available A programming model for a four-layer urban logistics distribution network is constructed and revised based on three types of carbon emissions policies such as Carbon tax, carbon emissions Cap, Carbon Trade. Effects of different policies on logistics costs and carbon emissions are analyzed based on a spatial Logistics Infrastructure layout of Beijing. Research findings are as follows: First, based on low-carbon policies, the logistics costs and carbon emissions can be changed by different modes of transport in a certain extent; second, only when carbon taxes and carbon trading prices are higher, carbon taxes and carbon trading policies can reduce carbon emissions while not significantly increase logistics costs at the same time, and more effectively achieve carbon reduction targets than use carbon cap policy.

  12. A morphological and structural approach to evaluate the electromagnetic performances of composites based on random networks of carbon nanotubes (United States)

    De Vivo, B.; Lamberti, P.; Spinelli, G.; Tucci, V.


    Small quantities of carbon nanotubes (CNTs) in polymer resins allow to obtain new lightweight nanocomposites suitable for microwave applications, such as efficient electromagnetic shielding or radar absorbing materials. The availability of appropriate simulation models taking into account the morphological and physical features of such very interesting composites is very important for design and performance optimization of devices and systems. In this study, a 3-dimensional (3D) numerical structure modeling the morphology of a CNT-based composite is considered in order to carry out a computational analysis of their electromagnetic performances. The main innovative features of the proposed model consists in the identification of a resistance and capacitance network whose values depend on the filler geometry and loading and whose complexity is associated with the percolation paths. Tunneling effect and capacitive interactions between the individual conductive particles are properly taken into account. The obtained network allows an easy calculation in a wide frequency range of the complex permittivity and others electromagnetic parameters. Moreover, a reliable sensitivity analysis concerning the impact of some crucial parameters, such as the CNTs properties and the dielectric permittivity of the neat resin, on the electromagnetic features of the resulting composites can be carried out. The model predictions are in good agreement with existing experimental data, suggesting that the proposed model can be a useful tool for their design and performance optimization in the microwave range.

  13. Flexible and Freestanding Supercapacitor Electrodes Based on Nitrogen-Doped Carbon Networks/Graphene/Bacterial Cellulose with Ultrahigh Areal Capacitance. (United States)

    Ma, Lina; Liu, Rong; Niu, Haijun; Xing, Lixin; Liu, Li; Huang, Yudong


    Flexible energy-storage devices based on supercapacitors rely largely on the scrupulous design of flexible electrodes with both good electrochemical performance and high mechanical properties. Here, nitrogen-doped carbon nanofiber networks/reduced graphene oxide/bacterial cellulose (N-CNFs/RGO/BC) freestanding paper is first designed as a high-performance, mechanically tough, and bendable electrode for a supercapacitor. The BC is exploited as both a supporting substrate for a large mass loading of 8 mg cm-2 and a biomass precursor for N-CNFs by pyrolysis. The one-step carbonization treatment not only fabricates the nitrogen-doped three-dimensional (3D) nanostructured carbon composite materials but also forms the reduction of the GO sheets at the same time. The fabricated paper electrode exhibits an ultrahigh areal capacitance of 2106 mF cm-2 (263 F g-1) in a KOH electrolyte and 2544 mF cm-2 (318 F g-1) in a H2SO4 electrolyte, exceptional cycling stability (∼100% retention after 20000 cycles), and excellent tensile strength (40.7 MPa). The symmetric supercapacitor shows a high areal capacitance (810 mF cm-2 in KOH and 920 mF cm-2 in H2SO4) and thus delivers a high energy density (0.11 mWh cm-2 in KOH and 0.29 mWh cm-2 in H2SO4) and a maximum power density (27 mW cm-2 in KOH and 37.5 mW cm-2 in H2SO4). This work shows that the new procedure is a powerful and promising way to design flexible and freestanding supercapacitor electrodes.

  14. Nitrogen-Enriched Carbon/CNT Composites Based on Schiff-Base Networks: Ultrahigh N Content and Enhanced Lithium Storage Properties. (United States)

    Xiao, Zhichang; Song, Qi; Guo, Ruiying; Kong, Debin; Zhou, Shanke; Huang, Xiaoxiong; Iqbal, Rashid; Zhi, Linjie


    To improve the electrochemical performance of carbonaceous anodes for lithium ion batteries (LIBs), the incorporation of both well-defined heteroatom species and the controllable 3D porous networks are urgently required. In this work, a novel N-enriched carbon/carbon nanotube composite (NEC/CNT) through a chemically induced precursor-controlled pyrolysis approach is developed. Instead of conventional N-containing sources or precursors, Schiff-base network (SNW-1) enables the desirable combination of a 3D polymer with intrinsic microporosity and ultrahigh N-content, which can significantly promote the fast transport of both Li + and electron. Significantly, the strong interaction between carbon skeleton and nitrogen atoms enables the retention of ultrahigh N-content up to 21 wt% in the resultant NEC/CNT, which exhibits a super-high capacity (1050 mAh g -1 ) for 1000 cycles and excellent rate performance (500 mAh g -1 at a current density of 5 A g -1 ) as the anode material for LIBs. The NEC/CNT composite affords a new model system as well as a totally different insight for deeply understanding the relationship between chemical structures and lithium ion storage properties, in which chemistry may play a more important role than previously expected. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. A black carbon air quality network (United States)

    Kirchstetter, T.; Caubel, J.; Cados, T.; Preble, C.; Rosen, A.


    We developed a portable, power efficient black carbon sensor for deployment in an air quality network in West Oakland, California. West Oakland is a San Francisco Bay Area residential/industrial community adjacent to regional port and rail yard facilities, and is surrounded by major freeways. As such, the community is affected by diesel particulate matter emissions from heavy-duty diesel trucks, locomotives, and ships associated with freight movement. In partnership with Environmental Defense Fund, the Bay Area Air Quality Management District, and the West Oakland Environmental Indicators Project, we are collaborating with community members to build and operate a 100-sensor black carbon measurement network for a period of several months. The sensor employs the filter-based light transmission method to measure black carbon. Each sensor node in the network transmits data hourly via SMS text messages. Cost, power consumption, and performance are considered in choosing components (e.g., pump) and operating conditions (e.g., sample flow rate). In field evaluation trials over several weeks at three monitoring locations, the sensor nodes provided black carbon concentrations comparable to commercial instruments and ran autonomously for a week before sample filters and rechargeable batteries needed to be replaced. Buildup to the 100-sensor network is taking place during Fall 2016 and will overlap with other ongoing air monitoring projects and monitoring platforms in West Oakland. Sensors will be placed along commercial corridors, adjacent to freeways, upwind of and within the Port, and throughout the residential community. Spatial and temporal black carbon concentration patterns will help characterize pollution sources and demonstrate the value of sensing networks for characterizing intra-urban air pollution concentrations and exposure to air pollution.

  16. Carbon-based spintronics (United States)

    Chen, Peng; Zhang, GuangYu


    Carbon-based spintronics refers mainly to the spin injection and transport in carbon materials including carbon nanotubes, graphene, fullerene, and organic materials. In the last decade, extraordinary development has been achieved for carbon-based spintronics, and the spin transport has been studied in both local and nonlocal spin valve devices. A series of theoretical and experimental studies have been done to reveal the spin relaxation mechanisms and spin transport properties in carbon materials, mostly for graphene and carbon nanotubes. In this article, we provide a brief review on spin injection and transport in graphene, carbon nanotubes, fullerene and organic thin films.

  17. Heating-Rate-Triggered Carbon-Nanotube-based 3-Dimensional Conducting Networks for a Highly Sensitive Noncontact Sensing Device

    KAUST Repository

    Tai, Yanlong


    Recently, flexible and transparent conductive films (TCFs) are drawing more attention for their central role in future applications of flexible electronics. Here, we report the controllable fabrication of TCFs for moisture-sensing applications based on heating-rate-triggered, 3-dimensional porous conducting networks through drop casting lithography of single-walled carbon nanotube (SWCNT)/poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS) ink. How ink formula and baking conditions influence the self-assembled microstructure of the TCFs is discussed. The sensor presents high-performance properties, including a reasonable sheet resistance (2.1 kohm/sq), a high visible-range transmittance (>69%, PET = 90%), and good stability when subjected to cyclic loading (>1000 cycles, better than indium tin oxide film) during processing, when formulation parameters are well optimized (weight ratio of SWCNT to PEDOT:PSS: 1:0.5, SWCNT concentration: 0.3 mg/ml, and heating rate: 36 °C/minute). Moreover, the benefits of these kinds of TCFs were verified through a fully transparent, highly sensitive, rapid response, noncontact moisture-sensing device (5 × 5 sensing pixels).

  18. Eco-efficient based logistics network design in hybrid manufacturing/ remanufacturing system in low-carbon economy

    Directory of Open Access Journals (Sweden)

    Yacan Wang


    Full Text Available Purpose: Low-carbon economy requires the pursuit of eco-efficiency, which is a win-win situation between economic and environmental efficiency. In this paper the question of trading off the economic and environmental effects embodied in eco-efficiency in the hybrid manufacturing/remanufacturing logistics network design in the context of low-carbon economy is examined.Design/methodology/approach: A multi-objective mixed integer linear programming model to find the optimal facility locations and materials flow allocation is established. In the objective function, three minimum targets are set: economic cost, CO2 emission and waste generation. Through an iterative algorithm, the Pareto Boundary of the problem is obtained.Findings: The results of numeric study show that in order to achieve a Pareto improvement over an original system, three of the critical rates (i.e. return rate, recovery rate, and cost substitute rate should be increased.Practical implications: To meet the need of low-carbon dioxide, an iso- CO2 emission curve in which decision makers have a series of optimal choices with the same CO2 emission but different cost and waste generation is plotted. Each choice may have different network design but all of these are Pareto optimal solutions, which provide a comprehensive evaluation of both economics and ecology for the decision making.Originality/value: This research chooses carbon emission as one of the three objective functions and uses Pareto sets to analyze how to balance profitability and environmental impacts in designing remanufacturing closed-loop supply chain in the context of low-carbon economy.

  19. An Efficient Upscaling Procedure Based on Stokes-Brinkman Model and Discrete Fracture Network Method for Naturally Fractured Carbonate Karst Reservoirs

    KAUST Repository

    Qin, Guan


    Naturally-fractured carbonate karst reservoirs are characterized by various-sized solution caves that are connected via fracture networks at multiple scales. These complex geologic features can not be fully resolved in reservoir simulations due to the underlying uncertainty in geologic models and the large computational resource requirement. They also bring in multiple flow physics which adds to the modeling difficulties. It is thus necessary to develop a method to accurately represent the effect of caves, fractures and their interconnectivities in coarse-scale simulation models. In this paper, we present a procedure based on our previously proposed Stokes-Brinkman model (SPE 125593) and the discrete fracture network method for accurate and efficient upscaling of naturally fractured carbonate karst reservoirs.

  20. Carbon emission flow in networks

    National Research Council Canada - National Science Library

    Kang, Chongqing; Zhou, Tianrui; Chen, Qixin; Xu, Qianyao; Xia, Qing; Ji, Zhen


    As the human population increases and production expands, energy demand and anthropogenic carbon emission rates have been growing rapidly, and the need to decrease carbon emission levels has drawn increasing attention...

  1. Networking Carbon Nanotubes for Integrated Electronics. (United States)

    Romo-Herrera, J. M.; Terrones, M.; Terrones, H.; Meunier, V.


    The unique electronic and mechanical properties of individual Carbon Nanotubes (CNTs) have attracted much interest as candidates for molecular electronic devices and reinforced materials. However, their integration in organized architectures remains a major challenge. Recent breakthroughs reported on the Self-Assembly of 1D Nanostructures[1], and on the coalescence mechanism for interconnecting CNTs[2], point to the possibility of designing and obtaining Ordered Networks based on CNTs (ON- CNTs). We propose a set with different complex architectures of ON- CNTs based on --but not limited to-- armchair and zigzag nanotubes. In addition to the study of the energetics of the structures, we have systematically investigated their electronic transport properties in the framework of the Landauer-Buttiker formalism and equilibrium Green functions. To take curvature into account, we employed a semi-empirical Hamiltonian based on 4 orbitals (s,px,py,pz) per carbon atom. Further insight is obtained analyzing the electron pathways from a scattering point of view, which allows a real-space analysis of the wave function from the transmitted electrons across the structure. [1]Whang D etal. Nanoletters,3 (2003). Tao A etal. Nanoletters,3 (2003). [2]Terrones M etal. PRL,89 (2002). Endo M etal. Nanoletters,5 (2005).

  2. Glucose oxidase immobilization onto carbon nanotube networking

    CERN Document Server

    Karachevtsev, V A; Zarudnev, E S; Karachevtsev, M V; Leontiev, V S; Linnik, A S; Lytvyn, O S; Plokhotnichenko, A M; Stepanian, S G


    When elaborating the biosensor based on single-walled carbon nanotubes (SWNTs), it is necessary to solve such an important problem as the immobilization of a target biomolecule on the nanotube surface. In this work, the enzyme (glucose oxidase (GOX)) was immobilized on the surface of a nanotube network, which was created by the deposition of nanotubes from their solution in 1,2-dichlorobenzene by the spray method. 1-Pyrenebutanoic acid succinimide ester (PSE) was used to form the molecular interface, the bifunctional molecule of which provides the covalent binding with the enzyme shell, and its other part (pyrene) is adsorbed onto the nanotube surface. First, the usage of such a molecular interface leaves out the direct adsorption of the enzyme (in this case, its activity decreases) onto the nanotube surface, and, second, it ensures the enzyme localization near the nanotube. The comparison of the resonance Raman (RR) spectrum of pristine nanotubes with their spectrum in the PSE environment evidences the creat...

  3. Directed graph based carbon flow tracing for demand side carbon obligation allocation

    DEFF Research Database (Denmark)

    Sun, Tao; Feng, Donghan; Ding, Teng


    method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution......In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based...

  4. Network-Based Effectiveness

    National Research Council Canada - National Science Library

    Friman, Henrik


    ... (extended from Leavitt, 1965). This text identifies aspects of network-based effectiveness that can benefit from a better understanding of leadership and management development of people, procedures, technology, and organizations...

  5. Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence (United States)

    Hamed Alemohammad, Seyed; Fang, Bin; Konings, Alexandra G.; Aires, Filipe; Green, Julia K.; Kolassa, Jana; Miralles, Diego; Prigent, Catherine; Gentine, Pierre


    A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solar-induced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H, and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H, and GPP from 2007 to 2015 at 1° × 1° spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events. Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.

  6. Modeling and optimization by particle swarm embedded neural network for adsorption of zinc (II) by palm kernel shell based activated carbon from aqueous environment. (United States)

    Karri, Rama Rao; Sahu, J N


    Zn (II) is one the common pollutant among heavy metals found in industrial effluents. Removal of pollutant from industrial effluents can be accomplished by various techniques, out of which adsorption was found to be an efficient method. Applications of adsorption limits itself due to high cost of adsorbent. In this regard, a low cost adsorbent produced from palm oil kernel shell based agricultural waste is examined for its efficiency to remove Zn (II) from waste water and aqueous solution. The influence of independent process variables like initial concentration, pH, residence time, activated carbon (AC) dosage and process temperature on the removal of Zn (II) by palm kernel shell based AC from batch adsorption process are studied systematically. Based on the design of experimental matrix, 50 experimental runs are performed with each process variable in the experimental range. The optimal values of process variables to achieve maximum removal efficiency is studied using response surface methodology (RSM) and artificial neural network (ANN) approaches. A quadratic model, which consists of first order and second order degree regressive model is developed using the analysis of variance and RSM - CCD framework. The particle swarm optimization which is a meta-heuristic optimization is embedded on the ANN architecture to optimize the search space of neural network. The optimized trained neural network well depicts the testing data and validation data with R2 equal to 0.9106 and 0.9279 respectively. The outcomes indicates that the superiority of ANN-PSO based model predictions over the quadratic model predictions provided by RSM. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Carbon Based Refractories

    National Research Council Canada - National Science Library

    EWAIS, Emad Mohamed M


    .... They are classified into two groups; carbon/bricks/blocks and carbon containing materials. Carbon containing materials are further classified into carbon containing basic refractories and non-basic refractories...

  8. Photothermal Conversion Triggered Precisely Targeted Healing of Epoxy Resin Based on Thermoreversible Diels-Alder Network and Amino-Functionalized Carbon Nanotubes. (United States)

    Li, Qiu-Tong; Jiang, Miao-Jie; Wu, Gang; Chen, Li; Chen, Si-Chong; Cao, Yu-Xiao; Wang, Yu-Zhong


    In the present work, we demonstrated the recyclability and precisely targeted reparability of amino functionalized multiwall carbon nanotubes-epoxy resin based on dynamic covalent Diels-Alder (DA) network (NH2-MWCNTs/DA-epoxy) by exploring the photothermal conversion of CNTs to trigger the reactions of dynamic chemical bonds. The covalent cross-linked networks of NH2-MWCNTs/DA-epoxy resin change their topology to linear polymer by thermally activated reverse Diels-Alder (r-DA) reactions at high temperatures, which endues the resin with almost 100% recyclability. The self-healing property of the epoxy resin was confirmed by the complete elimination of cracks after the reconstruction of DA network induced by heating or near-infrared (NIR) irradiation. For heat-triggered self-healing process, heat energy may also act on those uninjured parts of the resin and cause the dissociation of the whole DA network. Therefore, redundant r-DA and DA reactions, which have no contribution to self-healing, are also triggered during thermal treatment, resulting in not only a waste of energy but also the deformation of the sample under external force. Meanwhile, for the NIR-triggered self-healing process, the samples can maintain well their original shape without observable deformation after irradiation. The NIR-triggered healing process, which uses MWCNTs as the photothermal convertor, have very good regional controllability by simply tuning the MWCNTs content, the distance from NIR laser source to sample, and the laser power. The injured samples can be locally repaired with high precision and efficiency without an obvious influence on those uninjured parts.

  9. Three-Dimensional Conductive Nanocomposites Based on Multiwalled Carbon Nanotube Networks and PEDOT:PSS as a Flexible Transparent Electrode for Optoelectronics. (United States)

    Cho, Er-Chieh; Li, Chiu-Ping; Huang, Jui-Hsiung; Lee, Kuen-Chan; Huang, Jen-Hsien


    We have synthesized conductive nanocomposites composed of multiwalled carbon nanotubes (MWCNTs) and Au nanoparticles (NPs). The Au NPs with an average size of approximately 4.3 nm are uniformly anchored on the MWCNT. After being exposed to microwave (MW) plasma irradiation, the anchored Au NPs melt and fuse, leading to larger aggregates (34 nm) that can connect the MWCNT forming a three-dimensional conducting network. The formation of a continuous MWCNT network can produce more a conductive pathway, leading to lower sheet resistance. When the Au-MWCNT is dispersed in the highly conductive polymer, poly(ethylene dioxythiophene):polystyrenesulfonate ( PSS), we can obtain solution-processable composite formulations for the preparation of a flexible transparent electrode. The resulting Au-MWCNT/PEDOT:PSS hybrid films possess a sheet resistance of 51 Ω/sq with a transmittance of 86.2% at 550 nm. We also fabricate flexible organic solar cells and electrochromic devices to demonstrate the potential use of the as-prepared composite electrodes. Compared with the indium tin oxide-based devices, both the solar cells and electrochromic devices with the composites incorporated as a transparent electrode deliver comparable performance.

  10. BaFe12O19-chitosan Schiff-base Ag (I) complexes embedded in carbon nanotube networks for high-performance electromagnetic materials (United States)

    Zhao, Jie; Xie, Yu; Guan, Dongsheng; Hua, Helin; Zhong, Rong; Qin, Yuancheng; Fang, Jing; Liu, Huilong; Chen, Junhong


    The multiwalled carbon nanotubes/BaFe12O19-chitosan (MCNTs/BF-CS) Schiff base Ag (I) complex composites were synthesized successfully by a chemical bonding method. The morphology and structures of the composites were characterized with electron microscopy, Fourier transform infrared spectroscopy and X-ray diffraction techniques. Their conductive properties were measured using a four-probe conductivity tester at room temperature, and their magnetic properties were tested by a vibrating sample magnetometer. The results show that the BF-CS Schiff base Ag (I) complexes are embedded into MCNT networks. When the mass ratio of MCNTs and BF-CS Schiff base is 0.95:1, the conductivity, Ms (saturation magnetization), Mr (residual magnetization), and Hc (coercivity) of the BF-CS Schiff base composites reach 1.908 S cm−1, 28.20 emu g−1, 16.66 emu g−1 and 3604.79 Oe, respectively. Finally, a possible magnetic mechanism of the composites has also been proposed. PMID:26218269

  11. Photonics based on carbon nanotubes. (United States)

    Gu, Qingyuan; Gicquel-Guézo, Maud; Loualiche, Slimane; Pouliquen, Julie Le; Batte, Thomas; Folliot, Hervé; Dehaese, Olivier; Grillot, Frederic; Battie, Yann; Loiseau, Annick; Liang, Baolai; Huffaker, Diana


    Among direct-bandgap semiconducting nanomaterials, single-walled carbon nanotubes (SWCNT) exhibit strong quasi-one-dimensional excitonic optical properties, which confer them a great potential for their integration in future photonics devices as an alternative solution to conventional inorganic semiconductors. In this paper, we will highlight SWCNT optical properties for passive as well as active applications in future optical networking. For passive applications, we directly compare the efficiency and power consumption of saturable absorbers (SAs) based on SWCNT with SA based on conventional multiple quantum wells. For active applications, exceptional photoluminescence properties of SWCNT, such as excellent light-emission stabilities with temperature and excitation power, hold these nanometer-scale materials as prime candidates for future active photonics devices with superior performances.

  12. A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink

    DEFF Research Database (Denmark)

    Landschützer, P.; Gruber, N.; Bakker, D.C.E.


    pressure of CO2 (pCO2) at a resolution of 1° × 1°. From those, we compute the air–sea CO2 flux maps using a standard gas exchange parameterization and high-resolution wind speeds. The neural networks fit the observed pCO2 data with a root mean square error (RMSE) of about 10 μatm and with almost no bias......) a continuous improvement of the observations, i.e., the Surface Ocean CO2 Atlas (SOCAT) v1.5 database and (ii) a newly developed technique to interpolate the observations in space and time. In particular, we use a 2 step neural network approach to reconstruct basin-wide monthly maps of the sea surface partial...

  13. Estimates of Water-Column Nutrient Concentrations and Carbonate System Parameters in the Global Ocean: A Novel Approach Based on Neural Networks

    Directory of Open Access Journals (Sweden)

    Raphaëlle Sauzède


    Full Text Available A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network was developed to estimate water-column (i.e., from surface to 8,000 m depth biogeochemically relevant variables in the Global Ocean. These are the concentrations of three nutrients [nitrate (NO3−, phosphate (PO43−, and silicate (Si(OH4] and four carbonate system parameters [total alkalinity (AT, dissolved inorganic carbon (CT, pH (pHT, and partial pressure of CO2 (pCO2], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure, and oxygen (O2 together with sampling latitude, longitude, and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the diversity of open-ocean conditions, hence making CANYON potentially applicable to most oceanic environments. For each variable, CANYON was trained using 80 % randomly chosen data from the whole database (after eight 10° × 10° zones removed providing an “independent data-set” for additional validation, the remaining 20 % data were used for the neural-network test of validation. Overall, CANYON retrieved the variables with high accuracies (RMSE: 1.04 μmol kg−1 (NO3−, 0.074 μmol kg−1 (PO43−, 3.2 μmol kg−1 (Si(OH4, 0.020 (pHT, 9 μmol kg−1 (AT, 11 μmol kg−1 (CT and 7.6 % (pCO2 (30 μatm at 400 μatm. This was confirmed for the eight independent zones not included in the training process. CANYON was also applied to the Hawaiian Time Series site to produce a 22 years long simulated time series for the above seven variables. Comparison of modeled and measured data was also very satisfactory (RMSE in the order of magnitude of RMSE from validation test. CANYON is thus a promising method to derive distributions of key biogeochemical variables. It could be used for a variety of global and regional applications ranging from data quality control

  14. From Networks to Nematics -- Carbon Nanotubes as Soft Matter (United States)

    Hobbie, Erik K.


    Carbon nanotubes represent just one example of an emerging paradigm in condensed matter physics and materials science: traditionally ``hard'' materials appearing in new ``soft'' applications and environments. In part, this trend being is being fueled by the desire to exploit solution and fluid-based approaches, such as self assembly and flow processing, in an effort to streamline the engineering and commercialization of new materials and applications. In this talk I will review our recent work on dispersing, aligning and manipulating carbon nanotubes in complex fluids and polymer melts. Due to the large aspect ratios and strong attractive interaction potentials intrinsic to such materials, a number of scientific and technical challenges become immediately apparent. In particular, I will focus on the subtle interplay of rheological influences, such as externally applied shear and elongation stresses, with the inherent ``stickiness'' of carbon nanotube suspensions and melts, where the latter typically favors the formation of disordered networks or ``gels'' over the more desirable liquid-crystalline order. For simple shear, the strength of the applied stress is found to be a critical factor in dictating carbon nanotube morphology, which varies from a quiescent network to macroscopic aggregates to a fully dispersed, flow-aligned (para)nematic state. Although we find remarkably low loading thresholds for elastic percolation, our results highlight a fundamental dilemma for the engineering of conducting carbon nanotube polymer composites; dispersion stability will often be achieved at the expense of electrical conductivity.

  15. Carbon Nanotube Synaptic Transistor Network for Pattern Recognition. (United States)

    Kim, Sungho; Yoon, Jinsu; Kim, Hee-Dong; Choi, Sung-Jin


    Inspired by the human brain, a neuromorphic system combining complementary metal-oxide semiconductor (CMOS) and adjustable synaptic devices may offer new computing paradigms by enabling massive neural-network parallelism. In particular, synaptic devices, which are capable of emulating the functions of biological synapses, are used as the essential building blocks for an information storage and processing system. However, previous synaptic devices based on two-terminal resistive devices remain challenging because of their variability and specific physical mechanisms of resistance change, which lead to a bottleneck in the implementation of a high-density synaptic device network. Here we report that a three-terminal synaptic transistor based on carbon nanotubes can provide reliable synaptic functions that encode relative timing and regulate weight change. In addition, using system-level simulations, the developed synaptic transistor network associated with CMOS circuits can perform unsupervised learning for pattern recognition using a simplified spike-timing-dependent plasticity scheme.

  16. Black carbon network in Mexico. First Results (United States)

    Barrera, Valter; Peralta, Oscar; Granado, Karen; Ortinez, Abraham; Alvarez-Ospina, Harry; Espinoza, Maria de la Luz; Castro, Telma


    heating. The annual BC concentration media for Mexico City and Monterrey site were near 2.5 μg/m3, Guadalajara near 2 μg/m3, and Juriquilla 1.2 μg/m3. Daily and weekly data showed the BC and CO strong relationships produced by the traffic source in the three main cities. BC can be used as a marker for mobile sources policies in cities to evaluate these results quickly. Guadalajara and Juriquilla had some monitoring issues. Data verification is still been verified. This work presents a first year BC experimental network extended measure campaign for year 2015 in some cities in Mexico, to obtain direct equivalent black carbon (eBC) concentrations (Also, named when eBC data is derived from optical absorption methods) (Petzold, 2013) using aethalometers and photoacoustic extinctiometers. After this effort (mainly from National University and local agencies) it is planned to extend this BC Network to other cities around Mexico and with the Mexican Government support. REFERENCES Bond, T. C., et al., (2013). Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380-5552. Ramanathan, V. and Carmichael, G. (2008). Global and regional climate changes due to black carbon, Nat. Geosci., 1, 221-227 Petzold A., et al. (2013). Recommendations for reporting "black carbon" measurements. Atmos. Chem. Phys., 13, 8365-8379.

  17. Carbon based prosthetic devices

    Energy Technology Data Exchange (ETDEWEB)

    Devlin, D.J.; Carroll, D.W.; Barbero, R.S.; Archuleta, T. [Los Alamos National Lab., NM (US); Klawitter, J.J.; Ogilvie, W.; Strzepa, P. [Ascension Orthopedics (US); Cook, S.D. [Tulane Univ., New Orleans, LA (US). School of Medicine


    This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project objective was to evaluate the use of carbon/carbon-fiber-reinforced composites for use in endoprosthetic devices. The application of these materials for the metacarpophalangeal (MP) joints of the hand was investigated. Issues concerning mechanical properties, bone fixation, biocompatibility, and wear are discussed. A system consisting of fiber reinforced materials with a pyrolytic carbon matrix and diamond-like, carbon-coated wear surfaces was developed. Processes were developed for the chemical vapor infiltration (CVI) of pyrolytic carbon into porous fiber preforms with the ability to tailor the outer porosity of the device to provide a surface for bone in-growth. A method for coating diamond-like carbon (DLC) on the articulating surface by plasma-assisted chemical vapor deposition (CVD) was developed. Preliminary results on mechanical properties of the composite system are discussed and initial biocompatibility studies were performed.

  18. High performance all-carbon composite transparent electrodes containing uniform carbon nanotube networks

    Energy Technology Data Exchange (ETDEWEB)

    Yun, Hyung Duk; Kwak, Jinsung; Kim, Se-Yang [School of Materials Science and Engineering & Low-Dimensional Carbon Materials Center, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); Seo, Han; Bang, In Cheol; Kim, Sung Youb [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); Kang, Seoktae [Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141 (Korea, Republic of); Kwon, Soon-Yong, E-mail: [School of Materials Science and Engineering & Low-Dimensional Carbon Materials Center, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of)


    Indium tin oxide-free, flexible transparent electrodes (TEs) are crucial for the future commercialization of flexible and wearable electronics. While carbon-based TEs containing carbon nanotube (CNT) networks show promise, they usually exhibit poor dispersion properties, limiting their performance and practicality. In this study, we report a highly efficient and bending durable all-carbon composite TE (ac-TE) that employs uniform CNT networks on a monolayer graphene/polyethylene terephthalate (PET) substrate via a simple air spray deposition method. The air-sprayed CNT/graphene assembly was free-standing on solution, making a polymer-free transfer of carbon composites to target substrates possible. The excellent performance of the ac-TEs was attributed to the uniformly networked CNTs on the polycrystalline graphene with a well-controlled density, effectively bridging the line defects and filling the tears/voids or folds necessarily existing in the as-processed graphene. The sheet resistance of the ac-TEs was increased only 6% from its original value at a bending radius of 2.7 mm, while that of the pristine graphene/PET assembly increased 237%. Mechanical bending of the ac-TEs worsened the electrical performance by only ∼1.7% after 2000 bending cycles at a bending radius of 2.5 mm. Degradation of the performance by the bending was the result of line defects formation in the graphene, demonstrating the potential of the uniform CNT networks to achieve more efficient and flexible carbon-based TEs. Furthermore, the chemically-doped ac-TEs showed commercially suitable electronic and optical properties with much enhanced thermal stability, closer to practical TEs in flexible devices. - Highlights: • Highly efficient and bending durable all-carbon composite transparent electrodes (TEs) are designed. • The performance was strongly dependent on morphology of CNT networks on graphene. • The mechanism relies on the defect reductions in graphene by uniform CNT coating

  19. Weaving a knowledge network for Deep Carbon Science (United States)

    Ma, Xiaogang; West, Patrick; Zednik, Stephan; Erickson, John; Eleish, Ahmed; Chen, Yu; Wang, Han; Zhong, Hao; Fox, Peter


    Geoscience researchers are increasingly dependent on informatics and the Web to conduct their research. Geoscience is one of the first domains that take lead in initiatives such as open data, open code, open access, and open collections, which comprise key topics of Open Science in academia. The meaning of being open can be understood at two levels. The lower level is to make data, code, sample collections and publications, etc. freely accessible online and allow reuse, modification and sharing. The higher level is the annotation and connection between those resources to establish a network for collaborative scientific research. In the data science component of the Deep Carbon Observatory (DCO), we have leveraged state-of-the-art information technologies and existing online resources to deploy a web portal for the over 1000 researchers in the DCO community. An initial aim of the portal is to keep track of all research and outputs related to the DCO community. Further, we intend for the portal to establish a knowledge network, which supports various stages of an open scientific process within and beyond the DCO community. Annotation and linking are the key characteristics of the knowledge network. Not only are key assets, including DCO data and methods, published in an open and inter-linked fashion, but the people, organizations, groups, grants, projects, samples, field sites, instruments, software programs, activities, meetings, etc. are recorded and connected to each other through relationships based on well-defined, formal conceptual models. The network promotes collaboration among DCO participants, improves the openness and reproducibility of carbon-related research, facilitates accreditation to resource contributors, and eventually stimulates new ideas and findings in deep carbon-related studies.

  20. Cloud networking understanding cloud-based data center networks

    CERN Document Server

    Lee, Gary


    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

  1. A Single-Walled Carbon Nanotube Network Gas Sensing Device

    Directory of Open Access Journals (Sweden)

    I-Ju Teng


    Full Text Available The goal of this research was to develop a chemical gas sensing device based on single-walled carbon nanotube (SWCNT networks. The SWCNT networks are synthesized on Al2O3-deposted SiO2/Si substrates with 10 nm-thick Fe as the catalyst precursor layer using microwave plasma chemical vapor deposition (MPCVD. The development of interconnected SWCNT networks can be exploited to recognize the identities of different chemical gases by the strength of their particular surface adsorptive and desorptive responses to various types of chemical vapors. The physical responses on the surface of the SWCNT networks cause superficial changes in the electric charge that can be converted into electronic signals for identification. In this study, we tested NO2 and NH3 vapors at ppm levels at room temperature with our self-made gas sensing device, which was able to obtain responses to sensitivity changes with a concentration of 10 ppm for NO2 and 24 ppm for NH3.

  2. Scaling of dissolved organic carbon removal in river networks (United States)

    Bertuzzo, Enrico; Helton, Ashley M.; Hall, , Robert O.; Battin, Tom J.


    Streams and rivers play a major role in the global carbon cycle as they collect, transform and deliver terrestrial organic carbon to the ocean. The rate of dissolved organic carbon (DOC) removal depends on hydrological factors (primarily water depth and residence time) that change predictably within the river network and local DOC concentration and composition is the result of transformation and removal processes in the whole upstream catchment. We thus combine theory of the form and scaling of river networks with a model of DOC removal from streamwater to investigate how the structure of river networks and the related hydrological drivers control DOC dynamics. We find that minimization of energy dissipation, the physical process that shapes the topological and metric properties of river networks, leads to structures that are more efficient in terms of total DOC removal per unit of streambed area. River network structure also induces a scaling of the DOC mass flux with the contributing area that does not depend on the particular network used for the simulation and is robust to spatial heterogeneity of model parameters. Such scaling enables the derivation of removal patterns across a river network in terms of clearly identified biological, hydrological and geomorphological factors. In particular, we derive how the fraction of terrestrial DOC load removed by the river network scales with the catchment area and with the area of a region drained by multiple river networks. Such results further our understanding of the impact of streams and rivers on carbon cycling at large scales.

  3. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz


    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  4. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz


    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  5. Carbon nanostructures and networks produced by chemical vapor deposition

    NARCIS (Netherlands)

    Kowlgi, N.K.K.; Koper, G.J.M.; Van Raalten, R.A.D.


    The invention pertains to a method for manufacturing crystalline carbon nanostructures and/or a network of crystalline carbon nanostructures, comprising: (i) providing a bicontinuous micro-emulsion containing metal nanoparticles having an average particle size between 1and 100nm; (ii) bringing said

  6. A Pentagon Based Carbon Sheet (United States)

    Wang, Qian; Zhang, Shunhong; Zhou, Jian; Chen, Xiaoshuang; Kawazoe, Yoshiyuki; Jena, Puru; A international Team Collaboration


    A new two-dimensional (2D) meta-stable carbon allotrope, penta-graphene, composed entirely of carbon pentagons and resembling the Cairo pentagonal tiling, is proposed. State-of-the-art theoretical calculations confirm that the new carbon polymorph is not only dynamically and mechanically stable, but also can withstand temperatures as high as 1000 K. Due to its unique atomic configuration penta-graphene has an unusual negative Poisson's ratio (NPR) and ultra-high ideal strength that can even outperform graphene. Furthermore, unlike graphene that needs to be functionalized for opening a band gap, penta-graphene possesses an intrinsic quasi-direct band gap as large as 3.25 eV - close to that of ZnO and GaN. Equally important, when rolled up, penta-graphene can form a pentagon-based nanotube. The resulting penta-carbon nanotubes are semiconducting regardless of their chirality. When stacked in different patterns, dynamically and thermally stable 3D twin structures of T12-carbon are generated with band gaps even larger than that of T12-carbon. The versatility of penta-graphene and its derivatives are expected to have broad applications in nanoelectronics and nanomechanics. Peking University.

  7. Accessibility, searchability, transparency and engagement of soil carbon data: The International Soil Carbon Network (United States)

    Harden, Jennifer W.; Hugelius, Gustaf; Koven, Charlie; Sulman, Ben; O'Donnell, Jon; He, Yujie


    Soils are capacitors for carbon and water entering and exiting through land-atmosphere exchange. Capturing the spatiotemporal variations in soil C exchange through monitoring and modeling is difficult in part because data are reported unevenly across spatial, temporal, and management scales and in part because the unit of measure generally involves destructive harvest or non-recurrent measurements. In order to improve our fundamental basis for understanding soil C exchange, a multi-user, open source, searchable database and network of scientists has been formed. The International Soil Carbon Network (ISCN) is a self-chartered, member-based and member-owned network of scientists dedicated to soil carbon science. Attributes of the ISCN include 1) Targeted ISCN Action Groups which represent teams of motivated researchers that propose and pursue specific soil C research questions with the aim of synthesizing seminal articles regarding soil C fate. 2) Datasets to date contributed by institutions and individuals to a comprehensive, searchable open-access database that currently includes over 70,000 geolocated profiles for which soil C and other soil properties. 3) Derivative products resulting from the database, including depth attenuation attributes for C concentration and storage; C storage maps; and model-based assessments of emission/sequestration for future climate scenarios. Several examples illustrate the power of such a database and its engagement with the science community. First, a simplified, data-constrained global ecosystem model estimated a global sensitivity of permafrost soil carbon to climate change (g sensitivity) of -14 to -19 Pg C °C-1 of warming on a 100 years time scale. Second, using mathematical characterizations of depth profiles for organic carbon storage, C at the soil surface reflects Net Primary Production (NPP) and its allotment as moss or litter, while e-folding depths are correlated to rooting depth. Third, storage of deep C is highly

  8. Ecological network analysis for a low-carbon and high-tech industrial park. (United States)

    Lu, Yi; Su, Meirong; Liu, Gengyuan; Chen, Bin; Zhou, Shiyi; Jiang, Meiming


    Industrial sector is one of the indispensable contributors in global warming. Even if the occurrence of ecoindustrial parks (EIPs) seems to be a good improvement in saving ecological crises, there is still a lack of definitional clarity and in-depth researches on low-carbon industrial parks. In order to reveal the processes of carbon metabolism in a low-carbon high-tech industrial park, we selected Beijing Development Area (BDA) International Business Park in Beijing, China as case study, establishing a seven-compartment- model low-carbon metabolic network based on the methodology of Ecological Network Analysis (ENA). Integrating the Network Utility Analysis (NUA), Network Control Analysis (NCA), and system-wide indicators, we compartmentalized system sectors into ecological structure and analyzed dependence and control degree based on carbon metabolism. The results suggest that indirect flows reveal more mutuality and exploitation relation between system compartments and they are prone to positive sides for the stability of the whole system. The ecological structure develops well as an approximate pyramidal structure, and the carbon metabolism of BDA proves self-mutualistic and sustainable. Construction and waste management were found to be two active sectors impacting carbon metabolism, which was mainly regulated by internal and external environment.

  9. Carbon Nanostructure-Based Sensors


    Sarkar, Tapan


    One-dimensional (1-D) nanostructure-based sensors provide better sensitivity as compared to conventional thin film-based sensors due to their comparable dimensions with respect to Debye length. Single-walled carbon nanotubes (SWNTs) are 1-D nanostructures having high electrical mobility, high mechanical strength and high specific surface area that facilitate building of low-power, ultrahigh density sensors within limited space. However, pristine SWNTs posses limited sensitivity and selectivit...

  10. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L


    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  11. Can a wearable strain sensor based on a carbon nanotube network be an alternative to an isokinetic dynamometer for the measurement of knee-extensor muscle strength? (United States)

    Benlikaya, Ruhan; Ege, Yavuz; Pündük, Zekine; Slobodian, Petr; Meriç, Gökhan


    This study aimed to find out whether a wearable strain sensor including thermoplastic polyurethane composite with a multi-walled carbon nanotube network could be a viable alternative to an isokinetic dynamometer for the measurement of knee-extensor muscle strength. For the first time, the voltage-torque and angle-time relations of the sensor were determined to allow a comparison between the angle-dependent torque changes of the dynamometer and the sensor. This comparison suggested that the torque-angle relations of the dynamometer and the sensor did not have the same characteristics. In this regard, the sensor may be used in the torque measurements due to the moderate correlation between the torque values determined via the isokinetic dynamometer and the sensor and due to the significant difference between low and high torque values of the sensor. By the same token, the torque-angle graph of the sensor may be more informative than that of the dynamometer in evaluation of knee problems.

  12. Constraining spatial patterns and secular trends of springtime phenology with contrasting models based on plant phenology gardens and carbon dioxide flux networks (United States)

    White, M. A.; Baldocchi, D. D.; Schwartz, M. D.


    Shifts in the timing and distribution of spring phenological events are a central feature of global change research. Most evidence, especially for multi-decade records, indicates a shift towards earlier spring but with frequent differences in the magnitude and location of trends. Here, using two phenology models, one based on first bloom dates of clonal honeysuckle and lilac and one based on initiation of net carbon uptake at eddy covariance flux towers, we upscaled observations of spring arrival to the conterminous US at 1km resolution. The models shared similar and coherent spatial and temporal patterns at large regional scales but differed at smaller scales, likely attributable to: use of cloned versus extant species; chilling requirements; model complexity; and biome characteristics. Our results constrain climatically driven shifts in 1981 to 2003 spring arrival for the conterminous US to between -2.7 and 0.1 day/23 years. Estimated trend differences were minor in the biome of model development (deciduous broad leaf forest) but diverged strongly in woody evergreen and grassland areas. Based on comparisons with the normalized difference vegetation index (NDVI) and a limited independent ground dataset, predictions from both models were consistent with observations of satellite-based greenness and measured leaf expansion. First bloom trends, which were mostly statistically insignificant, were also consistent with NDVI trends while the net carbon uptake model predicted extensive trends towards earlier spring in the western US that were not observed in the NDVI data, showing the implication of model application outside the biome range of initial development.

  13. A modal analysis of carbon nanotube using elastic network model

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Hyeok; Seo, Sang Jae; Lim, Byeong Soo; Choi, Jae Boong; Kim, Moon Ki [Sungkyunkwan Univ., Suwon (Korea, Republic of); Liu, Wing Kam [Northwestern Univ., Evanston (United States)


    Although it is widely known that both size and chirality play significant roles in vibration behaviors of single walled carbon nanotubes (SWCNTs), there haven't been yet enough studies specifying the relationship between structure and vibration mode shape of SWCNTs. We have analyzed the chirality and length dependence of SWCNT by using normal mode analysis based elastic network model in which all interatomic interactions of the given SWCNTs structure are represented by a network of linear spring connections. As this method requires relatively short computation time compared to molecular dynamics simulation, we can efficiently analyze vibration behavior of SWCNTs. To ensure the relationship between SWCNT structure and its vibration mode shapes, we simulated more than one hundred SWCNTs having different types of chirality and length. Results indicated that the first two major mode shapes are bending and breathing. The minimum length of nanotube for maintaining the bending mode does not depend on chirality but on its diameter. Our simulations pointed out that there is a critical aspect ratio between diameter and length to determine vibration mode shapes, and it can be empirically formulated as a function of nanotube length and diameter. Therefore, uniformity control is the most important premise in order to utilize vibration features of SWCNTs. It is also expected that the obtained vibration aspect will play an important role in designing nanotube based devices such as resonators and sensors more accurately.

  14. Cooperative water network system to reduce carbon footprint. (United States)

    Lim, Seong-Rin; Park, Jong Moon


    Much effort has been made in reducing the carbon footprint to mitigate climate change. However, water network synthesis has been focused on reducing the consumption and cost of freshwater within each industrial plant. The objective of this study is to illustrate the necessity of the cooperation of industrial plants to reduce the total carbon footprint of their water supply systems. A mathematical optimization model to minimize global warming potentials is developed to synthesize (1) a cooperative water network system (WNS) integrated over two plants and (2) an individual WNS consisting of two WNSs separated for each plant. The cooperative WNS is compared to the individual WNS. The cooperation reduces their carbon footprint and is economically feasible and profitable. A strategy for implementing the cooperation is suggested for the fair distribution of costs and benefits. As a consequence, industrial plants should cooperate with their neighbor plants to further reduce the carbon footprint.

  15. A Multiperiod Supply Chain Network Design Considering Carbon Emissions

    Directory of Open Access Journals (Sweden)

    Yang Peng


    Full Text Available This paper introduces a mixed integer linear programming formulation for modeling and solving a multiperiod one-stage supply chain distribution network design problem. The model is aimed to minimize two objectives, the total supply chain cost and the greenhouse gas emissions generated mainly by transportation and warehousing operations. The demand forecast is known for the planning horizon and shortage of demand is allowed at a penalty cost. This scenario must satisfy a minimum service level. Two carbon emission regulatory policies are investigated, the tax or carbon credit and the carbon emission cap. Computational experiments are performed to analyze the trade-offs between the total cost of the supply chain, the carbon emission quantity, and both carbon emission regulatory policies. Results demonstrate that for a certain range the carbon credit price incentivizes the reduction of carbon emissions to the environment. On the other hand, modifying the carbon emission cap inside a certain range could lead to significant reductions of carbon emission while not significantly compromising the total cost of the supply chain.

  16. Polymer-Assisted Direct Deposition of Uniform Carbon Nanotube Bundle Networks for High Performance Transparent Electrodes

    KAUST Repository

    Hellstrom, Sondra L.


    Flexible transparent electrodes are crucial for touch screen, flat panel display, and solar cell technologies. While carbon nanotube network electrodes show promise, characteristically poor dispersion properties have limited their practicality. We report that addition of small amounts of conjugated polymer to nanotube dispersions enables straightforward fabrication of uniform network electrodes by spin-coating and simultaneous tuning of parameters such as bundle size and density. After treatment in thionyl chloride, electrodes have sheet resistances competitive with other reported carbon nanotube based transparent electrodes to date. © 2009 American Chemical Society.

  17. Investigations of Carbon Nanotube Networks for use as Transparent Conductors (United States)

    Topinka, Mark


    Recently there has been increasing interest in the physics of conduction through carbon nanotube networks and the possibility of using carbon nanotube networks as transparent conducting layers for solar cells and other optoelectronic applications(1). Conductivities as high as 30 ohm/square with transparencies of about 80% have been reported(2). Here we present results of our work on understanding the underlying physics behind the real-world behavior of these systems and identifying the bottlenecks which are currently limiting their performance. We focus in particular on their possible use in solar cells as a low-cost alternative to more expensive transparent conductor technologies such as Indium Tin Oxide (ITO). We include numerical simulations of conduction through nanotube networks and scanning probe microscopy studies of transport through these systems. (1) L.Hu, D.S.Hecht, G.Gruner, NanoLetters 4, 2513 (2) Z.Wu, et al, Science 305, 1273

  18. Comparison of QSAR models based on combinations of genetic algorithm, stepwise multiple linear regression, and artificial neural network methods to predict Kd of some derivatives of aromatic sulfonamides as carbonic anhydrase II inhibitors. (United States)

    Maleki, Afshin; Daraei, Hiua; Alaei, Loghman; Faraji, Aram


    Four stepwise multiple linear regressions (SMLR) and a genetic algorithm (GA) based multiple linear regressions (MLR), together with artificial neural network (ANN) models, were applied for quantitative structure-activity relationship (QSAR) modeling of dissociation constants (Kd) of 62 arylsulfonamide (ArSA) derivatives as human carbonic anhydrase II (HCA II) inhibitors. The best subsets of molecular descriptors were selected by SMLR and GA-MLR methods. These selected variables were used to generate MLR and ANN models. The predictability power of models was examined by an external test set and cross validation. In addition, some tests were done to examine other aspects of the models. The results show that for certain purposes GA-MLR is better than SMLR and for others, ANN overcomes MLR models.

  19. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg


    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  20. CNEM: Cluster Based Network Evolution Model

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani


    Full Text Available This paper presents a network evolution model, which is based on the clustering approach. The proposed approach depicts the network evolution, which demonstrates the network formation from individual nodes to fully evolved network. An agglomerative hierarchical clustering method is applied for the evolution of network. In the paper, we present three case studies which show the evolution of the networks from the scratch. These case studies include: terrorist network of 9/11 incidents, terrorist network of WMD (Weapons Mass Destruction plot against France and a network of tweets discussing a topic. The network of 9/11 is also used for evaluation, using other social network analysis methods which show that the clusters created using the proposed model of network evolution are of good quality, thus the proposed method can be used by law enforcement agencies in order to further investigate the criminal networks

  1. Percolated carbon nanotube networks for high-speed humidity sensors. (United States)

    Choi, Woo Suk; Jung, Kyung Hoon; Hong, Hyun Pyo; Lee, Myung Jin; Min, Nam Ki


    Improving the response time for polyimide (PI)-based capacitive humidity sensors is critical for real-time sensing. Multi-walled carbon nanotube (MWCNT) films were used to form the upper electrode of humidity sensor to realize an extremely short response times. MWCNT films were spray-deposited on a moisture-sensitive PI layer and subsequently patterned by oxygen plasma. Random-network MWCNT electrodes have a well-entangled and open porous structure that is almost impossible to obtain with conventional metal electrodes. Compared with porous metal electrode-based sensors as an upper electrode, the fabricated capacitive humidity sensors with MWCNT electrodes showed an exceptionally short response time of less than 2.5 s and a good linearity of 0.998. An analysis of the long-term (100 days) stability data revealed that the MWCNT electrode humidity sensors showed little drift even after 100 days aging, indicating that they are suitable for practical and reliable humidity measurements. These improvements in performance may stem from their interconnected microscopic porous structure, which is more accessible to water molecules through the conductive electrode.

  2. Electron percolation in realistic models of carbon nanotube networks (United States)

    Simoneau, Louis-Philippe; Villeneuve, Jérémie; Rochefort, Alain


    The influence of penetrable and curved carbon nanotubes (CNT) on the charge percolation in three-dimensional disordered CNT networks have been studied with Monte-Carlo simulations. By considering carbon nanotubes as solid objects but where the overlap between their electron cloud can be controlled, we observed that the structural characteristics of networks containing lower aspect ratio CNT are highly sensitive to the degree of penetration between crossed nanotubes. Following our efficient strategy to displace CNT to different positions to create more realistic statistical models, we conclude that the connectivity between objects increases with the hard-core/soft-shell radii ratio. In contrast, the presence of curved CNT in the random networks leads to an increasing percolation threshold and to a decreasing electrical conductivity at saturation. The waviness of CNT decreases the effective distance between the nanotube extremities, hence reducing their connectivity and degrading their electrical properties. We present the results of our simulation in terms of thickness of the CNT network from which simple structural parameters such as the volume fraction or the carbon nanotube density can be accurately evaluated with our more realistic models.

  3. Polymer-Based Carbon Monoxide Sensors (United States)

    Homer, M. L.; Shevade, A. V.; Zhou, H.; Kisor, A. K.; Lara, L. M.; Yen, S.-P. S.; Ryan, M. A.


    Polymer-based sensors have been used primarily to detect volatile organics and inorganics; they are not usually used for smaller, gas phase molecules. We report the development and use of two types of polymer-based sensors for the detection of carbon monoxide. Further understanding of the experimental results is also obtained by performing molecular modeling studies to investigate the polymer-carbon monoxide interactions. The first type is a carbon-black-polymer composite that is comprised of a non-conducting polymer base that has been impregnated with carbon black to make it conducting. These chemiresistor sensors show good response to carbon monoxide but do not have a long lifetime. The second type of sensor has a non-conducting polymer base but includes both a porphyrin-functionalized polypyrrole and carbon black. These sensors show good, repeatable and reversible response to carbon monoxide at room temperature.

  4. Carbon nanotubes based vacuum gauge (United States)

    Rudyk, N. N.; Il’in, O. I.; Il’ina, M. V.; Fedotov, A. A.; Klimin, V. S.; Ageev, O. A.


    We have created an ionization type Vacuum gauge with sensor element based on an array of vertically aligned carbon nanotubes. Obtained asymmetrical current-voltage characteristics at different voltage polarity on the electrode with the CNTs. It was found that when applying a negative potential on an electrode with the CNTs, the current in the gap is higher than at a positive potential. In the pressure range of 1 ÷ 103 Torr vacuum gauge sensitivity was 6 mV/Torr (at a current of 4.5·10-5 A) and in the range of 10-5 ÷ 1 Torr was 10 mV/Torr (at a current of 1.3·10-5 A). It is shown that the energy efficiency of vacuum gauge can be increased in the case where electrode with CNT operates as an emitter of electrons.

  5. Modeling economic and carbon consequences of a shift to wood-based energy in a rural 'cluster'; a network analysis in southeast Alaska (United States)

    David Saah; Trista Patterson; Thomas Buchholz; David Ganz; David Albert; Keith. Rush


    Integrated ecological and economic solutions are increasingly sought after by communities to provide basic energy needs such as home heating, transport, and electricity, while reducing drivers of and vulnerability to climate change. Small rural communities may require a coordinated approach to overcome the limitations of economies of scale. Low-carbon development...

  6. Carbon nanotube based hybrid nanocarbon foam (United States)

    Shahrizan Jamal, M.; Zhang, Mei


    Carbon nanotube (CNT) based nanocarbon foams (NFs) and the hybrid nanocarbon foams (HNFs) are fabricated in this work. The NFs are formed by using poly(methyl methacrylate) microspheres as a template to create micro-scaled pores. The cell walls are made of CNT networks with nano-scaled pores. The interconnections among CNTs are secured using graphene and nanographite generated via carbonization of polyacrylonitrile. The resulting NFs are ultra-lightweight, highly elastic, electrically and thermally conductive, and robust in structure. The HNFs are made by infiltrating thermoplastic polymer into the NFs in a controllable procedure. Compared to NFs, the HNFs have much higher strength, same electrical conductivity, and limited increase in density. The compressive strength of the HNF increased more than 50 times while the density was changed less than 10 times due to the polymer infiltration. It is found that the deformed HNFs can recover in both structure and property when they are heated over the glass transition temperature of the infiltrated polymer. Such remarkable healing capability could broaden the applications of the HNFs.

  7. Location-Based Services in Vehicular Networks (United States)

    Wu, Di


    Location-based services have been identified as a promising communication paradigm in highly mobile and dynamic vehicular networks. However, existing mobile ad hoc networking cannot be directly applied to vehicular networking due to differences in traffic conditions, mobility models and network topologies. On the other hand, hybrid architectures…

  8. Activated, coal-based carbon foam (United States)

    Rogers, Darren Kenneth; Plucinski, Janusz Wladyslaw


    An ablation resistant, monolithic, activated, carbon foam produced by the activation of a coal-based carbon foam through the action of carbon dioxide, ozone or some similar oxidative agent that pits and/or partially oxidizes the carbon foam skeleton, thereby significantly increasing its overall surface area and concurrently increasing its filtering ability. Such activated carbon foams are suitable for application in virtually all areas where particulate or gel form activated carbon materials have been used. Such an activated carbon foam can be fabricated, i.e. sawed, machined and otherwise shaped to fit virtually any required filtering location by simple insertion and without the need for handling the "dirty" and friable particulate activated carbon foam materials of the prior art.

  9. Scalable Approach To Construct Free-Standing and Flexible Carbon Networks for Lithium–Sulfur Battery

    KAUST Repository

    Li, Mengliu


    Reconstructing carbon nanomaterials (e.g., fullerene, carbon nanotubes (CNTs), and graphene) to multidimensional networks with hierarchical structure is a critical step in exploring their applications. Herein, a sacrificial template method by casting strategy is developed to prepare highly flexible and free-standing carbon film consisting of CNTs, graphene, or both. The scalable size, ultralight and binder-free characteristics, as well as the tunable process/property are promising for their large-scale applications, such as utilizing as interlayers in lithium-sulfur battery. The capability of holding polysulfides (i.e., suppressing the sulfur diffusion) for the networks made from CNTs, graphene, or their mixture is pronounced, among which CNTs are the best. The diffusion process of polysulfides can be visualized in a specially designed glass tube battery. X-ray photoelectron spectroscopy analysis of discharged electrodes was performed to characterize the species in electrodes. A detailed analysis of lithium diffusion constant, electrochemical impedance, and elementary distribution of sulfur in electrodes has been performed to further illustrate the differences of different carbon interlayers for Li-S batteries. The proposed simple and enlargeable production of carbon-based networks may facilitate their applications in battery industry even as a flexible cathode directly. The versatile and reconstructive strategy is extendable to prepare other flexible films and/or membranes for wider applications.

  10. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der


    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  11. Characterization of electrospun lignin based carbon fibers (United States)

    Poursorkhabi, Vida; Mohanty, Amar; Misra, Manjusri


    The production of lignin fibers has been studied in order to replace the need for petroleum based precursors for carbon fiber production. In addition to its positive environmental effects, it also benefits the economics of the industries which cannot take advantage of carbon fiber properties because of their high price. A large amount of lignin is annually produced as the byproduct of paper and growing cellulosic ethanol industry. Therefore, finding high value applications for this low cost, highly available material is getting more attention. Lignin is a biopolymer making about 15 - 30 % of the plant cell walls and has a high carbon yield upon carbonization. However, its processing is challenging due to its low molecular weight and also variations based on its origin and the method of separation from cellulose. In this study, alkali solutions of organosolv lignin with less than 1 wt/v% of poly (ethylene oxide) and two types of lignin (hardwood and softwood) were electrospun followed by carbonization. Different heating programs for carbonization were tested. The carbonized fibers had a smooth surface with an average diameter of less than 5 µm and the diameter could be controlled by the carbonization process and lignin type. Scanning electron microscopy (SEM) was used to study morphology of the fibers before and after carbonization. Thermal conductivity of a sample with amorphous carbon was 2.31 W/m.K. The electrospun lignin carbon fibers potentially have a large range of application such as in energy storage devices and water or gas purification systems.

  12. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    The availability of location information in mobile devices, e.g., through built-in GPS receivers in smart phones, has motivated the investigation of the usefulness of location based network optimizations. Since the quality of input information is important for network optimizations, a main focus...... of this work is to evaluate how location based network optimizations are affected by varying quality of input information such as location information and user movements. The first contribution in this thesis concerns cooperative network-based localization systems. The investigations focus on assessing...... the achievable accuracy of future localization system in mobile settings, as well as quantifying the impact of having a realistic model of the required measurement exchanges. Secondly, this work has considered different large scale and small scale location based network optimizations, namely centralized relay...

  13. Carbon-based Fuel Cell

    Energy Technology Data Exchange (ETDEWEB)

    Steven S. C. Chuang


    The direct use of coal in the solid oxide fuel cell to generate electricity is an innovative concept for power generation. The C-fuel cell (carbon-based fuel cell) could offer significant advantages: (1) minimization of NOx emissions due to its operating temperature range of 700-1000 C, (2) high overall efficiency because of the direct conversion of coal to CO{sub 2}, and (3) the production of a nearly pure CO{sub 2} exhaust stream for the direct CO{sub 2} sequestration. The objective of this project is to determine the technical feasibility of using a highly active anode catalyst in a solid oxide fuel for the direct electrochemical oxidation of coal to produce electricity. Results of this study showed that the electric power generation from Ohio No 5 coal (Lower Kittanning) Seam, Mahoning County, is higher than those of coal gas and pure methane on a solid oxide fuel cell assembly with a promoted metal anode catalyst at 950 C. Further study is needed to test the long term activity, selectivity, and stability of anode catalysts.

  14. A Quantum Cryptography Communication Network Based on Software Defined Network

    Directory of Open Access Journals (Sweden)

    Zhang Hongliang


    Full Text Available With the development of the Internet, information security has attracted great attention in today’s society, and quantum cryptography communication network based on quantum key distribution (QKD is a very important part of this field, since the quantum key distribution combined with one-time-pad encryption scheme can guarantee the unconditional security of the information. The secret key generated by quantum key distribution protocols is a very valuable resource, so making full use of key resources is particularly important. Software definition network (SDN is a new type of network architecture, and it separates the control plane and the data plane of network devices through OpenFlow technology, thus it realizes the flexible control of the network resources. In this paper, a quantum cryptography communication network model based on SDN is proposed to realize the flexible control of quantum key resources in the whole cryptography communication network. Moreover, we propose a routing algorithm which takes into account both the hops and the end-to-end availible keys, so that the secret key generated by QKD can be used effectively. We also simulate this quantum cryptography communication network, and the result shows that based on SDN and the proposed routing algorithm the performance of this network is improved since the effective use of the quantum key resources.

  15. A Network Coding Based Routing Protocol for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xin Guan


    Full Text Available Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs. Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR.We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.

  16. A network coding based routing protocol for underwater sensor networks. (United States)

    Wu, Huayang; Chen, Min; Guan, Xin


    Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.


    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari


    Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

  18. Inference of Gene Regulatory Network Based on Local Bayesian Networks. (United States)

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan


    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  19. Toward a Mexican eddy covariance network for carbon cycle science (United States)

    Vargas, Rodrigo; Yépez, Enrico A.


    First Annual MexFlux Principal Investigators Meeting; Hermosillo, Sonora, Mexico, 4-8 May 2011; The carbon cycle science community has organized a global network, called FLUXNET, to measure the exchange of energy, water, and carbon dioxide (CO2) between the ecosystems and the atmosphere using the eddy covariance technique. This network has provided unprecedented information for carbon cycle science and global climate change but is mostly represented by study sites in the United States and Europe. Thus, there is an important gap in measurements and understanding of ecosystem dynamics in other regions of the world that are seeing a rapid change in land use. Researchers met under the sponsorship of Red Temática de Ecosistemas and Consejo Nacional de Ciencia y Tecnologia (CONACYT) to discuss strategies to establish a Mexican eddy covariance network (MexFlux) by identifying researchers, study sites, and scientific goals. During the meeting, attendees noted that 10 study sites have been established in Mexico with more than 30 combined years of information. Study sites span from new sites installed during 2011 to others with 9 to 6 years of measurements. Sites with the longest span measurements are located in Baja California Sur (established by Walter Oechel in 2002) and Sonora (established by Christopher Watts in 2005); both are semiarid ecosystems. MexFlux sites represent a variety of ecosystem types, including Mediterranean and sarcocaulescent shrublands in Baja California; oak woodland, subtropical shrubland, tropical dry forest, and a grassland in Sonora; tropical dry forests in Jalisco and Yucatan; a managed grassland in San Luis Potosi; and a managed pine forest in Hidalgo. Sites are maintained with an individual researcher's funds from Mexican government agencies (e.g., CONACYT) and international collaborations, but no coordinated funding exists for a long-term program.

  20. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou


    Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.

  1. Predicting Carbonation Depth of Prestressed Concrete under Different Stress States Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Chunhua Lu


    Full Text Available Two artificial neural networks (ANN, back-propagation neural network (BPNN and the radial basis function neural network (RBFNN, are proposed to predict the carbonation depth of prestressed concrete. In order to generate the training and testing data for the ANNs, an accelerated carbonation experiment was carried out, and the influence of stress level of concrete on carbonation process was taken into account especially. Then, based on the experimental results, the BPNN and RBFNN models which all take the stress level of concrete, water-cement ratio, cement-fine aggregate, cement-coarse aggregate ratio and testing age as input parameters were built and all the training and testing work was performed in MATLAB. It can be found that the two ANN models seem to have a high prediction and generalization capability in evaluation of carbonation depth, and the largest absolute percentage errors of BPNN and RBFNN are 10.88% and 8.46%, respectively. The RBFNN model shows a better prediction precision in comparison to BPNN model.

  2. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira


    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  3. Antimicrobial Activity of Carbon-Based Nanoparticles

    Directory of Open Access Journals (Sweden)

    Solmaz Maleki Dizaj


    Full Text Available Due to the vast and inappropriate use of the antibiotics, microorganisms have begun to develop resistance to the commonly used antimicrobial agents. So therefore, development of the new and effective antimicrobial agents seems to be necessary. According to some recent reports, carbon-based nanomaterials such as fullerenes, carbon nanotubes (CNTs (especially single-walled carbon nanotubes (SWCNTs and graphene oxide (GO nanoparticles show potent antimicrobial properties. In present review, we have briefly summarized the antimicrobial activity of carbon-based nanoparticles together with their mechanism of action. Reviewed literature show that the size of carbon nanoparticles plays an important role in the inactivation of the microorganisms. As major mechanism, direct contact of microorganisms with carbon nanostructures seriously affects their cellular membrane integrity, metabolic processes and morphology. The antimicrobial activity of carbon-based nanostructures may interestingly be investigated in the near future owing to their high surface/volume ratio, large inner volume and other unique chemical and physical properties. In addition, application of functionalized carbon nanomaterials as carriers for the ordinary antibiotics possibly will decrease the associated resistance, enhance their bioavailability and provide their targeted delivery.

  4. The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring

    National Research Council Canada - National Science Library

    Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai


    .... In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus...

  5. Network Medicine: A Network-based Approach to Human Diseases (United States)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  6. Fermentation based carbon nanotube multifunctional bionic composites

    National Research Council Canada - National Science Library

    Valentini, Luca; Bon, Silvia Bittolo; Signetti, Stefano; Tripathi, Manoj; Iacob, Erica; Pugno, Nicola M


    .... Based on bread fermentation, a bionic composite made of carbon nanotubes (CNTs) and a single-cell fungi, the Saccharomyces cerevisiae yeast extract, was prepared by fermentation of such microorganisms at room temperature...

  7. Carbon nanoparticle-based fluorescent bioimaging probes

    National Research Council Canada - National Science Library

    Bhunia, Susanta Kumar; Saha, Arindam; Maity, Amit Ranjan; Ray, Sekhar C; Jana, Nikhil R


    ... metals have severely limited the application potential of these nanocrystals. Here, we report a fluorescent carbon nanoparticle-based, alternative, nontoxic imaging probe that is suitable for biological staining and diagnostics...

  8. Network repair based on community structure (United States)

    Wang, Tianyu; Zhang, Jun; Sun, Xiaoqian; Wandelt, Sebastian


    Real-world complex systems are often fragile under disruptions. Accordingly, research on network repair has been studied intensively. Recently proposed efficient strategies for network disruption, based on collective influence, call for more research on efficient network repair strategies. Existing strategies are often designed to repair networks with local information only. However, the absence of global information impedes the creation of efficient repairs. Motivated by this limitation, we propose a concept of community-level repair, which leverages the community structure of the network during the repair process. Moreover, we devise a general framework of network repair, with in total six instances. Evaluations on real-world and random networks show the effectiveness and efficiency of the community-level repair approaches, compared to local and random repairs. Our study contributes to a better understanding of repair processes, and reveals that exploitation of the community structure improves the repair process on a disrupted network significantly.

  9. Characterization of electrospun lignin based carbon fibers

    Energy Technology Data Exchange (ETDEWEB)

    Poursorkhabi, Vida; Mohanty, Amar; Misra, Manjusri [School of Engineering, Thornbrough Building, University of Guelph, Guelph, N1G 2W1, Ontario (Canada); Bioproducts Discovery and Development Centre, Department of Plant Agriculture, Crop Science Building, University of Guelph, Guelph, N1G 2W1, Ontario (Canada)


    The production of lignin fibers has been studied in order to replace the need for petroleum based precursors for carbon fiber production. In addition to its positive environmental effects, it also benefits the economics of the industries which cannot take advantage of carbon fiber properties because of their high price. A large amount of lignin is annually produced as the byproduct of paper and growing cellulosic ethanol industry. Therefore, finding high value applications for this low cost, highly available material is getting more attention. Lignin is a biopolymer making about 15 – 30 % of the plant cell walls and has a high carbon yield upon carbonization. However, its processing is challenging due to its low molecular weight and also variations based on its origin and the method of separation from cellulose. In this study, alkali solutions of organosolv lignin with less than 1 wt/v% of poly (ethylene oxide) and two types of lignin (hardwood and softwood) were electrospun followed by carbonization. Different heating programs for carbonization were tested. The carbonized fibers had a smooth surface with an average diameter of less than 5 µm and the diameter could be controlled by the carbonization process and lignin type. Scanning electron microscopy (SEM) was used to study morphology of the fibers before and after carbonization. Thermal conductivity of a sample with amorphous carbon was 2.31 W/m.K. The electrospun lignin carbon fibers potentially have a large range of application such as in energy storage devices and water or gas purification systems.

  10. Glassy carbon based supercapacitor stacks

    Energy Technology Data Exchange (ETDEWEB)

    Baertsch, M.; Braun, A.; Koetz, R.; Haas, O. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)


    Considerable effort is being made to develop electrochemical double layer capacitors (EDLC) that store relatively large quantities of electrical energy and possess at the same time a high power density. Our previous work has shown that glassy carbon is suitable as a material for capacitor electrodes concerning low resistance and high capacity requirements. We present the development of bipolar electrochemical glassy carbon capacitor stacks of up to 3 V. Bipolar stacks are an efficient way to meet the high voltage and high power density requirements for traction applications. Impedance and cyclic voltammogram measurements are reported here and show the frequency response of a 1, 2, and 3 V stack. (author) 3 figs., 1 ref..

  11. Community Based Networks and 5G

    DEFF Research Database (Denmark)

    Williams, Idongesit


    is hinged on a research aimed at understanding how and why Community Based Networks deploy telecom and Broadband infrastructure. The study was a qualitative study carried out inductively using Grounded Theory. Six cases were investigated.Two Community Based Network Mobilization models were identified......The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

  12. Functional Carbon Nanotube/Mesoporous Carbon/MnO2 Hybrid Network for High-Performance Supercapacitors

    Directory of Open Access Journals (Sweden)

    Tao Tao


    Full Text Available A functional carbon nanotube/mesoporous carbon/MnO2 hybrid network has been developed successfully through a facile route. The resulting composites exhibited a high specific capacitance of 351 F/g at 1 A g−1, with intriguing charge/discharge rate performance and cycling stability due to a synergistic combination of large surface area and excellent electron-transport capabilities of MnO2 with the good conductivity of the carbon nanotube/mesoporous carbon networks. Such composite shows great potential to be used as electrodes for supercapacitors.

  13. Lithography-free fabrication of carbon nanotube network transistors

    Energy Technology Data Exchange (ETDEWEB)

    Timmermans, Marina Y; Nasibulin, Albert G; Kauppinen, Esko I [NanoMaterials Group, Department of Applied Physics and Center for New Materials, Aalto University School of Science and Technology, PO Box 15100, 00076 Aalto (Finland); Grigoras, Kestutis; Franssila, Sami [Microfabrication Group, Department of Materials Science and Engineering, Aalto University School of Science and Technology, PL 13000, 00076 Aalto (Finland); Hurskainen, Ville; Ermolov, Vladimir, E-mail:, E-mail: [Nokia Research Center, Itaemerenkatu 9, 00180 Helsinki (Finland)


    A novel non-lithographic technique for the fabrication of carbon nanotube thin film transistors is presented. The whole transistor fabrication process requires only one mask which is used both to pattern transistor channels based on aerosol synthesized carbon nanotubes and to deposit electrodes by metal evaporation at different angles. An important effect of electrodynamic focusing was utilized for the directed assembly of transistor channels with feature sizes smaller than the mask openings. This dry non-lithographic method opens up new avenues for device fabrication especially for low cost flexible and transparent electronics.

  14. Analysis of the transmission characteristics of China's carbon market transaction price volatility from the perspective of a complex network. (United States)

    Jia, Jingjing; Li, Huajiao; Zhou, Jinsheng; Jiang, Meihui; Dong, Di


    Research on the price fluctuation transmission of the carbon trading pilot market is of great significance for the establishment of China's unified carbon market and its development in the future. In this paper, the carbon market transaction prices of Beijing, Shanghai, Tianjin, Shenzhen, and Guangdong were selected from December 29, 2013 to March 26, 2016, as sample data. Based on the view of the complex network theory, we construct a price fluctuation transmission network model of five pilot carbon markets in China, with the purposes of analyzing the topological features of this network, including point intensity, weighted clustering coefficient, betweenness centrality, and community structure, and elucidating the characteristics and transmission mechanism of price fluctuation in China's five pilot cities. The results of point intensity and weighted clustering coefficient show that the carbon prices in the five markets remained unchanged and transmitted smoothly in general, and price fragmentation is serious; however, at some point, the price fluctuates with mass phenomena. The result of betweenness centrality reflects that a small number of price fluctuations can control the whole market carbon price transmission and price fluctuation evolves in an alternate manner. The study provides direction for the scientific management of the carbon price. Policy makers should take a positive role in promoting market activity, preventing the risks that may arise from mass trade and scientifically forecasting the volatility of trading prices, which will provide experience for the establishment of a unified carbon market in China.

  15. Smart Cellulose Fibers Coated with Carbon Nanotube Networks

    Directory of Open Access Journals (Sweden)

    Haisong Qi


    Full Text Available Smart multi-walled carbon nanotube (MWCNT-coated cellulose fibers with a unique sensing ability were manufactured by a simple dip coating process. The formation of electrically-conducting MWCNT networks on cellulose mono- and multi-filament fiber surfaces was confirmed by electrical resistance measurements and visualized by scanning electron microscopy. The interaction between MWCNT networks and cellulose fiber was investigated by Raman spectroscopy. The piezoresistivity of these fibers for strain sensing was investigated. The MWCNT-coated cellulose fibers exhibited a unique linear strain-dependent electrical resistance change up to 18% strain, with good reversibility and repeatability. In addition, the sensing behavior of these fibers to volatile molecules (including vapors of methanol, ethanol, acetone, chloroform and tetrahydrofuran was investigated. The results revealed a rapid response, high sensitivity and good reproducibility for these chemical vapors. Besides, they showed good selectivity to different vapors. It is suggested that the intrinsic physical and chemical features of cellulose fiber, well-formed MWCNT networks and favorable MWCNT-cellulose interaction caused the unique and excellent sensing ability of the MWCNT-coated cellulose fibers, which have the potential to be used as smart materials.

  16. Outcome-based Carbon Sequestration Resource Assessment (United States)

    Sundquist, E. T.; Jain, A. K.


    Opportunities for carbon sequestration are an important consideration in developing policies to manage the mass balance of atmospheric carbon dioxide (CO2). Assessments of potential carbon sequestration, like other resource assessments, should be widely accepted within the scientific community and broadly applicable to public needs over a range of spatial and temporal scales. The essential public concern regarding all forms of carbon sequestration is their effectiveness in offsetting CO2 emissions. But the diverse forms and mechanisms of potential sequestration are reflected in diverse assessment methodologies that are very difficult for decision-makers to compare and apply to comprehensive carbon management. For example, assessments of potential geologic sequestration are focused on total capacities derived from probabilistic analyses of rock strata, while assessments of potential biologic sequestration are focused on annual rates calculated using biogeochemical models. Non-specialists cannot readily compare and apply such dissimilar estimates of carbon storage. To address these problems, assessment methodologies should not only tabulate rates and capacities of carbon storage, but also enable comparison of the time-dependent effects of various sequestration activities on the mitigation of increasing atmospheric CO2. This outcome-based approach requires consideration of the sustainability of the assessed carbon storage, as well as the response of carbon-cycle feedbacks. Global models can be used to compare atmospheric CO2 trajectories implied by alternative global sequestration strategies, but such simulations may not be accessible or useful in many decision settings. Simplified assessment metrics, such as ratios using impulse response functions, show some promise in providing comparisons of CO2 mitigation that are broadly useful while minimizing sensitivity to differences in global models and emissions scenarios. Continued improvements will require close

  17. Memristor-based neural networks (United States)

    Thomas, Andy


    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

  18. Hierarchical network architectures of carbon fiber paper supported cobalt oxide nanonet for high-capacity pseudocapacitors. (United States)

    Yang, Lei; Cheng, Shuang; Ding, Yong; Zhu, Xingbao; Wang, Zhong Lin; Liu, Meilin


    We present a high-capacity pseudocapacitor based on a hierarchical network architecture consisting of Co(3)O(4) nanowire network (nanonet) coated on a carbon fiber paper. With this tailored architecture, the electrode shows ideal capacitive behavior (rectangular shape of cyclic voltammograms) and large specific capacitance (1124 F/g) at high charge/discharge rate (25.34 A/g), still retaining ~94% of the capacitance at a much lower rate of 0.25 A/g. The much-improved capacity, rate capability, and cycling stability may be attributed to the unique hierarchical network structures, which improves electron/ion transport, enhances the kinetics of redox reactions, and facilitates facile stress relaxation during cycling. © 2011 American Chemical Society

  19. BILP-19-An Ultramicroporous Organic Network with Exceptional Carbon Dioxide Uptake. (United States)

    Klumpen, Christoph; Radakovitsch, Florian; Jess, Andreas; Senker, Jürgen


    Porous benzimidazole-based polymers (BILPs) have proven to be promising for carbon dioxide capture and storage. The polarity of their chemical structure in combination with an inherent porosity allows for adsorbing large amounts of carbon dioxide in combination with high selectivities over unpolar guest molecules such as methane and nitrogen. For this reason, among purely organic polymers, BILPs contain some of the most effective networks to date. Nevertheless, they are still outperformed by competitive materials such as metal-organic frameworks (MOFs) or metal doped porous polymers. Here, we report the synthesis of BILP-19 and its exceptional carbon dioxide uptake of up to 6 mmol•g-1 at 273 K, making the network comparable to state-of-the-art materials. BILP-19 precipitates in a particulate structure with a strongly anisotropic growth into platelets, indicating a sheet-like structure for the network. It exhibits only a small microporous but a remarkable ultra-microporous surface area of 144 m2•g-1 and 1325 m2•g-1, respectively. We attribute the exceptional uptake of small guest molecules such as carbon dioxide and water to the distinct ultra-microporosity. Additionally, a pronounced hysteresis for both guests is observed, which in combination with the platelet character is probably caused by an expansion of the interparticle space, creating additional accessible ultra-microporous pore volume. For nitrogen and methane, this effect does not occur which explains their low affinity. In consequence, Henry selectivities of 123 for CO2/N2 at 298 K and 12 for CO2/CH4 at 273 K were determined. The network was carefully characterized with solid-state nuclear magnetic resonance (NMR) and infrared (IR) spectroscopy, thermal gravimetry (TG) and elemental analyses as well as physisorption experiments with Ar, N2, CO2, CH4 and water.

  20. About aerogels based on carbon nanomaterials

    Directory of Open Access Journals (Sweden)

    Fail Sultanov


    Full Text Available In this review a current trends in development and application of carbon nanomaterials and derivatives based on them are presented. Aerogels based on graphene and other carbon nanomaterials present a class of novel ultralight materials in which a liquid phase is completely substituted by gaseous. In its turn graphene based aerogel was named as the lightest material, thus the record of aerographite, which has retained for a long time was beaten. Aerogels are characterized by low density, high surface area and high index of hydrophobicity. In addition, depending on its application, aerogels based on carbon nanomaterials can be electrically conductive and magnetic, while retaining the flexibility of its 3D structure. Impressive properties of novel material – aerogels causes a huge interest of scientists in order to find their application in various fields, ranging from environment problems to medicine and electronics.

  1. A three-dimensional carbon nanotube network for water treatment (United States)

    Camilli, L.; Pisani, C.; Gautron, E.; Scarselli, M.; Castrucci, P.; D'Orazio, F.; Passacantando, M.; Moscone, D.; De Crescenzi, M.


    The bulk synthesis of freestanding carbon nanotube (CNT) frameworks is developed through a sulfur-addition strategy during an ambient-pressure chemical vapour deposition process, with ferrocene used as the catalyst precursor. This approach enhances the CNTs’ length and contorted morphology, which are the key features leading to the formation of the synthesized porous networks. We demonstrate that such a three-dimensional structure selectively uptakes from water a mass of toxic organic solvent (i.e. o-dichlorobenzene) about 3.5 times higher than that absorbed by individual CNTs. In addition, owing to the presence of highly defective nanostructures constituting them, our samples exhibit an oil-absorption capacity higher than that reported in the literature for similar CNT sponges.

  2. Cilia-based transport networks (United States)

    Bodenschatz, Eberhard

    Cerebrospinal fluid conveys many physiologically important signaling factors through the ventricular cavities of the brain. We investigated the transport of cerebrospinal fluid in the third ventricle of the mouse brain and discovered a highly organized pattern of cilia modules, which collectively give rise to a network of fluid flows that allows for precise transport within this ventricle. Our work suggests that ciliated epithelia can generate and maintain complex, spatiotemporally regulated flow networks. I shall also show results on how to assemble artificial cilia and cilia carpets. Supported by the BMBF MaxSynBio.

  3. Spontaneous Weaving of Graphitic Carbon Networks Synthesized by Pyrolysis of ZIF-67 Crystals. (United States)

    Zhang, Wei; Jiang, Xiangfen; Wang, Xuebin; Kaneti, Yusuf Valentino; Chen, Yinxiang; Liu, Jian; Jiang, Ji-Sen; Yamauchi, Yusuke; Hu, Ming


    Three-dimensional (3D) networks of graphitic carbon are promising materials for energy storage and conversion devices because of their high electrical conductivity, which is promoted by the good interconnection between the carbon particles. However, it is still difficult to directly synthesize such carbon networks. Herein, we report the novel synthesis of 3D graphitic carbon networks through the pyrolysis of nanosized ZIF-67 crystals. Interestingly, the unusual effect of downsizing the ZIF-67 crystals and the incorporation of catalytic Co nanoparticles was the spontaneous formation of graphitic networks. The obtained graphitic carbon networks show excellent electrochemical performance for the insertion and extraction of potassium ions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Fabrication of an interpenetrated network of carbon nanotubes and electroactive polymers to be used in oligonucletide biosensing

    Energy Technology Data Exchange (ETDEWEB)

    Acevedo, D.F. [Departamento de Quimica, Universidad Nacional de Rio Cuarto - Ruta 8, km 601, 5800 Rio Cuarto (Argentina); Reisberg, S.; Piro, B. [ITODYS, University Paris VII-CNRS, 1, Rue Guy de la Brosse, 75005 Paris (France); Peralta, D.O.; Miras, M.C. [Departamento de Quimica, Universidad Nacional de Rio Cuarto - Ruta 8, km 601, 5800 Rio Cuarto (Argentina); Pham, M.C. [ITODYS, University Paris VII-CNRS, 1, Rue Guy de la Brosse, 75005 Paris (France); Barbero, C.A. [Departamento de Quimica, Universidad Nacional de Rio Cuarto - Ruta 8, km 601, 5800 Rio Cuarto (Argentina)], E-mail:


    Layers of multiwall carbon nanotubes (MWNT), with different thickness, are built by sequential drop coating of a MWNT-Nafion dispersion in ethanol onto glassy carbon substrates. The layers form a 3D conductive network towards the electrochemical reactions of soluble redox couples (Fe{sup 3+/2+}) in aqueous solutions. Digital simulation of the electrochemical response suggests that the electron transfer is controlled by finite diffusion of the redox species inside the network. It is possible to create an interpenetrated network of carbon nanotubes and electroactive polymers (poly(hydroxynaphtoquinones)) by electropolymerization in nonaqueous media, which are electroactive in aqueous and nonaqueous media. The electrochemical response, both in cyclic voltammetry (CV) and square wave voltammetry (SWV), is significantly increased. In that way, the sensitivity of sensors (e.g. DNA biosensors based on the change of electroactive polymer response upon hybridization) could be improved.

  5. Metabolic network architecture and carbon source determine metabolite production costs. (United States)

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


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

  6. Interlayer shear behaviors of graphene-carbon nanotube network (United States)

    Qin, Huasong; Liu, Yilun


    The interlayer shear resistance plays an important role in graphene related applications, and different mechanisms have been proposed to enhance its interlayer load capacity. In this work, we performed molecular dynamics (MD) simulations and theoretical analysis to study interlayer shear behaviors of three dimensional graphene-carbon (3D-GC) nanotube networks. The shear mechanical properties of carbon nanotubes (CNTs) crosslink with different diameters are obtained which is one order of magnitude larger than that of other types of crosslinks. Under shear loading, 3D-GC exhibits two failure modes, i.e., fracture of graphene sheet and failure of CNT crosslink, determined by the diameter of CNT crosslink, crosslink density, and length of 3D-GC. A modified tension-shear chain model is proposed to predict the shear mechanical properties and failure mode of 3D-GC, which agrees well with MD simulation results. The results presented in this work may provide useful insights for future development of high-performance 3D-GC materials.

  7. Cognitive Radio-based Home Area Networks

    NARCIS (Netherlands)

    Sarijari, M.A.B.


    A future home area network (HAN) is envisaged to consist of a large number of devices that support various applications such as smart grid, security and safety systems, voice call, and video streaming. Most of these home devices are communicating based on various wireless networking technologies

  8. Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

    KAUST Repository

    Mora Cordova, Angel


    One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite\\'s conductivity based on these parameters.

  9. Phthalocyanine based metal containing porous carbon sheet (United States)

    Honda, Z.; Sakaguchi, Y.; Tashiro, M.; Hagiwara, M.; Kida, T.; Sakai, M.; Fukuda, T.; Kamata, N.


    Highly-ordered fused-ring poly copper phthalocyanine (PCuPc) was prepared using copper octacyanophthalocyanine as a building block, and two-dimensional (2D) square superlattices were directly observed by the transmission electron microscopy. Remarkably, we have found a formation of polymer network that consists of a 2D porous PCuPc sheet in which the centers of phthalocyanine units are alternately occupied by Cu atom and vacancy. Using this "half-filling" PCuPc, it must be possible to create alternating arrangements for transition metal centers, and therefore control the magnetic properties of the 2D carbon sheets.

  10. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A


    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  11. Modeling the interdependent network based on two-mode networks (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian


    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  12. Networks of connected Pt nanoparticles supported on carbon nanotubes as superior catalysts for methanol electrooxidation (United States)

    Huang, Meihua; Zhang, Jianshuo; Wu, Chuxin; Guan, Lunhui


    The high cost and short lifetime of the Pt-based anode catalyst for methanol oxidation reaction (MOR) hamper the widespread commercialization of direct methanol fuel cell (DMFC). Therefore, improving the activity of Pt-based catalysts is necessary for their practical application. For the first time, we prepared networks of connected Pt nanoparticles supported on multi-walled carbon nanotubes with loading ratio as high as 91 wt% (Pt/MWCNTs). Thanks for the unique connected structure, the Pt mass activity of Pt/MWCNTs for methanol oxidation reaction is 4.4 times as active as that of the commercial Pt/C (20 wt%). When carbon support is considered, the total mass activity of Pt/MWCNTs is 20 times as active as that of the commercial Pt/C. The durability and anti-poisoning ability are also improved greatly.

  13. Dynamics-based centrality for directed networks. (United States)

    Masuda, Naoki; Kori, Hiroshi


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

  14. Carbon-based nanomaterials for tissue engineering. (United States)

    Ku, Sook Hee; Lee, Minah; Park, Chan Beum


    Carbon-based nanomaterials such as graphene sheets and carbon nanotubes possess unique mechanical, electrical, and optical properties that present new opportunities for tissue engineering, a key field for the development of biological alternatives that repair or replace whole or a portion of tissue. Carbon nanomaterials can also provide a similar microenvironment as like a biological extracellular matrix in terms of chemical composition and physical structure, making them a potential candidate for the development of artificial scaffolds. In this review, we summarize recent research advances in the effects of carbon nanomaterial-based substrates on cellular behaviors, including cell adhesion, proliferation, and differentiation into osteo- or neural- lineages. The development of 3D scaffolds based on carbon nanomaterials (or their composites with polymers and inorganic components) is introduced, and the potential of these constructs in tissue engineering, including toxicity issues, is discussed. Future perspectives and emerging challenges are also highlighted. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Network environ perspective for urban metabolism and carbon emissions: a case study of Vienna, Austria. (United States)

    Chen, Shaoqing; Chen, Bin


    Cities are considered major contributors to global warming, where carbon emissions are highly embedded in the overall urban metabolism. To examine urban metabolic processes and emission trajectories we developed a carbon flux model based on Network Environ Analysis (NEA). The mutual interactions and control situation within the urban ecosystem of Vienna were examined, and the system-level properties of the city's carbon metabolism were assessed. Regulatory strategies to minimize carbon emissions were identified through the tracking of the possible pathways that affect these emission trajectories. Our findings suggest that indirect flows have a strong bearing on the mutual and control relationships between urban sectors. The metabolism of a city is considered self-mutualistic and sustainable only when the local and distal environments are embraced. Energy production and construction were found to be two factors with a major impact on carbon emissions, and whose regulation is only effective via ad-hoc pathways. In comparison with the original life-cycle tracking, the application of NEA was better at revealing details from a mechanistic aspect, which is crucial for informed sustainable urban management.

  16. Cloud-based Networked Visual Servo Control

    DEFF Research Database (Denmark)

    Wu, Haiyan; Lu, Lei; Chen, Chih-Chung


    feedback, ii) a stabilizing control law for the networked visual servo control system with time-varying feedback time delay, and iii) a sending rate scheduling strategy aiming at reducing the communication network load. The performance of the networked visual servo control system with sending rate......The performance of vision-based control systems, in particular of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control......, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

  17. Modelling Carbon Nanotubes-Based Mediatorless Biosensor

    Directory of Open Access Journals (Sweden)

    Julija Razumiene


    Full Text Available This paper presents a mathematical model of carbon nanotubes-based mediatorless biosensor. The developed model is based on nonlinear non-stationary reaction-diffusion equations. The model involves four layers (compartments: a layer of enzyme solution entrapped on a terylene membrane, a layer of the single walled carbon nanotubes deposited on a perforated membrane, and an outer diffusion layer. The biosensor response and sensitivity are investigated by changing the model parameters with a special emphasis on the mediatorless transfer of the electrons in the layer of the enzyme-loaded carbon nanotubes. The numerical simulation at transient and steady state conditions was carried out using the finite difference technique. The mathematical model and the numerical solution were validated by experimental data. The obtained agreement between the simulation results and the experimental data was admissible at different concentrations of the substrate.

  18. Building a Network Based Laboratory Environment

    Directory of Open Access Journals (Sweden)

    Sea Shuan Luo


    Full Text Available This paper presents a comparative study about the development of a network based laboratory environment in the “Unix introduction” course for the undergraduate students. The study results and the response from the students from 2005 to 2006 will be used to better understand what kind of method is more suitable for students. We also use the data collected to adjust our teaching strategy and try to build up a network based laboratory environment.

  19. Permeability evolution due to dissolution and precipitation of carbonates using reactive transport modeling in pore networks (United States)

    Nogues, Juan P.; Fitts, Jeffrey P.; Celia, Michael A.; Peters, Catherine A.


    A reactive transport model was developed to simulate reaction of carbonates within a pore network for the high-pressure CO2-acidified conditions relevant to geological carbon sequestration. The pore network was based on a synthetic oolithic dolostone. Simulation results produced insights that can inform continuum-scale models regarding reaction-induced changes in permeability and porosity. As expected, permeability increased extensively with dissolution caused by high concentrations of carbonic acid, but neither pH nor calcite saturation state alone was a good predictor of the effects, as may sometimes be the case. Complex temporal evolutions of interstitial brine chemistry and network structure led to the counterintuitive finding that a far-from-equilibrium solution produced less permeability change than a nearer-to-equilibrium solution at the same pH. This was explained by the pH buffering that increased carbonate ion concentration and inhibited further reaction. Simulations of different flow conditions produced a nonunique set of permeability-porosity relationships. Diffusive-dominated systems caused dissolution to be localized near the inlet, leading to substantial porosity change but relatively small permeability change. For the same extent of porosity change caused from advective transport, the domain changed uniformly, leading to a large permeability change. Regarding precipitation, permeability changes happen much slower compared to dissolution-induced changes and small amounts of precipitation, even if located only near the inlet, can lead to large changes in permeability. Exponent values for a power law that relates changes in permeability and porosity ranged from 2 to 10, but a value of 6 held constant when conditions led to uniform changes throughout the domain.

  20. Functional Ecological Gene Networks to Reveal the Changes Among Microbial Interactions Under Elevated Carbon Dioxide Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Ye; Zhou, Jizhong; Luo, Feng; He, Zhili; Tu, Qichao; Zhi, Xiaoyang


    Biodiversity and its responses to environmental changes is a central issue in ecology, and for society. Almost all microbial biodiversity researches focus on species richness and abundance but ignore the interactions among different microbial species/populations. However, determining the interactions and their relationships to environmental changes in microbial communities is a grand challenge, primarily due to the lack of information on the network structure among different microbial species/populations. Here, a novel random matrix theory (RMT)-based conceptual framework for identifying functional ecological gene networks (fEGNs) is developed with the high throughput functional gene array hybridization data from the grassland microbial communities in a long-term FACE (Free Air CO2 Enrichment) experiment. Both fEGNs under elevated CO2 (eCO2) and ambient CO2 (aCO2) possessed general characteristics of many complex systems such as scale-free, small-world, modular and hierarchical. However, the topological structure of the fEGNs is distinctly different between eCO2 and aCO2, suggesting that eCO2 dramatically altered the interactions among different microbial functional groups/populations. In addition, the changes in network structure were significantly correlated with soil carbon and nitrogen dynamics, and plant productivity, indicating the potential importance of network interactions in ecosystem functioning. Elucidating network interactions in microbial communities and their responses to environmental changes are fundamentally important for research in microbial ecology, systems microbiology, and global change.

  1. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  2. Using Carbon flux network data to investigate the impact of new European greening rules on carbon budgets - a case study. (United States)

    Schmidt, Marius; Graf, Alexander; Carsten, Montzka; Vereecken, Harry


    In 2015 the European Commission introduced new greening payments as part of their common agricultural practices to address environmental and sustainability issues. The payment is worth about 30% of the total subsidies for European farmers. Sowing nitrogen fixing catch/cover crops in the off season (generally in fall and winter) is one way to achieve the prerequisite for the greening payments. Therefore it is expected that the proportion of catch/cover crops will increase from 2015 onwards at the expense of bare soil fields. In particular, with regard to more frequently occurring mild weather conditions during fall and winter, we assume that the extensive shift to catch/cover crops will have a significant impact on the carbon cycle of agricultural areas. In this study we aim to evaluate this change in agricultural practice on local and regional CO2 fluxes and carbon budgets of the intensively used northern Rur catchment in Germany. In a preliminary study, we observed the daily courses of net CO2 flux and soil respiration of three different catch/cover crops: greening mix, oil radish, and white mustard (Sinapis alba), by means of a net flux chamber and a soil respiration chamber and compared them against Eddy covariance flux data from fields cultivated with (i) winter barley (Hordeum vulgare), and (ii) without vegetation. In the main study, we compare multi-year measurements of carbon fluxes from a regional network of Eddy Covariance sites, partly included in larger networks like Fluxnet, European Fluxes Database Cluster or ICOS. We especially used site data where comparisons of catch crop seasons and conventional seasons between different sites or years were possible. To allow an assessment of the change in carbon fluxes and budgets on regional scale, a land use comparison based on satellite images for the years 2014 to 2016 was applied. With these results, a first regional evaluation of the impact of the new greening policies on carbon fluxes and budgets for the

  3. PID Controller Based on Memristive CMAC Network

    Directory of Open Access Journals (Sweden)

    Lidan Wang


    Full Text Available Compound controller which consists of CMAC network and PID network is mainly used in control system, especially in robot control. It can realize nonlinear tracking control of the real-time dynamic trajectory and possesses good approximation effect. According to the structure and principle of the compound controller, memristor is introduced to CMAC network to be a compound controller in this paper. The new PID controller based on memristive CMAC network is built up by replacing the synapse in the original controller by memristors. The effect of curve approximation is obtained by MATLAB simulation experiments. This network improves the response and learning speed of the system and processes better robustness and antidisturbance performance.

  4. Network based sky Brightness Monitor (United States)

    McKenna, Dan; Pulvermacher, R.; Davis, D. R.


    We have developed and are currently testing an autonomous 2 channel photometer designed to measure the night sky brightness in the visual wavelengths over a multi-year campaign. The photometer uses a robust silicon sensor filtered with Hoya CM500 glass. The Sky brightness is measured every minute at two elevation angles typically zenith and 20 degrees to monitor brightness and transparency. The Sky Brightness monitor consists of two units, the remote photometer and a network interface. Currently these devices use 2.4 Ghz transceivers with a free space range of 100 meters. The remote unit is battery powered with day time recharging using a solar panel. Data received by the network interface transmits data via standard POP Email protocol. A second version is under development for radio sensitive areas using an optical fiber for data transmission. We will present the current comparison with the National Park Service sky monitoring camera. We will also discuss the calibration methods used for standardization and temperature compensation. This system is expected to be deployed in the next year and be operated by the International Dark Sky Association SKYMONITOR project.

  5. Piezoresistive Strain Sensors Made from Carbon Nanotubes Based Polymer Nanocomposites

    Directory of Open Access Journals (Sweden)

    Jinhua Li


    Full Text Available In recent years, nanocomposites based on various nano-scale carbon fillers, such as carbon nanotubes (CNTs, are increasingly being thought of as a realistic alternative to conventional smart materials, largely due to their superior electrical properties. Great interest has been generated in building highly sensitive strain sensors with these new nanocomposites. This article reviews the recent significant developments in the field of highly sensitive strain sensors made from CNT/polymer nanocomposites. We focus on the following two topics: electrical conductivity and piezoresistivity of CNT/polymer nanocomposites, and the relationship between them by considering the internal conductive network formed by CNTs, tunneling effect, aspect ratio and piezoresistivity of CNTs themselves, etc. Many recent experimental, theoretical and numerical studies in this field are described in detail to uncover the working mechanisms of this new type of strain sensors and to demonstrate some possible key factors for improving the sensor sensitivity.

  6. Response of asymmetric carbon nanotube network devices to sub-terahertz and terahertz radiation

    Energy Technology Data Exchange (ETDEWEB)

    Gayduchenko, I., E-mail:, E-mail: [Physics Department, Moscow State Pedagogical University, Moscow 119991 (Russian Federation); National Research Centre “Kurchatov Institute,” Moscow 123128 (Russian Federation); Kardakova, A.; Voronov, B.; Finkel, M. [Physics Department, Moscow State Pedagogical University, Moscow 119991 (Russian Federation); Fedorov, G., E-mail:, E-mail: [Physics Department, Moscow State Pedagogical University, Moscow 119991 (Russian Federation); Moscow Institute of Physics and Technology (State University), Dolgoprudny 141700 (Russian Federation); Jiménez, D. [Departament d' Enginyeria Electrònica, Escola d' Enginyeria, Universitat Autònoma de Barcelona, 08193 Bellaterra (Spain); Morozov, S. [Moscow Institute of Physics and Technology (State University), Dolgoprudny 141700 (Russian Federation); Presniakov, M. [National Research Centre “Kurchatov Institute,” Moscow 123128 (Russian Federation); Goltsman, G. [Physics Department, Moscow State Pedagogical University, Moscow 119991 (Russian Federation); Moscow Institute of Electronics and Mathematics, National Research University Higher School of Economics, Moscow 109028 (Russian Federation)


    Demand for efficient terahertz radiation detectors resulted in intensive study of the asymmetric carbon nanostructures as a possible solution for that problem. It was maintained that photothermoelectric effect under certain conditions results in strong response of such devices to terahertz radiation even at room temperature. In this work, we investigate different mechanisms underlying the response of asymmetric carbon nanotube (CNT) based devices to sub-terahertz and terahertz radiation. Our structures are formed with CNT networks instead of individual CNTs so that effects probed are more generic and not caused by peculiarities of an individual nanoscale object. We conclude that the DC voltage response observed in our structures is not only thermal in origin. So called diode-type response caused by asymmetry of the device IV characteristic turns out to be dominant at room temperature. Quantitative analysis provides further routes for the optimization of the device configuration, which may result in appearance of novel terahertz radiation detectors.

  7. Carbon Nanotube-Based Synthetic Gecko Tapes (United States)

    Dhinojwala, Ali


    Wall-climbing geckos have unique ability to attach to different surfaces without the use of any viscoelastic glues. On coming in contact with any surface, the micron-size gecko foot-hairs deform, enabling molecular contact over large areas, thus translating weak van der Waals (vdW) interactions into enormous shear forces. We will present our recent results on the development of synthetic gecko tape using aligned carbon nanotubes to mimic the keratin hairs found on gecko feet. The patterned carbon nanotube-based gecko tape can support a shear stress (36 N/cm^2) nearly four times higher than the gecko foot and sticks to a variety of surfaces, including Teflon. Both the micron-size setae (replicated by nanotube bundles) and nanometer-size spatulas (individual nanotubes) are necessary to achieve macroscopic shear adhesion and to translate the weak vdW interactions into high shear forces. The carbon nanotube based tape offers an excellent synthetic option as a dry conductive reversible adhesive in microelectronics, robotics and space applications. The mechanism behind these large shear forces and self-cleaning properties of these carbon nanotube based synthetic gecko tapes will be discussed. This work was performed in collaboration with graduate students Liehui Ge, and Sunny Sethi, and collaborators from RPI; Lijie Ci and Professor Pulickel Ajayan.

  8. SDL-based network performance simulation (United States)

    Yang, Yang; Lu, Yang; Lin, Xiaokang


    Specification and description language (SDL) is an object-oriented formal language defined as a standard by ITU-T. Though SDL is mainly used in describing communication protocols, it is an efficient way to simulate the network performance with SDL tools according to our experience. This paper presents our methodology of SDL-based network performance simulation in such aspects as the simulation platform, the simulation modes and the integrated simulation environment. Note that Telelogic Tau 4.3 SDL suite is used here as the simulation environment though our methodology isn't limited to the software. Finally the SDL-based open shortest path first (OSPF) performance simulation in the wireless private network is illustrated as an example of our methodology, which indicates that SDL is indeed an efficient language in the area of the network performance simulation.

  9. Toward Measuring Network Aesthetics Based on Symmetry

    Directory of Open Access Journals (Sweden)

    Zengqiang Chen


    Full Text Available In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

  10. Fifty years in studying carbon-based materials (United States)

    Dresselhaus, Mildred S.


    A review is presented based on our 50 year involvement in studying carbon materials physics and carbon-based nanostructures. The review topics include an early history of studies of graphene and graphite, graphite intercalation compounds, forerunners of nano-carbons, fullerenes, carbon nanotubes and, finally, graphene and graphene nanoribbons.

  11. Digital image analysis to quantify carbide networks in ultrahigh carbon steels

    Energy Technology Data Exchange (ETDEWEB)

    Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N., E-mail:


    A method has been developed and demonstrated to quantify the degree of carbide network connectivity in ultrahigh carbon steels through digital image processing and analysis of experimental micrographs. It was shown that the network connectivity and carbon content can be correlated to toughness for various ultrahigh carbon steel specimens. The image analysis approach first involved segmenting the carbide network and pearlite matrix into binary contrast representations via a grayscale intensity thresholding operation. Next, the carbide network pixels were skeletonized and parceled into braches and nodes, allowing the determination of a connectivity index for the carbide network. Intermediate image processing steps to remove noise and fill voids in the network are also detailed. The connectivity indexes of scanning electron micrographs were consistent in both secondary and backscattered electron imaging modes, as well as across two different (50 × and 100 ×) magnifications. Results from ultrahigh carbon steels reported here along with other results from the literature generally showed lower connectivity indexes correlated with higher Charpy impact energy (toughness). A deviation from this trend was observed at higher connectivity indexes, consistent with a percolation threshold for crack propagation across the carbide network. - Highlights: • A method for carbide network analysis in steels is proposed and demonstrated. • ImageJ method extracts a network connectivity index from micrographs. • Connectivity index consistent in different imaging conditions and magnifications. • Impact energy may plateau when a critical network connectivity is exceeded.

  12. Carbon Nanotube Paper-Based Electroanalytical Devices

    Directory of Open Access Journals (Sweden)

    Youngmi Koo


    Full Text Available Here, we report on carbon nanotube paper-based electroanalytical devices. A highly aligned-carbon nanotube (HA-CNT array, grown using chemical vapor deposition (CVD, was processed to form bi-layered paper with an integrated cellulose-based Origami-chip as the electroanalytical device. We used an inverse-ordered fabrication method from a thick carbon nanotube (CNT sheet to a thin CNT sheet. A 200-layered HA-CNT sheet and a 100-layered HA-CNT sheet are explored as a working electrode. The device was fabricated using the following methods: (1 cellulose-based paper was patterned using a wax printer, (2 electrical connection was made using a silver ink-based circuit printer, and (3 three electrodes were stacked on a 2D Origami cell. Electrochemical behavior was evaluated using electrochemical impedance spectroscopy (EIS and cyclic voltammetry (CV. We believe that this platform could attract a great deal of interest for use in various chemical and biomedical applications.

  13. Wireless Mid-Infrared Spectroscopy Sensor Network for Automatic Carbon Dioxide Fertilization in a Greenhouse Environment

    Directory of Open Access Journals (Sweden)

    Jianing Wang


    Full Text Available In this paper, a wireless mid-infrared spectroscopy sensor network was designed and implemented for carbon dioxide fertilization in a greenhouse environment. A mid-infrared carbon dioxide (CO2 sensor based on non-dispersive infrared (NDIR with the functionalities of wireless communication and anti-condensation prevention was realized as the sensor node. Smart transmission power regulation was applied in the wireless sensor network, according to the Received Signal Strength Indication (RSSI, to realize high communication stability and low-power consumption deployment. Besides real-time monitoring, this system also provides a CO2 control facility for manual and automatic control through a LabVIEW platform. According to simulations and field tests, the implemented sensor node has a satisfying anti-condensation ability and reliable measurement performance on CO2 concentrations ranging from 30 ppm to 5000 ppm. As an application, based on the Fuzzy proportional, integral, and derivative (PID algorithm realized on a LabVIEW platform, the CO2 concentration was regulated to some desired concentrations, such as 800 ppm and 1200 ppm, in 30 min with a controlled fluctuation of <±35 ppm in an acre of greenhouse.

  14. Wireless Mid-Infrared Spectroscopy Sensor Network for Automatic Carbon Dioxide Fertilization in a Greenhouse Environment. (United States)

    Wang, Jianing; Niu, Xintao; Zheng, Lingjiao; Zheng, Chuantao; Wang, Yiding


    In this paper, a wireless mid-infrared spectroscopy sensor network was designed and implemented for carbon dioxide fertilization in a greenhouse environment. A mid-infrared carbon dioxide (CO₂) sensor based on non-dispersive infrared (NDIR) with the functionalities of wireless communication and anti-condensation prevention was realized as the sensor node. Smart transmission power regulation was applied in the wireless sensor network, according to the Received Signal Strength Indication (RSSI), to realize high communication stability and low-power consumption deployment. Besides real-time monitoring, this system also provides a CO₂ control facility for manual and automatic control through a LabVIEW platform. According to simulations and field tests, the implemented sensor node has a satisfying anti-condensation ability and reliable measurement performance on CO₂ concentrations ranging from 30 ppm to 5000 ppm. As an application, based on the Fuzzy proportional, integral, and derivative (PID) algorithm realized on a LabVIEW platform, the CO₂ concentration was regulated to some desired concentrations, such as 800 ppm and 1200 ppm, in 30 min with a controlled fluctuation of <±35 ppm in an acre of greenhouse.

  15. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun


    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  16. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz


    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  17. Carbon-based tribofilms from lubricating oils

    Energy Technology Data Exchange (ETDEWEB)

    Erdemir, Ali; Ramirez, Giovanni; Eryilmaz, Osman L.; Narayanan, Badri; Liao, Yifeng; Kamath, Ganesh; Sankaranarayanan, Subramanian K. R. S.


    Moving mechanical interfaces are commonly lubricated and separated by a combination of fluid films and solid 'tribofilms', which together ensure easy slippage and long wear life(1). The efficacy of the fluid film is governed by the viscosity of the base oil in the lubricant; the efficacy of the solid tribofilm, which is produced as a result of sliding contact between moving parts, relies upon the effectiveness of the lubricant's anti-wear additive (typically zinc dialkyldithiophosphate)(2). Minimizing friction and wear continues to be a challenge, and recent efforts have focused on enhancing the anti-friction and anti-wear properties of lubricants by incorporating inorganic nanoparticles and ionic liquids(3,4). Here, we describe the in operando formation of carbon-based tribofilms via dissociative extraction from base-oil molecules on catalytically active, sliding nanometre-scale crystalline surfaces, enabling base oils to provide not only the fluid but also the solid tribofilm. We study nanocrystalline catalytic coatings composed of nitrides of either molybdenum or vanadium, containing either copper or nickel catalysts, respectively. Structurally, the resulting tribofilms are similar to diamond-like carbon(5). Ball-on-disk tests at contact pressures of 1.3 gigapascals reveal that these tribofilms nearly eliminate wear, and provide lower friction than tribofilms formed with zinc dialkyldithiophosphate. Reactive and ab initio molecular-dynamics simulations show that the catalytic action of the coatings facilitates dehydrogenation of linear olefins in the lubricating oil and random scission of their carbon-carbon backbones; the products recombine to nucleate and grow a compact, amorphous lubricating tribofilm.

  18. Fermentation based carbon nanotube bionic functional composites


    Valentini, Luca; Bon, Silvia Bittolo; Signetti, Stefano; Tripathi, Manoj; Iacob, Erica; Pugno, Nicola M.


    The exploitation of the processes used by microorganisms to digest nutrients for their growth can be a viable method for the formation of a wide range of so called biogenic materials that have unique mechanical and physical properties that are not produced by abiotic processes. Based on grape must and bread fermentation, a bionic composite made of carbon nanotubes (CNTs) and single-cell fungi, the Saccharomyces cerevisiae yeast extract, was prepared by fermentation of such microorganisms at r...

  19. Carbon nanotube-based synthetic gecko tapes


    Ge, Liehui; Sethi, Sunny; Ci, Lijie; Ajayan, Pulickel M.; Dhinojwala, Ali


    We have developed a synthetic gecko tape by transferring micropatterned carbon nanotube arrays onto flexible polymer tape based on the hierarchical structure found on the foot of a gecko lizard. The gecko tape can support a shear stress (36 N/cm2) nearly four times higher than the gecko foot and sticks to a variety of surfaces, including Teflon. Both the micrometer-size setae (replicated by nanotube bundles) and nanometer-size spatulas (individual nanotubes) are necessary to achieve macroscop...

  20. The Bidirectional Optimization of Carbon Fiber Production by Neural Network with a GA-IPSO Hybrid Algorithm

    Directory of Open Access Journals (Sweden)

    Jiajia Chen


    Full Text Available A hybrid approach of genetic algorithm (GA and improved particle swarm optimization (IPSO is proposed to construct the radial basis function neural network (RNN for real-time optimizing of the carbon fiber manufacture process. For the three-layer RNN, we adopt the nearest neighbor-clustering algorithm to determine the neurons number of the hidden layer. When the appropriate network structure is fixed, we present the GA-IPSO algorithm to tune the parameters of the network, which means the center and the width of the node in the hidden layer and the weight of output layer. We introduce a penalty factor to adjust the velocity and position of the particles to expedite convergence of the PSO. The GA is used to mutate the particles to escape local optimum. Then we employ this network to develop the bidirectional optimization model: in one direction, we take production parameters as input and properties indices as output; in this case, the model is a carbon fiber product performance prediction system; in the other direction, we take properties indices as input and production parameters as output, and at this situation, the model is a production scheme design tool for novel style carbon fiber. Based on the experimental data, the proposed model is compared to the conventional RBF network and basic PSO method; the research results show its validity and the advantages in dealing with optimization problems.

  1. Carbon Nanotube Network Ambipolar Field-Effect Transistors with 108 On/Off Ratio

    NARCIS (Netherlands)

    Derenskyi, Vladimir; Gomulya, Widianta; Salazar Rios, Jorge Mario; Fritsch, Martin; Fröhlich, Nils; Jung, Stefan; Allard, Sybille; Bisri, Satria Zulkarnaen; Gordiichuk, Pavlo; Herrmann, Andreas; Scherf, Ullrich; Loi, Maria Antonietta


    Polymer wrapping is a highly effective method of selecting semiconducting carbon nanotubes and dispersing them in solution. Semi-aligned semiconducting carbon nanotube networks are obtained by blade coating, an effective and scalable process. The field-effect transistor (FET) performance can be

  2. Overlapping Community Detection based on Network Decomposition (United States)

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


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

  3. Influence of O-2 and N-2 on the conductivity of carbon nanotube networks

    DEFF Research Database (Denmark)

    Mowbray, Duncan; Morgan, C.; Thygesen, Kristian Sommer


    We have performed experiments on single-wall carbon nanotube (SWNT) networks and compared with density-functional theory (DFT) calculations to identify the microscopic origin of the observed sensitivity of the network conductivity to physisorbed O-2 and N-2. Previous DFT calculations...

  4. Location-based Forwarding in Vehicular Networks

    NARCIS (Netherlands)

    Klein Wolterink, W.


    In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems (ITSs). ITSs are transport systems that utilise information and communication technologies to increase their level of automation, in this way levering the performance of



    Attila Trohák; Máté Kolozsi-Tóth; Péter Rádi


    In the paper we will introduce an intelligent conveyor surveillance system. We started a research project to design and develop a conveyor surveillance system based on wireless sensor network and GPRS communication. Our system is able to measure temperature on fixed and moving, rotating surfaces and able to detect smoke. We would like to introduce the developed devices and give an application example.

  6. Plankton networks driving carbon export in the oligotrophic ocean. (United States)

    Guidi, Lionel; Chaffron, Samuel; Bittner, Lucie; Eveillard, Damien; Larhlimi, Abdelhalim; Roux, Simon; Darzi, Youssef; Audic, Stephane; Berline, Léo; Brum, Jennifer; Coelho, Luis Pedro; Espinoza, Julio Cesar Ignacio; Malviya, Shruti; Sunagawa, Shinichi; Dimier, Céline; Kandels-Lewis, Stefanie; Picheral, Marc; Poulain, Julie; Searson, Sarah; Stemmann, Lars; Not, Fabrice; Hingamp, Pascal; Speich, Sabrina; Follows, Mick; Karp-Boss, Lee; Boss, Emmanuel; Ogata, Hiroyuki; Pesant, Stephane; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Bork, Peer; de Vargas, Colomban; Iudicone, Daniele; Sullivan, Matthew B; Raes, Jeroen; Karsenti, Eric; Bowler, Chris; Gorsky, Gabriel


    The biological carbon pump is the process by which CO2 is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterized. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150 m and highlight unexpected taxa such as Radiolaria and alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of a few bacterial and viral genes can predict a significant fraction of the variability in carbon export in these regions.

  7. Characterization of low thermal conductivity PAN-based carbon fibers (United States)

    Katzman, Howard A.; Adams, P. M.; Le, T. D.; Hemminger, Carl S.


    The microstructure and surface chemistry of eight low thermal conductivity (LTC) PAN-based carbon fibers were determined and compared with PAN-based fibers heat treated to higher temperatures. Based on wide-angle x ray diffraction, the LTC PAN fibers all appear to have a similar turbostratic structure with large 002 d-spacings, small crystallite sizes, and moderate preferred orientation. Limited small-angle x ray scattering (SAXS) results indicate that, with the exception of LTC fibers made by BASF, the LTC fibers do not have well developed pores. Transmission electron microscopy shows that the texture of the two LTC PAN-based fibers studied (Amoco T350/23X and /25X) consists of multiple sets of parallel, wavy, bent layers that interweave with each other forming a complex three dimensional network oriented randomly around the fiber axis. X ray photoelectron spectroscopy (XPS) analysis finds correlations between heat treated temperatures and the surface composition chemistry of the carbon fiber samples.

  8. SAR ATR Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Tian Zhuangzhuang


    Full Text Available This study presents a new method of Synthetic Aperture Radar (SAR image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.

  9. Fixation of carbon dioxide into dimethyl carbonate over titanium-based zeolitic thiophene-benzimidazolate framework (United States)

    U.S. Environmental Protection Agency — A titanium-based zeolitic thiophene-benzimidazolate framework has been designed for the direct synthesis of dimethyl carbonate (DMC) from methanol and carbon...

  10. Ultrasensitive, Stretchable Strain Sensors Based on Fragmented Carbon Nanotube Papers

    KAUST Repository

    Zhou, Jian


    The development of strain sensors featuring both ultra high sensitivity and high stretchability is still a challenge. We demonstrate that strain sensors based on fragmented single-walled carbon nanotube (SWCNT) paper embedded in poly(dimethylsiloxane) (PDMS) can sustain their sensitivity even at very high strain levels (with a gauge factor of over 10(7) at 50% strain). This record sensitivity is ascribed to the low initial electrical resistance (5-28 Omega) of the SWCNT paper and the wide change in resistance (up to 10(6) Omega) governed by the percolated network of SWCNT in the cracked region. The sensor response remains nearly unchanged after 10 000 strain cycles at 20% proving the robustness of this technology. This fragmentation based sensing system brings opportunities to engineer highly sensitive stretchable sensors.

  11. An Electrically Conductive and Organic Solvent Vapors Detecting Composite Composed of an Entangled Network of Carbon Nanotubes Embedded in Polystyrene

    Directory of Open Access Journals (Sweden)

    R. Olejnik


    Full Text Available A composite composed of electrically conductive entangled carbon nanotubes embedded in a polystyrene base has been prepared by the innovative procedure, when the nonwoven polystyrene filter membrane is enmeshed with carbon nanotubes. Both constituents are then interlocked by compression molding. The mechanical and electrical resistance testing show that the polymer increases nanotube network mechanical integrity, tensile strength, and the reversibility of electrical resistance in deformation cycles. Another obvious effect of the supporting polymer is the reduction of resistance temperature dependence of composite and the reproducibility of methanol vapor sensing.

  12. Discrete Fracture Network Models for Risk Assessment of Carbon Sequestration in Coal

    Energy Technology Data Exchange (ETDEWEB)

    Jack Pashin; Guohai Jin; Chunmiao Zheng; Song Chen; Marcella McIntyre


    A software package called DFNModeler has been developed to assess the potential risks associated with carbon sequestration in coal. Natural fractures provide the principal conduits for fluid flow in coal-bearing strata, and these fractures present the most tangible risks for the leakage of injected carbon dioxide. The objectives of this study were to develop discrete fracture network (DFN) modeling tools for risk assessment and to use these tools to assess risks in the Black Warrior Basin of Alabama, where coal-bearing strata have high potential for carbon sequestration and enhanced coalbed methane recovery. DFNModeler provides a user-friendly interface for the construction, visualization, and analysis of DFN models. DFNModeler employs an OpenGL graphics engine that enables real-time manipulation of DFN models. Analytical capabilities in DFNModeler include display of structural and hydrologic parameters, compartmentalization analysis, and fluid pathways analysis. DFN models can be exported to third-party software packages for flow modeling. DFN models were constructed to simulate fracturing in coal-bearing strata of the upper Pottsville Formation in the Black Warrior Basin. Outcrops and wireline cores were used to characterize fracture systems, which include joint systems, cleat systems, and fault-related shear fractures. DFN models were constructed to simulate jointing, cleating, faulting, and hydraulic fracturing. Analysis of DFN models indicates that strata-bound jointing compartmentalizes the Pottsville hydrologic system and helps protect shallow aquifers from injection operations at reservoir depth. Analysis of fault zones, however, suggests that faulting can facilitate cross-formational flow. For this reason, faults should be avoided when siting injection wells. DFN-based flow models constructed in TOUGH2 indicate that fracture aperture and connectivity are critical variables affecting the leakage of injected CO{sub 2} from coal. Highly transmissive joints

  13. Network Based High Speed Product Innovation

    DEFF Research Database (Denmark)

    Lindgren, Peter

    In the first decade of the 21st century, New Product Development has undergone major changes in the way NPD is managed and organised. This is due to changes in technology, market demands, and in the competencies of companies. As a result NPD organised in different forms of networks is predicted...... to be of ever-increasing importance to many different kinds of companies. This happens at the same times as the share of new products of total turnover and earnings is increasing at unprecedented speed in many firms and industries. The latter results in the need for very fast innovation and product development...... - a need that can almost only be resolved by organising NPD in some form of network configuration. The work of Peter Lindgren is on several aspects of network based high speed product innovation and contributes to a descriptive understanding of this phenomenon as well as with normative theory on how NPD...

  14. Hydrogel networks based on ABA triblock copolymers. (United States)

    Tartivel, Lucile; Behl, Marc; Schroeter, Michael; Lendlein, Andreas


    Triblock copolymers from hydrophilic oligo(ethylene glycol) segment A and oligo(propylene glycol) segment B, providing an ABA structure (OEG-OPG-OEG triblock), are known to be biocompatible and are used as self-solidifying gels in drug depots. A complete removal of these depots would be helpful in cases of undesired side effects of a drug, but this remains a challenge as they liquefy below their transition temperature. Therefore we describe the synthesis of covalently cross-linked hydrogel networks. Triblock copolymer-based hydrogels were created by irradiating aqueous solutions of the corresponding macro-dimethacrylates with UV light. The degree of swelling, swelling kinetics, mechanical properties and morphology of the networks were investigated. Depending on precursor concentration, equilibrium degree of swelling of the films ranged between 500% and 880% and was reached in 1 hour. In addition, values for storage and loss moduli of the hydrogel networks were in the 100 Pa to 10 kPa range. Although OEG-OPG-OEG triblocks are known for their micellization, which could hamper polymer network formation, reactive OEG-OPG-OEG triblock oligomers could be successfully polymerized into hydrogel networks. The degree of swelling of these hydrogels depends on their molecular weight and on the oligomer concentration used for hydrogel preparation. In combination with the temperature sensitivity of the ABA triblock copolymers, it is assumed that such hydrogels might be beneficial for future medical applications - e.g., removable drug release systems.

  15. Dynamic social networks based on movement (United States)

    Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.


    Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

  16. Carbon nanomaterials-based electrochemical aptasensors. (United States)

    Wang, Zonghua; Yu, Jianbo; Gui, Rijun; Jin, Hui; Xia, Yanzhi


    Carbon nanomaterials (CNMs) have attracted increasing attention due to their unique electrical, optical, thermal, mechanical and chemical properties. CNMs are extensively applied in electronic, optoelectronic, photovoltaic and sensing devices fields, especially in bioassay technology. These excellent properties significantly depend on not only the functional atomic structures of CNMs, but also the interactions with other materials, such as gold nanoparticles, SiO2, chitosan, etc. This review systematically summarizes applications of CNMs in electrochemical aptasensors (ECASs). Firstly, definition and development of ECASs are introduced. Secondly, different ways of ECASs about working principles, classification and construction of CNMs are illustrated. Thirdly, the applications of different CNMs used in ECASs are discussed. In this review, different types of CNMs are involved such as carbon nanotubes, graphene, graphene oxide, etc. Besides, the newly emerging CNMs and CNMs-based composites are also discoursed. Finally, we demonstrate the future prospects of CNMs-based ECASs, and some suggestions about the near future development of CNMs-based ECASs are highlighted. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Sensing performances of pure and hybridized carbon nanotubes-ZnO nanowire networks: A detailed study. (United States)

    Lupan, Oleg; Schütt, Fabian; Postica, Vasile; Smazna, Daria; Mishra, Yogendra Kumar; Adelung, Rainer


    In this work, the influence of carbon nanotube (CNT) hybridization on ultraviolet (UV) and gas sensing properties of individual and networked ZnO nanowires (NWs) is investigated in detail. The CNT concentration was varied to achieve optimal conditions for the hybrid with improved sensing properties. In case of CNT decorated ZnO nanonetworks, the influence of relative humidity (RH) and applied bias voltage on the UV sensing properties was thoroughly studied. By rising the CNT content to about 2.0 wt% (with respect to the entire ZnO network) the UV sensing response is considerably increased from 150 to 7300 (about 50 times). With respect to gas sensing, the ZnO-CNT networks demonstrate an excellent selectivity as well as a high gas response to NH3 vapor. A response of 430 to 50 ppm at room temperature was obtained, with an estimated detection limit of about 0.4 ppm. Based on those results, several devices consisting of individual ZnO NWs covered with CNTs were fabricated using a FIB/SEM system. The highest sensing performance was obtained for the finest NW with diameter (D) of 100 nm,  with a response of about 4 to 10 ppm NH3 vapor at room temperature.

  18. The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring. (United States)

    Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai


    Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.

  19. Community structure of complex networks based on continuous neural network (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou


    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  20. Carbon- and Nitrogen-Based Organic Frameworks. (United States)

    Sakaushi, Ken; Antonietti, Markus


    This Account provides an overview of organic, covalent, porous frameworks and solid-state materials mainly composed of the elements carbon and nitrogen. The structures under consideration are rather diverse and cover a wide spectrum. This Account will summarize current works on the synthetic concepts leading toward those systems and cover the application side where emphasis is set on the exploration of those systems as candidates for unusual high-performance catalysis, electrocatalysis, electrochemical energy storage, and artificial photosynthesis. These issues are motivated by the new global energy cycles and the fact that sustainable technologies should not be based on rare and expensive resources. We therefore present the strategic design of functionality in cost-effective, affordable artificial materials starting from a spectrum of simple synthetic options to end up with carbon- and nitrogen-based porous frameworks. Following the synthetic strategies, we demonstrate how the electronic structure of polymeric frameworks can be tuned and how this can modify property profiles in a very unexpected fashion. Covalent triazine-based frameworks (CTFs), for instance, showed both enormously high energy and high power density in lithium and sodium battery systems. Other C,N-based organic frameworks, such as triazine-based graphitic carbon nitride, are suggested to show promising band gaps for many (photo)electrochemical reactions. Nitrogen-rich carbonaceous frameworks, which are developed from C,N-based organic framework strategies, are highlighted in order to address their promising electrocatalytic properties, such as in the hydrogen evolution reaction, oxygen reduction reaction (ORR), and oxygen evolution reaction (OER). With careful design, those materials can be multifunctional catalysts, such as a bifunctional ORR/OER electrocatalyst. Although the majority of new C,N-based materials are still not competitive with the best (usually nonsustainable candidates) for each

  1. Quantitative learning strategies based on word networks (United States)

    Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng


    Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

  2. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida


    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  3. Carbon-Nanotube-Based Electrodes for Biomedical Applications (United States)

    Li, Jun; Meyyappan, M.


    A nanotube array based on vertically aligned nanotubes or carbon nanofibers has been invented for use in localized electrical stimulation and recording of electrical responses in selected regions of an animal body, especially including the brain. There are numerous established, emerging, and potential applications for localized electrical stimulation and/or recording, including treatment of Parkinson s disease, Tourette s syndrome, and chronic pain, and research on electrochemical effects involved in neurotransmission. Carbon-nanotube-based electrodes offer potential advantages over metal macroelectrodes (having diameters of the order of a millimeter) and microelectrodes (having various diameters ranging down to tens of microns) heretofore used in such applications. These advantages include the following: a) Stimuli and responses could be localized at finer scales of spatial and temporal resolution, which is at subcellular level, with fewer disturbances to, and less interference from, adjacent regions. b) There would be less risk of hemorrhage on implantation because nano-electrode-based probe tips could be configured to be less traumatic. c) Being more biocompatible than are metal electrodes, carbon-nanotube-based electrodes and arrays would be more suitable for long-term or permanent implantation. d) Unlike macro- and microelectrodes, a nano-electrode could penetrate a cell membrane with minimal disruption. Thus, for example, a nanoelectrode could be used to generate an action potential inside a neuron or in proximity of an active neuron zone. Such stimulation may be much more effective than is extra- or intracellular stimulation via a macro- or microelectrode. e) The large surface area of an array at a micron-scale footprint of non-insulated nanoelectrodes coated with a suitable electrochemically active material containing redox ingredients would make it possible to obtain a pseudocapacitance large enough to dissipate a relatively large amount of electric charge

  4. Carbon nanotube based aliphatic hydrocarbon sensor. (United States)

    Padigi, Sudhaprasanna Kumar; Reddy, Ravi Kiran Kondama; Prasad, Shalini


    A hybrid multi-walled carbon nanotube (MWCNT) based chemical sensor was designed and developed by integration of microfabrication techniques with nano-assembly. This integrated sensing mechanism on a chip, comprised of thiol functionalized MWCNTs that functioned as transducers which were integrated with micro-electrode array measurement sites. The detection of the four fundamental hydrocarbons belonging to the aliphatic hydrocarbon family--methanol, ethanol, propanol and butanol was experimentally demonstrated. High degree of selectivity was demonstrated by repeated robust identification of individual hydro carbons belonging to the same family. The sensor demonstrated 1 ppm detection sensitivity. The detection mechanism was based on nano-scale transduction of the detection of the localized binding event between the functional binding sites and the chemical species of interest. Specific electrical signatures for each of these chemicals were identified using multiple levels of data analysis comprising of Fast Fourier Transformation (FFT) and Power Spectral Density (PSD). The sensor demonstrated a rapid response time with portability, accuracy and versatility for the in situ detection of multiple chemical agents, with potential for automation.

  5. Yeast-based microporous carbon materials for carbon dioxide capture. (United States)

    Shen, Wenzhong; He, Yue; Zhang, Shouchun; Li, Junfen; Fan, Weibin


    A hierarchical microporous carbon material with a Brunauer-Emmett-Teller surface area of 1348 m(2) g(-1) and a pore volume of 0.67 cm(3) g(-1) was prepared from yeast through chemical activation with potassium hydroxide. This type of material contains large numbers of nitrogen-containing groups (nitrogen content >5.3 wt%), and, consequently, basic sites. As a result, this material shows a faster adsorption rate and a higher adsorption capacity of CO(2) than the material obtained by directly carbonizing yeast under the same conditions. The difference is more pronounced in the presence of N(2) or H(2)O, showing that chemical activation of discarded yeast with potassium hydroxide could afford high-performance microporous carbon materials for the capture of CO(2). Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. High Interlaminar Shear Strength Enhancement of Carbon Fiber/Epoxy Composite through Fiber- and Matrix-Anchored Carbon Nanotube Networks. (United States)

    Wang, Yilei; Raman Pillai, Suresh Kumar; Che, Jianfei; Chan-Park, Mary B


    To improve the interlaminar shear strength (ILSS) of carbon fiber reinforced epoxy composite, networks of multiwalled carbon nanotubes (MWNTs) were grown on micron-sized carbon fibers and single-walled carbon nanotubes (SWNTs) were dispersed into the epoxy matrix so that these two types of carbon nanotubes entangle at the carbon fiber (CF)/epoxy matrix interface. The MWNTs on the CF fiber (CF-MWNTs) were grown by chemical vapor deposition (CVD), while the single-walled carbon nanotubes (SWNTs) were finely dispersed in the epoxy matrix precursor with the aid of a dispersing agent polyimide-graft-bisphenol A diglyceryl acrylate (PI-BDA) copolymer. Using vacuum assisted resin transfer molding, the SWNT-laden epoxy matrix precursor was forced into intimate contact with the "hairy" surface of the CF-MWNT fiber. The tube density and the average tube length of the MWNT layer on CF was controlled by the CVD growth time. The ILSS of the CF-MWNT/epoxy resin composite was examined using the short beam shear test. With addition of MWNTs onto the CF surface as well as SWNTs into the epoxy matrix, the ILSS of CF/epoxy resin composite was 47.59 ± 2.26 MPa, which represented a ∼103% increase compared with the composite made with pristine CF and pristine epoxy matrix (without any SWNT filler). FESEM established that the enhanced composite did not fail at the CF/epoxy matrix interface.

  7. Network-based recommendation algorithms: A review (United States)

    Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš


    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

  8. Fixation of carbon dioxide into dimethyl carbonate over titanium-based zeolitic thiophene-benzimidazolate framework (United States)

    A titanium-based zeolitic thiophene-benzimidazolate framework has been designed for the direct synthesis of dimethyl carbonate (DMC) from methanol and carbon dioxide. The developed catalyst activates carbon dioxide and delivers over 16% yield of DMC without the use of any dehydra...

  9. Modeling carrier density dependent charge transport in semiconducting carbon nanotube networks (United States)

    Schießl, Stefan P.; de Vries, Xander; Rother, Marcel; Massé, Andrea; Brohmann, Maximilian; Bobbert, Peter A.; Zaumseil, Jana


    Charge transport in a network of only semiconducting single-walled carbon nanotubes is modeled as a random-resistor network of tube-tube junctions. Solving Kirchhoff's current law with a numerical solver and taking into account the one-dimensional density of states of the nanotubes enables the evaluation of carrier density dependent charge transport properties such as network mobility, local power dissipation, and current distribution. The model allows us to simulate and investigate mixed networks that contain semiconducting nanotubes with different diameters, and thus different band gaps and conduction band edge energies. The obtained results are in good agreement with available experimental data.

  10. Research on Network Scanning Strategy Based on Information Granularity (United States)

    Qin, Futong; Shi, Pengfei; Du, Jing; Cheng, Ruosi; Zhou, Yunyan


    As the basic mean to obtain the information of the targets network, network scanning is often used to discover the security risks and vulnerabilities existing on the network. However, with the development of network technology, the scale of network is more and more large, and the network scanning efficiency put forward higher requirements. In this paper, the concept of network scanning information granularity is proposed, and the design method of network scanning strategy based on information granularity is proposed. Based on single information granularity and hybrid information granularity, four network scanning strategies were designed and verified experimentally. Experiments show that the network scanning strategies based on hybrid information granularity can improve the efficiency of network scanning.

  11. A carbon nanotube based ammonia sensor on cotton textile (United States)

    Han, Jin-Woo; Kim, Beomseok; Li, Jing; Meyyappan, M.


    A single-wall carbon nanotube (CNT) based ammonia (NH3) sensor was implemented on a cotton yarn. Two types of sensors were fabricated: Au/sensing CNT/Au and conducting/sensing/conducting all CNT structures. Two perpendicular Au wires were designed to contact CNT-cotton yarn for metal-CNT sensor, whereas nanotubes were used for the electrode as well as sensing material for the all CNT sensor. The resistance shift of the CNT network upon NH3 was monitored in a chemiresistor approach. The CNT-cotton yarn sensors exhibited uniformity and repeatability. Furthermore, the sensors displayed good mechanical robustness against bending. The present approach can be utilized for low-cost smart textile applications.

  12. Wireless Sensor Network Based Smart Parking System

    Directory of Open Access Journals (Sweden)

    Jeffrey JOSEPH


    Full Text Available Ambient Intelligence is a vision in which various devices come together and process information from multiple sources in order to exert control on the physical environment. In addition to computation and control, communication plays a crucial role in the overall functionality of such a system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment. In this work, an implementation of an energy-efficient and cost-effective, wireless sensor networks based vehicle parking system for a multi-floor indoor parking facility has been introduced. The system monitors the availability of free parking slots and guides the vehicle to the nearest free slot. The amount of time the vehicle has been parked is monitored for billing purposes. The status of the motes (dead/alive is also recorded. Information like slot allocated, directions to the slot and billing data is sent as a message to customer’s mobile phones. This paper extends our previous work 1 with the development of a low cost sensor mote, about one tenth the cost of a commercially available mote, keeping in mind the price sensitive markets of the developing countries.

  13. Dynamics of hate based Internet user networks (United States)

    Sobkowicz, P.; Sobkowicz, A.


    We present a study of the properties of network of political discussions on one of the most popular Polish Internet forums. This provides the opportunity to study the computer mediated human interactions in strongly bipolar environment. The comments of the participants are found to be mostly disagreements, with strong percentage of invective and provocative ones. Binary exchanges (quarrels) play significant role in the network growth and topology. Statistical analysis shows that the growth of the discussions depends on the degree of controversy of the subject and the intensity of personal conflict between the participants. This is in contrast to most previously studied social networks, for example networks of scientific citations, where the nature of the links is much more positive and based on similarity and collaboration rather than opposition and abuse. The work discusses also the implications of the findings for more general studies of consensus formation, where our observations of increased conflict contradict the usual assumptions that interactions between people lead to averaging of opinions and agreement.

  14. Community detection based on network communicability (United States)

    Estrada, Ernesto


    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  15. Community detection based on network communicability. (United States)

    Estrada, Ernesto


    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  16. Carbon Nanotube Based Chemical Sensors for Space and Terrestrial Applications (United States)

    Li, Jing; Lu, Yijiang


    A nanosensor technology has been developed using nanostructures, such as single walled carbon nanotubes (SWNTs), on a pair of interdigitated electrodes (IDE) processed with a silicon-based microfabrication and micromachining technique. The IDE fingers were fabricated using photolithography and thin film metallization techniques. Both in-situ growth of nanostructure materials and casting of the nanostructure dispersions were used to make chemical sensing devices. These sensors have been exposed to nitrogen dioxide, acetone, benzene, nitrotoluene, chlorine, and ammonia in the concentration range of ppm to ppb at room temperature. The electronic molecular sensing of carbon nanotubes in our sensor platform can be understood by intra- and inter-tube electron modulation in terms of charge transfer mechanisms. As a result of the charge transfer, the conductance of p-type or hole-richer SWNTs in air will change. Due to the large surface area, low surface energy barrier and high thermal and mechanical stability, nanostructured chemical sensors potentially can offer higher sensitivity, lower power consumption and better robustness than the state-of-the-art systems, which make them more attractive for defense and space applications. Combined with MEMS technology, light weight and compact size sensors can be made in wafer scale with low cost. Additionally, a wireless capability of such a sensor chip can be used for networked mobile and fixed-site detection and warning systems for military bases, facilities and battlefield areas.

  17. Capacitance-Voltage Characteristics of Thin-film Transistors Fabricated with Solution-Processed Semiconducting Carbon Nanotube Networks. (United States)

    Cai, Le; Zhang, Suoming; Miao, Jinshui; Wei, Qinqin; Wang, Chuan


    We report the capacitance-voltage (C-V) measurements on thin-film transistors (TFTs) using solution-processed semiconducting carbon nanotube networks with different densities and channel lengths. From the measured C-V characteristics, gate capacitance and field-effect mobility (up to ~50 cm(2) V(-1) s(-1)) of the TFTs were evaluated with better precision compared with the results obtained from calculated gate capacitance. The C-V characteristics measured under different frequencies further enabled the extraction and analysis of the interface trap density at the nanotube-dielectric layer interface, which was found to increase significantly as the network density increases. The results presented here indicate that C-V measurement is a powerful tool to assess the electrical performance and to investigate the carrier transport mechanism of TFTs based on carbon nanotubes.

  18. Epoxy-based carbon nanotubes reinforced composites

    CSIR Research Space (South Africa)

    Kesavan Pillai, Sreejarani


    Full Text Available developed strategy offering promising results is to reinforce epoxy matrices with nano-sized organic and inorganic particles such as carbon nanotubes (CNTs), carbon nanofibres (CNFs), nanoclays, metal oxide nanoparticles, etc. and make new materials...

  19. COCARDE: new view on old mounds - an international network of carbonate mound research (United States)

    Rüggeberg, A.; Foubert, A.; Vertino, A.; van Rooij, D.; Spezzaferri, S.; Henriet, J.-P.; Dullo, W.-C.; Cocarde Science Community


    Carbonate mounds are important contributors of life in different settings, from warm-water to cold-water environments, and throughout geological history. Research on modern cold-water coral carbonate mounds over the last decades made a major contribution to our overall understanding of these particular sedimentary systems. By looking to the modern carbonate mound community with cold-water corals as main framework builders, some fundamental questions could be addressed, until now not yet explored in fossil mound settings. The international network COCARDE ( is a platform for exploring new insights in carbonate mound research of recent and ancient mound systems. The aim of the COCARDE network is to bring together scientific communities, studying Recent carbonate mounds in midslope environments in the present ocean and investigating fossil mounds spanning the whole Phanerozoic time, respectively. Scientific challenges in modern and ancient carbonate mound research got well defined during the ESF Magellan Workshop COCARDE in Fribourg, Switzerland (21.-24.01.2009). The Special Volume Cold-water Carbonate Reservoir systems in Deep Environments - COCARDE (Marine Geology, Vol. 282) was the major outcome of this meeting and highlights the diversity of Recent carbonate mound studies. The following first joint Workshop and Field Seminar held in Oviedo, Spain (16.-20.09.2009) highlighted ongoing research from both Recent and fossil academic groups integrating the message from the industry. The field seminar focused on mounds from the Carboniferous platform of Asturias and Cantabria, already intensively visited by industrial and academic researchers. However, by comparing ancient, mixed carbonate-siliciclastic mound systems of Cantabria with the Recent ones in the Porcupine Seabight, striking similarities in their genesis and processes in mound development asked for an integrated drilling campaign to understand better the 3D internal mound build-up. The

  20. Fermentation based carbon nanotube multifunctional bionic composites (United States)

    Valentini, Luca; Bon, Silvia Bittolo; Signetti, Stefano; Tripathi, Manoj; Iacob, Erica; Pugno, Nicola M.


    The exploitation of the processes used by microorganisms to digest nutrients for their growth can be a viable method for the formation of a wide range of so called biogenic materials that have unique properties that are not produced by abiotic processes. Here we produced living hybrid materials by giving to unicellular organisms the nutrient to grow. Based on bread fermentation, a bionic composite made of carbon nanotubes (CNTs) and a single-cell fungi, the Saccharomyces cerevisiae yeast extract, was prepared by fermentation of such microorganisms at room temperature. Scanning electron microscopy analysis suggests that the CNTs were internalized by the cell after fermentation bridging the cells. Tensile tests on dried composite films have been rationalized in terms of a CNT cell bridging mechanism where the strongly enhanced strength of the composite is governed by the adhesion energy between the bridging carbon nanotubes and the matrix. The addition of CNTs also significantly improved the electrical conductivity along with a higher photoconductive activity. The proposed process could lead to the development of more complex and interactive structures programmed to self-assemble into specific patterns, such as those on strain or light sensors that could sense damage or convert light stimulus in an electrical signal.

  1. A cell nanoinjector based on carbon nanotubes

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xing; Kis, Andras; Zettl, Alex; Bertozzi, Carolyn R.


    Technologies for introducing molecules into living cells are vital for probing the physical properties and biochemical interactions that govern the cell's behavior. Here we report the development of a nanoscale cell injection system-termed the nanoinjector-that uses carbon nanotubes to deliver cargo into cells. A single multi-walled carbon nanotube attached to an atomic force microscope tip was functionalized with cargo via a disulfide-based linker. Penetration of cell membranes with this 'nanoneedle', followed by reductive cleavage of the disulfide bonds within the cell's interior, resulted in the release of cargo inside the cells. The capability of the nanoinjector was demonstrated by injection of protein-coated quantum dots into live human cells. Single-particle tracking was employed to characterize the diffusion dynamics of injected quantum dots in the cytosol. This new technique causes no discernible membrane or cell damage, and can deliver a discrete number of molecules to the cell's interior without the requirement of a carrier solvent.

  2. Research of ad hoc network based on SINCGARS network (United States)

    Nie, Hao; Cai, Xiaoxia; Chen, Hong; Chen, Jian; Weng, Pengfei


    In today's world, science and technology make a spurt of progress, so society has entered the era of information technology, network. Only the comprehensive use of electronic warfare and network warfare means can we maximize their access to information and maintain the information superiority. Combined with the specific combat mission and operational requirements, the research design and construction in accordance with the actual military which are Suitable for the future of information technology needs of the tactical Adhoc network, tactical internet, will greatly improve the operational efficiency of the command of the army. Through the study of the network of the U.S. military SINCGARS network, it can explore the routing protocol and mobile model, to provide a reference for the research of our army network.

  3. Electroadsorption Desalination with Carbon Nanotube/PAN-Based Carbon Fiber Felt Composites as Electrodes (United States)

    Liu, Yang; Zhou, Junbo


    The chemical vapor deposition method is used to prepare CNT (carbon nanotube)/PCF (PAN-based carbon fiber felt) composite electrodes in this paper, with the surface morphology of CNT/PCF composites and electroadsorption desalination performance being studied. Results show such electrode materials with three-dimensional network nanostructures having a larger specific surface area and narrower micropore distribution, with a huge number of reactive groups covering the surface. Compared with PCF electrodes, CNT/PCF can allow for a higher adsorption and desorption rate but lower energy consumption; meanwhile, under the condition of the same voltage change, the CNT/PCF electrodes are provided with a better desalination effect. The study also found that the higher the original concentration of the solution, the greater the adsorption capacity and the lower the adsorption rate. At the same time, the higher the solution's pH, the better the desalting; the smaller the ions' radius, the greater the amount of adsorption. PMID:24963504

  4. Real-time network traffic classification technique for wireless local area networks based on compressed sensing (United States)

    Balouchestani, Mohammadreza


    Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

  5. On the synthesis and structure of resorcinol-formaldehyde polymeric networks – Precursors to 3D-carbon macroassemblies

    Energy Technology Data Exchange (ETDEWEB)

    Lewicki, James P.; Fox, Christina A.; Worsley, Marcus A.


    With the new impetus towards the development of hierarchical graphene and CNT macro-assemblies for application in fields such as advanced energy storage, catalysis and electronics; there is much renewed interest in organic carbon-based sol–gel processes as a synthetically convenient and versatile means of forming three dimensional, covalently bonded organic/inorganic networks. Such matrices can act as highly effective precursors, scaffolds or molecular ‘glues’ for the assembly of a wide variety of functional carbon macro-assemblies. However, despite the utility and broad use of organic sol–gel processes – such as the ubiquitous resorcinol-formaldehyde (RF) reaction, there are details of the reaction chemistries of these important sol–gel processes that remain poorly understood at present. It is therefore both timely and necessary to examine these reactions in more detail using modern analytical techniques in order to gain a more rigorous understanding of the mechanisms by which these organic networks form. The goal of such studies is to obtain improved and rational control over the organic network structure, in order to better direct and tailor the architecture of the final inorganic carbon matrix. In this study we have investigated in detail, the mechanism of the organic sol–gel network forming reaction of resorcinol and formaldehyde from a structural and kinetic standpoint, by using a combination of real-time high field solution state nuclear magnetic resonance (NMR), low field NMR relaxometry and differential scanning calorimetry (DSC). These investigations have allowed us to track the network formation processes in real-time, gain both detailed structural information on the mechanisms of the RF sol–gel process and a quantitative assessment of the kinetics of the global network formation process. It has been shown that the mechanism, by which the RF organic network forms, proceeds via an initial exothermic step correlated to the formation of a

  6. Carbon Nanotube-Based Chemiresistive Sensors

    Directory of Open Access Journals (Sweden)

    Ruixian Tang


    Full Text Available The development of simple and low-cost chemical sensors is critically important for improving human life. Many types of chemical sensors have been developed. Among them, the chemiresistive sensors receive particular attention because of their simple structure, the ease of high precise measurement and the low cost. This review mainly focuses on carbon nanotube (CNT-based chemiresistive sensors. We first describe the properties of CNTs and the structure of CNT chemiresistive sensors. Next, the sensing mechanism and the performance parameters of the sensors are discussed. Then, we detail the status of the CNT chemiresistive sensors for detection of different analytes. Lastly, we put forward the remaining challenges for CNT chemiresistive sensors and outlook the possible opportunity for CNT chemiresistive sensors in the future.

  7. Carbon Nanotube-Based Chemiresistive Sensors. (United States)

    Tang, Ruixian; Shi, Yongji; Hou, Zhongyu; Wei, Liangming


    The development of simple and low-cost chemical sensors is critically important for improving human life. Many types of chemical sensors have been developed. Among them, the chemiresistive sensors receive particular attention because of their simple structure, the ease of high precise measurement and the low cost. This review mainly focuses on carbon nanotube (CNT)-based chemiresistive sensors. We first describe the properties of CNTs and the structure of CNT chemiresistive sensors. Next, the sensing mechanism and the performance parameters of the sensors are discussed. Then, we detail the status of the CNT chemiresistive sensors for detection of different analytes. Lastly, we put forward the remaining challenges for CNT chemiresistive sensors and outlook the possible opportunity for CNT chemiresistive sensors in the future.

  8. Receiver Based Traffic Control Mechanism to Protect Low Capacity Network in Infrastructure Based Wireless Mesh Network (United States)

    Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi

    Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.

  9. Virtualized Network Function Orchestration System and Experimental Network Based QR Recognition for a 5G Mobile Access Network

    Directory of Open Access Journals (Sweden)

    Misun Ahn


    Full Text Available This paper proposes a virtualized network function orchestration system based on Network Function Virtualization (NFV, one of the main technologies in 5G mobile networks. This system should provide connectivity between network devices and be able to create flexible network function and distribution. This system focuses more on access networks. By experimenting with various scenarios of user service established and activated in a network, we examine whether rapid adoption of new service is possible and whether network resources can be managed efficiently. The proposed method is based on Bluetooth transfer technology and mesh networking to provide automatic connections between network machines and on a Docker flat form, which is a container virtualization technology for setting and managing key functions. Additionally, the system includes a clustering and recovery measure regarding network function based on the Docker platform. We will briefly introduce the QR code perceived service as a user service to examine the proposal and based on this given service, we evaluate the function of the proposal and present analysis. Through the proposed approach, container relocation has been implemented according to a network device’s CPU usage and we confirm successful service through function evaluation on a real test bed. We estimate QR code recognition speed as the amount of network equipment is gradually increased, improving user service and confirm that the speed of recognition is increased as the assigned number of network devices is increased by the user service.

  10. Electrical behavior of multi-walled carbon nanotube network embedded in amorphous silicon nitride

    Directory of Open Access Journals (Sweden)

    Buiculescu Raluca


    Full Text Available Abstract The electrical behavior of multi-walled carbon nanotube network embedded in amorphous silicon nitride is studied by measuring the voltage and temperature dependences of the current. The microstructure of the network is investigated by cross-sectional transmission electron microscopy. The multi-walled carbon nanotube network has an uniform spatial extension in the silicon nitride matrix. The current-voltage and resistance-temperature characteristics are both linear, proving the metallic behavior of the network. The I-V curves present oscillations that are further analyzed by computing the conductance-voltage characteristics. The conductance presents minima and maxima that appear at the same voltage for both bias polarities, at both 20 and 298 K, and that are not periodic. These oscillations are interpreted as due to percolation processes. The voltage percolation thresholds are identified with the conductance minima.

  11. Optimising TCP for cloud-based mobile networks

    DEFF Research Database (Denmark)

    Artuso, Matteo; Christiansen, Henrik Lehrmann


    Cloud-based mobile networks are foreseen to be a technological enabler for the next generation of mobile networks. Their design requires substantial research as they pose unique challenges, especially from the point of view of additional delays in the fronthaul network. Commonly used network prot...

  12. Optimization of Microporous Carbon Structures for Lithium-Sulfur Battery Applications in Carbonate-Based Electrolyte. (United States)

    Hu, Lei; Lu, Yue; Li, Xiaona; Liang, Jianwen; Huang, Tao; Zhu, Yongchun; Qian, Yitai


    Developing appropriate sulfur cathode materials in carbonate-based electrolyte is an important research subject for lithium-sulfur batteries. Although several microporous carbon materials as host for sulfur reveal the effect, methods for producing microporous carbon are neither easy nor well controllable. Moreover, due to the complexity and limitation of microporous carbon in their fabrication process, there has been rare investigation of influence on electrochemical behavior in the carbonate-based electrolyte for lithium-sulfur batteries by tuning different micropore size(0-2 nm) of carbon host. Here, we demonstrate an immediate carbonization process, self-activation strategy, which can produce microporous carbon for a sulfur host from alkali-complexes. Besides, by changing different alkali-ion in the previous complex, the obtained microporous carbon exhibits a major portion of ultramicropore (micropore structure of the host material plays a vital role in confining sulfur molecule. When evaluated as cathode materials in a carbonate-based electrolyte for Li-S batteries, such microporous carbon/sulfur composite can provide high reversible capacity, cycling stability and good rate capability. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon


    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  14. Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challenges


    Zhang, H.; Liu, N.; Chu, X; Long, K.; Aghvami, A.; Leung, V. C. M.


    The fifth-generation (5G) networks are expected to be able to satisfy users' different quality-of-service (QoS) requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on networ...

  15. The Impact of Carbon Emissions Policies on Reverse Supply Chain Network Design

    Directory of Open Access Journals (Sweden)

    Bandar A. ALKHAYYAL


    Full Text Available Reverse Supply Chain is described as an initiative that plays an important role in the global supply chain for those who seek environmentally responsible solutions for their end-of-life products. The relative economic and environmental benefits of reverse supply chain are influenced by costs and emissions during collection, transportation, recovery facilities, disassembly, recycling, remanufacturing, and disposal of unrecoverable components. The design of reverse supply chain network takes into account social, economic and environmental objectives. This paper addresses the design of reverse supply chain under the three common regulatory policies, strict carbon caps, carbon tax, and carbon cap-and-trade.

  16. Control of neuronal network organization by chemical surface functionalization of multi-walled carbon nanotube arrays

    Energy Technology Data Exchange (ETDEWEB)

    Liu Jie; Bibari, Olivier; Marchand, Gilles; Benabid, Alim-Louis; Sauter-Starace, Fabien [CEA, LETI-Minatec, 17 Rue des Martyrs, 38054 Grenoble Cedex 9 (France); Appaix, Florence; De Waard, Michel, E-mail:, E-mail: [Inserm U836, Grenoble Institute of Neuroscience, Site Sante la Tronche, Batiment Edmond J Safra, Chemin Fortune Ferrini, BP170, 38042 Grenoble Cedex 09 (France)


    Carbon nanotube substrates are promising candidates for biological applications and devices. Interfacing of these carbon nanotubes with neurons can be controlled by chemical modifications. In this study, we investigated how chemical surface functionalization of multi-walled carbon nanotube arrays (MWNT-A) influences neuronal adhesion and network organization. Functionalization of MWNT-A dramatically modifies the length of neurite fascicles, cluster inter-connection success rate, and the percentage of neurites that escape from the clusters. We propose that chemical functionalization represents a method of choice for developing applications in which neuronal patterning on MWNT-A substrates is required.

  17. A morphological investigation of conductive networks in polymers loaded with carbon nanotubes

    KAUST Repository

    Lubineau, Gilles


    Loading polymers with conductive nanoparticles, such as carbon nanotubes, is a popular approach toward improving their electrical properties. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. Because these conductive particles are only capable of charge transfer over a very short range, most do not interact with the percolated paths nor do they participate to the electrical transfer. Understanding how these particles are arranged is necessary to increase their efficiency. It is of special interest to understand how these particles participate in creating percolated clusters, either in a specific or in all directions, and non-percolated clusters. For this, we present a computational modeling strategy based on a full morphological analysis of a network to systematically analyse conductive networks and show how particles are arranged. This study provides useful information for designing these types of materials and examples suitable for characterizing important features, such as representative volume element, the role of nanotube tortuosity and the role of tunneling cutoff distance.

  18. Community Detection for Multiplex Social Networks Based on Relational Bayesian Networks

    DEFF Research Database (Denmark)

    Jiang, Jiuchuan; Jaeger, Manfred


    . In this paper we propose to use relational Bayesian networks for the specification of probabilistic network models, and develop inference techniques that solve the community detection problem based on these models. The use of relational Bayesian networks as a flexible high-level modeling framework enables us......Many techniques have been proposed for community detection in social networks. Most of these techniques are only designed for networks defined by a single relation. However, many real networks are multiplex networks that contain multiple types of relations and different attributes on the nodes...

  19. Dynamic Object Identification with SOM-based neural networks

    Directory of Open Access Journals (Sweden)

    Aleksey Averkin


    Full Text Available In this article a number of neural networks based on self-organizing maps, that can be successfully used for dynamic object identification, is described. Unique SOM-based modular neural networks with vector quantized associative memory and recurrent self-organizing maps as modules are presented. The structured algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results and comparison with some other neural networks are given.

  20. Harvesting a 3D N-Doped Carbon Network from Waste Bean Dregs by Ionothermal Carbonization as an Electrocatalyst for an Oxygen Reduction Reaction

    Directory of Open Access Journals (Sweden)

    Yimai Chen


    Full Text Available Three-dimensional nitrogen-doped carbon (3D-NCN has been synthesized via the ionothermal carbonization method using waste soybean dregs (SD as the precursor. N2 adsorption/desorption isotherms show that the as-prepared 3D-NCN formed a hierarchically porous structure with a specific BET surface area of 1093.4 m2 g−1 and a total pore volume of 1.77 cm3 g−1. The TEM images clearly show that graphene-like carbon sheets were formed on the edge of the networks. The characterization of the samples collected at different temperature indicated that salt melt plays the key role in the formation of the network structure and rich pores. When 3D-NCN is as electrocatalyst for ORR, it shows an onset potential of 0.945 V with a more positive half-wave potential (0.846 V, which is comparable to that of commercial Pt/C. In addition, the long-term cycle results show that the onset potential and half-wave potential only negatively shifted by 6 mV and 8 mV after 10,000 cycles respectively, which are smaller than those values of commercial Pt/C. Due to its high ORR activity, durability, and low-cost, producing 3D-NCN from SD in molten salt medium provides a promising approach to replace the Pt-based catalysts for use in fuel cells.

  1. Network-based automation for SMEs

    DEFF Research Database (Denmark)

    Parizi, Mohammad Shahabeddini; Radziwon, Agnieszka


    could be obtained through network interaction. Based on two extreme cases of SMEs representing low-tech industry and an in-depth analysis of their manufacturing facilities this paper presents how collaboration between firms embedded in a regional ecosystem could result in implementation of new...... automation solutions. The empirical data collection involved application of a combination of comparative case study method with action research elements. This article provides an outlook over the challenges in implementing technological improvements and the way how it could be resolved in collaboration......, this paper develops and discusses a set of guidelines for systematic productivity improvement within an innovative collaboration in regards to automation processes in SMEs....


    Directory of Open Access Journals (Sweden)

    Hakan KAPTAN


    Full Text Available As a result of developing on Internet and computer fields, web based education becomes one of the area that many improving and research studies are done. In this study, web based education materials have been explained for multimedia animation and simulation aided Computer Networks course in Technical Education Faculties. Course content is formed by use of university course books, web based education materials and technology web pages of companies. Course content is formed by texts, pictures and figures to increase motivation of students and facilities of learning some topics are supported by animations. Furthermore to help working principles of routing algorithms and congestion control algorithms simulators are constructed in order to interactive learning

  3. A Critical Review of Glucose Biosensors Based on Carbon Nanomaterials: Carbon Nanotubes and Graphene

    Directory of Open Access Journals (Sweden)

    William I. Milne


    Full Text Available There has been an explosion of research into the physical and chemical properties of carbon-based nanomaterials, since the discovery of carbon nanotubes (CNTs by Iijima in 1991. Carbon nanomaterials offer unique advantages in several areas, like high surface-volume ratio, high electrical conductivity, chemical stability and strong mechanical strength, and are thus frequently being incorporated into sensing elements. Carbon nanomaterial-based sensors generally have higher sensitivities and a lower detection limit than conventional ones. In this review, a brief history of glucose biosensors is firstly presented. The carbon nanotube and grapheme-based biosensors, are introduced in Sections 3 and 4, respectively, which cover synthesis methods, up-to-date sensing approaches and nonenzymatic hybrid sensors. Finally, we briefly outline the current status and future direction for carbon nanomaterials to be used in the sensing area.

  4. CUFID-query: accurate network querying through random walk based network flow estimation. (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun


    Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

  5. Highly Enhanced Vapor Sensing of Multiwalled Carbon Nanotube Network Sensors by n-Butylamine Functionalization

    Directory of Open Access Journals (Sweden)

    P. Slobodian


    Full Text Available The sensing of volatile organic compounds by multiwall carbon nanotube networks of randomly entangled pristine nanotubes or the nanotubes functionalized by n-butylamine, which were deposited on polyurethane supporting electrospinned nonwoven membrane, has been investigated. The results show that the sensing of volatile organic compounds by functionalized nanotubes considerably increases with respect to pristine nanotubes. The increase is highly dependent on used vapor polarity. For the case of highly polar methanol, the functionalized MWCNT network exhibits even more than eightfold higher sensitivity in comparison to the network prepared from pristine nanotubes.

  6. Embedded Carbon Nanotube Networks for Damage Precursor Detection (United States)


    Black-Filled Polymeric Concrete . Polymer Engineering and Science 2000, 40 (9), 2101–2104. 12 List of Symbols, Abbreviations, and Acronyms A0...system with CNT- reinforced epoxy. Epoxy is widely used in vehicles, particularly aerospace vehicles, where fiber - reinforced epoxy is integral to the...Monitoring of Glass Fiber Reinforced Composites Using Embedded Carbon Nanotube (CNT) Fibers . Composites Science and Technology 2009, 70 (2), 260–271

  7. The implementation of a standards based heterogeneous network

    Energy Technology Data Exchange (ETDEWEB)

    Eldridge, J.M.; Tolendino, L.F.


    Computer networks, supporting an organization's activities, are prevalent and very important to the organization's mission. Implementing a heterogenous organizational network allows the staff to select the computing environment that best supports their job requirements. This paper outlines the lessons learned implementing a heterogenous computer network based on networking standards such as TCP/IP and Ethernet. Such a network is a viable alternative to a proprietary, vendor supported network and can provide all the functionality customers expect in a computer network. 2 figs.

  8. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle


    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  9. Development of softwood kraft lignin based carbon fibers


    Nordström, Ylva


    The polymer composites designed for high-performance applications are mostly based on carbon fiber reinforcement. The two most common precursors used currently for carbon fiber production are poly(acrylonitrile) and pitch (petroleum- or coal- based). As of today, the most promising alternative to these fossil originated raw materials is lignin. Previous research has mainly focused on carbon fiber production from pre-treated hardwood lignin with the addition of different softening agents. Soft...

  10. Carbon nanomaterial-based electrochemical biosensors: an overview (United States)

    Wang, Zhaoyin; Dai, Zhihui


    Carbon materials on the nanoscale exhibit diverse outstanding properties, rendering them extremely suitable for the fabrication of electrochemical biosensors. Over the past two decades, advances in this area have continuously emerged. In this review, we attempt to survey the recent developments of electrochemical biosensors based on six types of carbon nanomaterials (CNs), i.e., graphene, carbon nanotubes, carbon dots, carbon nanofibers, nanodiamonds and buckminsterfullerene. For each material, representative samples are introduced to expound the different roles of the CNs in electrochemical bioanalytical strategies. In addition, remaining challenges and perspectives for future developments are also briefly discussed.

  11. An electron-rich free-standing carbon@Au core-shell nanofiber network as a highly active and recyclable catalyst for the reduction of 4-nitrophenol. (United States)

    Zhang, Peng; Shao, Changlu; Li, Xinghua; Zhang, Mingyi; Zhang, Xin; Su, Chunyan; Lu, Na; Wang, Kexin; Liu, Yichun


    A three-dimensional (3D) free-standing network composed of cross-linked carbon@Au core-shell nanofibers was fabricated by combining the electrospinning technique and an in situ reduction approach. The results showed that a uniform Au layer of approximately 5 nm thickness was formed around the electrospun carbon nanofiber. What's more, it's interesting to note that the Au layer was composed of small Au nanoparticles. And, the as-prepared CNFs@Au network exhibited excellent catalytic activity for the reduction of 4-nitrophenol (4-NP) based on the electron-rich catalytic platform arising from the synergistic effect between carbon and Au. Notably, the free-standing 3D nanofibrous cross-linked network structure could improve the catalyst's performance in separation and reuse.

  12. High Performance Ambipolar Field-Effect Transistor of Random Network Carbon Nanotubes

    NARCIS (Netherlands)

    Bisri, Satria Zulkarnaen; Gao, Jia; Derenskyi, Vladimir; Gomulya, Widianta; Iezhokin, Igor; Gordiichuk, Pavlo; Herrmann, Andreas; Loi, Maria Antonietta


    Ambipolar field-effect transistors of random network carbon nanotubes are fabricated from an enriched dispersion utilizing a conjugated polymer as the selective purifying medium. The devices exhibit high mobility values for both holes and electrons (3 cm(2)/V.s) with a high on/off ratio (10(6)). The

  13. Hierarchical and Multifunctional Three-dimensional Network of Carbon Nanotubes for Supercapacitor and Strain Sensor Applications (United States)


    for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection...Collaborations that Resulted from this AOARD Supported Project a) papers published in non-peer- reviewed journals and conference proceedings 1. Seo...Hierarchical Three-dimensional Network of Carbon Nanotubes for Biosensor Applications, 2013 INST Symposium “Bioinspired Namomaterials and Systems“, 2013

  14. Dynamics of carbon dioxide transport in a multiple sink network (GHGT-11)

    NARCIS (Netherlands)

    Veltin, J.; Belfroid, S.P.C.


    As Carbon Capture and Storage slowly gets accepted and integrated as a mean for cleaner utilization of fossil fuels, the integration of capture, transport and storage becomes a key component to properly design a CO2 network. While the boundary conditions set by the capture and storage units have

  15. Highly Stable Carbon Nanotube/Polyaniline Porous Network for Multifunctional Applications. (United States)

    Zhao, Wenqi; Li, Yibin; Wu, Shiting; Wang, Dezhi; Zhao, Xu; Xu, Fan; Zou, Mingchu; Zhang, Hui; He, Xiaodong; Cao, Anyuan


    Three-dimensional carbon nanotube (CNT) networks with high porosity and electrical conductivity have many potential applications in energy and environmental areas, but the network structure is not very stable due to weak inter-CNT interactions. Here, we coat a thin polyaniline (PANI) layer on as-synthesized CNT sponge to obtain a mechanically and electrically stable network, and enable multifunctional applications. The resulting CNT/PANI network serves as stable strain sensors, highly compressible supercapacitor electrode with enhanced volume-normalized capacitance (632 F/cm3), and reinforced nanocomposites with the PANI as intermediate layer between the CNT fillers and polymeric matrix. Our results provide a simple and controllable method for achieving high-stability porous networks composed of CNTs, graphene, or other nanostructures.

  16. UPM: unified policy-based network management (United States)

    Law, Eddie; Saxena, Achint


    Besides providing network management to the Internet, it has become essential to offer different Quality of Service (QoS) to users. Policy-based management provides control on network routers to achieve this goal. The Internet Engineering Task Force (IETF) has proposed a two-tier architecture whose implementation is based on the Common Open Policy Service (COPS) protocol and Lightweight Directory Access Protocol (LDAP). However, there are several limitations to this design such as scalability and cross-vendor hardware compatibility. To address these issues, we present a functionally enhanced multi-tier policy management architecture design in this paper. Several extensions are introduced thereby adding flexibility and scalability. In particular, an intermediate entity between the policy server and policy rule database called the Policy Enforcement Agent (PEA) is introduced. By keeping internal data in a common format, using a standard protocol, and by interpreting and translating request and decision messages from multi-vendor hardware, this agent allows a dynamic Unified Information Model throughout the architecture. We have tailor-made this unique information system to save policy rules in the directory server and allow executions of policy rules with dynamic addition of new equipment during run-time.

  17. Paper-based Synthetic Gene Networks (United States)

    Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.


    Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167

  18. Resilient Disaster Network Based on Software Defined Cognitive Wireless Network Technology

    Directory of Open Access Journals (Sweden)

    Goshi Sato


    Full Text Available In order to temporally recover the information network infrastructure in disaster areas from the Great East Japan Earthquake in 2011, various wireless network technologies such as satellite IP network, 3G, and Wi-Fi were effectively used. However, since those wireless networks are individually introduced and installed but not totally integrated, some of networks were congested due to the sudden network traffic generation and unbalanced traffic distribution, and eventually the total network could not effectively function. In this paper, we propose a disaster resilient network which integrates various wireless networks into a cognitive wireless network that users can use as an access network to the Internet at the serious disaster occurrence. We designed and developed the disaster resilient network based on software defined network (SDN technology to automatically select the best network link and route among the possible access networks to the Internet by periodically monitoring their network states and evaluate those using extended AHP method. In order to verify the usefulness of our proposed system, a prototype system is constructed and its performance is evaluated.



    Taylor, Dane; MYERS, SEAN A.; Clauset, Aaron; Porter, Mason A.; Mucha, Peter J.


    Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centralit...

  20. Process based modelling of soil organic carbon redistribution on landscape scale (United States)

    Schindewolf, Marcus; Seher, Wiebke; Amorim, Amorim S. S.; Maeso, Daniel L.; Jürgen, Schmidt


    Recent studies have pointed out the great importance of erosion processes in global carbon cycling. Continuous erosion leads to a massive loss of top soils including the loss of organic carbon accumulated over long time in the soil humus fraction. Lal (2003) estimates that 20% of the organic carbon eroded with top soils is emitted into atmosphere, due to aggregate breakdown and carbon mineralization during transport by surface runoff. Furthermore soil erosion causes a progressive decrease of natural soil fertility, since cation exchange capacity is associated with organic colloids. As a consequence the ability of soils to accumulate organic carbon is reduced proportionately to the drop in soil productivity. The colluvial organic carbon might be protected from further degradation depending on the depth of the colluvial cover and local decomposing conditions. Some colluvial sites can act as long-term sinks for organic carbon. The erosional transport of organic carbon may have an effect on the global carbon budget, however, it is uncertain, whether erosion is a sink or a source for carbon in the atmosphere. Another part of eroded soils and organic carbon will enter surface water bodies and might be transported over long distances. These sediments might be deposited in the riparian zones of river networks. Erosional losses of organic carbon will not pass over into atmosphere for the most part. But soil erosion limits substantially the potential of soils to sequester atmospheric CO2 by generating humus. The present study refers to lateral carbon flux modelling on landscape scale using the process based EROSION 3D soil loss simulation model, using existing parameter values. The selective nature of soil erosion results in a preferentially transport of fine particles while less carbonic larger particles remain on site. Consequently organic carbon is enriched in the eroded sediment compared to the origin soil. For this reason it is essential that EROSION 3D provides the

  1. Bacterial Cellulose: A Robust Platform for Design of Three Dimensional Carbon-Based Functional Nanomaterials. (United States)

    Wu, Zhen-Yu; Liang, Hai-Wei; Chen, Li-Feng; Hu, Bi-Cheng; Yu, Shu-Hong


    Three dimensional (3D) carbon nanomaterials exhibit great application potential in environmental protection, electrochemical energy storage and conversion, catalysis, polymer science, and advanced sensors fields. Current methods for preparing 3D carbon nanomaterials, for example, carbonization of organogels, chemical vapor deposition, and self-assembly of nanocarbon building blocks, inevitably involve some drawbacks, such as expensive and toxic precursors, complex equipment and technological requirements, and low production ability. From the viewpoint of practical application, it is highly desirable to develop a simple, cheap, and environmentally friendly way for fabricating 3D carbon nanomaterials in large scale. On the other hand, in order to extend the application scope and improve the performance of 3D carbon nanomaterials, we should explore efficient strategies to prepare diverse functional nanomaterials based on their 3D carbon structure. Recently, many researchers tend to fabricate high-performance 3D carbon-based nanomaterials from biomass, which is low cost, easy to obtain, and nontoxic to humans. Bacterial cellulose (BC), a typical biomass material, has long been used as the raw material of nata-de-coco (an indigenous dessert food of the Philippines). It consists of a polysaccharide with a β-1,4-glycosidic linkage and has a interconnected 3D porous network structure. Interestingly, the network is made up of a random assembly of cellulose nanofibers, which have a high aspect ratio with a diameter of 20-100 nm. As a result, BC has a high specific surface area. Additionally, BC hydrogels can be produced on an industrial scale via a microbial fermentation process at a very low price. Thus, it can be an ideal platform for design of 3D carbon-based functional nanomaterials. Before our work, no systematic work and summary on this topic had been reported. This Account presents the concepts and strategies of our studies on BC in the past few years, that is

  2. Communication Network Architectures Based on Ethernet Passive Optical Network for Offshore Wind Power Farms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Ahmed


    Full Text Available Nowadays, with large-scale offshore wind power farms (WPFs becoming a reality, more efforts are needed to maintain a reliable communication network for WPF monitoring. Deployment topologies, redundancy, and network availability are the main items to enhance the communication reliability between wind turbines (WTs and control centers. Traditional communication networks for monitoring and control (i.e., supervisory control and data acquisition (SCADA systems using switched gigabit Ethernet will not be sufficient for the huge amount of data passing through the network. In this paper, the optical power budget, optical path loss, reliability, and network cost of the proposed Ethernet Passive Optical Network (EPON-based communication network for small-size offshore WPFs have been evaluated for five different network architectures. The proposed network model consists of an optical network unit device (ONU deployed on the WT side for collecting data from different internal networks. All ONUs from different WTs are connected to a central optical line terminal (OLT, placed in the control center. There are no active electronic elements used between the ONUs and the OLT, which reduces the costs and complexity of maintenance and deployment. As fiber access networks without any protection are characterized by poor reliability, three different protection schemes have been configured, explained, and discussed. Considering the cost of network components, the total implementation expense of different architectures with, or without, protection have been calculated and compared. The proposed network model can significantly contribute to the communication network architecture for next generation WPFs.

  3. Network-Based and Binless Frequency Analyses.

    Directory of Open Access Journals (Sweden)

    Sybil Derrible

    Full Text Available We introduce and develop a new network-based and binless methodology to perform frequency analyses and produce histograms. In contrast with traditional frequency analysis techniques that use fixed intervals to bin values, we place a range ±ζ around each individual value in a data set and count the number of values within that range, which allows us to compare every single value of a data set with one another. In essence, the methodology is identical to the construction of a network, where two values are connected if they lie within a given a range (±ζ. The value with the highest degree (i.e., most connections is therefore assimilated to the mode of the distribution. To select an optimal range, we look at the stability of the proportion of nodes in the largest cluster. The methodology is validated by sampling 12 typical distributions, and it is applied to a number of real-world data sets with both spatial and temporal components. The methodology can be applied to any data set and provides a robust means to uncover meaningful patterns and trends. A free python script and a tutorial are also made available to facilitate the application of the method.

  4. Network video transmission system based on SOPC (United States)

    Zhang, Zhengbing; Deng, Huiping; Xia, Zhenhua


    Video systems have been widely used in many fields such as conferences, public security, military affairs and medical treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system. In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application program scheme is proposed.

  5. Object Classification Using Substance Based Neural Network

    Directory of Open Access Journals (Sweden)

    P. Sengottuvelan


    Full Text Available Object recognition has shown tremendous increase in the field of image analysis. The required set of image objects is identified and retrieved on the basis of object recognition. In this paper, we propose a novel classification technique called substance based image classification (SIC using a wavelet neural network. The foremost task of SIC is to remove the surrounding regions from an image to reduce the misclassified portion and to effectively reflect the shape of an object. At first, the image to be extracted is performed with SIC system through the segmentation of the image. Next, in order to attain more accurate information, with the extracted set of regions, the wavelet transform is applied for extracting the configured set of features. Finally, using the neural network classifier model, misclassification over the given natural images and further background images are removed from the given natural image using the LSEG segmentation. Moreover, to increase the accuracy of object classification, SIC system involves the removal of the regions in the surrounding image. Performance evaluation reveals that the proposed SIC system reduces the occurrence of misclassification and reflects the exact shape of an object to approximately 10–15%.

  6. Carbon nanotube based functional superhydrophobic coatings (United States)

    Sethi, Sunny

    The main objective of this dissertation is synthesis of carbon nanotube (CNT) based superhydrophobic materials. The materials were designed such that electrical and mechanical properties of CNTs could be combined with superhydrophobicity to create materials with unique properties, such as self-cleaning adhesives, miniature flotation devices, ice-repellant coatings, and coatings for heat transfer furnaces. The coatings were divided into two broad categories based on CNT structure: Vertically aligned CNT arrays (VA coatings) and mesh-like (non-aligned) carbon nanotube arrays (NA coatings). VA coatings were used to create self-cleaning adhesives and flexible field emission devices. Coatings with self cleaning property along with high adhesiveness were inspired from structure found on gecko foot. Gecko foot is covered with thousands of microscopic hairs called setae; these setae are further divided into hundreds of nanometer sized hairs called spatulas. When gecko presses its foot against any surface, these hairs bend and conform to the topology of the surface resulting into very large area of contact. Such large area of intimate contact allows geckos to adhere to surfaces using van der Waals (vdW) interactions alone. VA-CNTs adhere to a variety of surfaces using a similar mechanism. CNTs of suitable diameter could withstand four times higher adhesion force than gecko foot. We found that upon soiling these CNT based adhesives (gecko tape) could be cleaned using a water droplet (lotus effect) or by applying vibrations. These materials could be used for applications requiring reversible adhesion. VA coatings were also used for developing field emission devices. A single CNT can emit electrons at very low threshold voltages. Achieving efficient electron emission on large scale has a lot of challenges such as screening effect, pull-off and lower current efficiency. We have explored the use of polymer-CNT composite structures to overcome these challenges in this work. NA

  7. Flexible Tube-Based Network Control Project (United States)

    National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...

  8. nanoparticles-decorated activated carbon nanocomposite based ...

    Indian Academy of Sciences (India)



    decorated activated carbon. (AC) nanocomposite for selective detection of dopamine (DA) in the presence of uric acid (UA) and ascorbic acid (AA). The nanocomposite was prepared by a simple hydrothermal method and the ...

  9. Carbon nanotube based stationary phases for microchip chromatography

    DEFF Research Database (Denmark)

    Mogensen, Klaus Bo; Kutter, Jörg Peter


    The objective of this article is to provide an overview and critical evaluation of the use of carbon nanotubes and related carbon-based nanomaterials for microchip chromatography. The unique properties of carbon nanotubes, such as a very high surface area and intriguing adsorptive behaviour, have...... already been demonstrated in more classical formats, for improved separation performance in gas and liquid chromatography, and for unique applications in solid phase extraction. Carbon nanotubes are now also entering the field of microfluidics, where there is a large potential to be able to provide...... integrated, tailor-made nanotube columns by means of catalytic growth of the nanotubes inside the fluidic channels. An evaluation of the different implementations of carbon nanotubes and related carbon-based nanomaterials for microfluidic chromatography devices is given in terms of separation performance...

  10. Carbon-based Supercapacitors Produced by Activation of Graphene

    Energy Technology Data Exchange (ETDEWEB)

    Y Zhu; S Murali; M Stoller; K Ganesh; W Cai; P Ferreira; A Pirkle; R Wallace; K Cychosz; et al.


    Supercapacitors, also called ultracapacitors or electrochemical capacitors, store electrical charge on high-surface-area conducting materials. Their widespread use is limited by their low energy storage density and relatively high effective series resistance. Using chemical activation of exfoliated graphite oxide, we synthesized a porous carbon with a Brunauer-Emmett-Teller surface area of up to 3100 square meters per gram, a high electrical conductivity, and a low oxygen and hydrogen content. This sp{sup 2}-bonded carbon has a continuous three-dimensional network of highly curved, atom-thick walls that form primarily 0.6- to 5-nanometer-width pores. Two-electrode supercapacitor cells constructed with this carbon yielded high values of gravimetric capacitance and energy density with organic and ionic liquid electrolytes. The processes used to make this carbon are readily scalable to industrial levels.

  11. Selective breakdown of metallic pathways in double-walled carbon nanotube networks. (United States)

    Ng, Allen L; Sun, Yong; Powell, Lyndsey; Sun, Chuan-Fu; Chen, Chien-Fu; Lee, Cheng S; Wang, YuHuang


    Covalently functionalized, semiconducting double-walled carbon nanotubes exhibit remarkable properties and can outperform their single-walled carbon nanotube counterparts. In order to harness their potential for electronic applications, metallic double-walled carbon nanotubes must be separated from the semiconductors. However, the inner wall is inaccessible to current separation techniques which rely on the surface properties. Here, the first approach to address this challenge through electrical breakdown of metallic double-walled carbon nanotubes, both inner and outer walls, within networks of mixed electronic types is described. The intact semiconductors demonstrate a ∼62% retention of the ON-state conductance in thin film transistors in response to covalent functionalization. The selective elimination of the metallic pathways improves the ON/OFF ratio, by more than 360 times, to as high as 40 700, while simultaneously retaining high ON-state conductance. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Personalized Network-Based Treatments in Oncology

    DEFF Research Database (Denmark)

    Robin, Xavier; Creixell, Pau; Radetskaya, Oxana


    Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technol...

  13. Analysis of neural networks through base functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

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

  14. Measurement-Based Network Link Dimensioning

    NARCIS (Netherlands)

    de Oliveira Schmidt, R.; van den Berg, Hans Leo; Pras, Aiko

    The ever increasing traffic demands and the current trend of network and services virtualization calls for effective approaches for optimal use of network resources. In the future Internet multiple virtual networks will coexist on top of the same physical infrastructure, and these will compete for

  15. Measurement-based network link dimensioning

    NARCIS (Netherlands)

    Schmidt, R. de O.; Den Berg, J.L. van den; Pras, A.


    The ever increasing traffic demands and the current trend of network and services virtualization calls for effective approaches for optimal use of network resources. In the future Internet multiple virtual networks will coexist on top of the same physical infrastructure, and these will compete for

  16. Effect of tetrahedral amorphous carbon coating on the resistivity and wear of single-walled carbon nanotube network

    Energy Technology Data Exchange (ETDEWEB)

    Iyer, Ajai, E-mail:; Etula, Jarkko; Liu, Xuwen; Koskinen, Jari [Department of Materials Science and Engineering, School of Chemical Technology, Aalto University, P.O. Box 16200, 00076 Espoo (Finland); Kaskela, Antti; Kauppinen, Esko I. [NanoMaterials Group, Department of Applied Physics, School of Science, Aalto University, P.O. Box 15100, 00076 Espoo (Finland); Novikov, Serguei [Department of Micro and Nanosciences, Aalto University, P.O. Box 13500, 00076 Aalto (Finland)


    Single walled carbon nanotube networks (SWCNTNs) were coated by tetrahedral amorphous carbon (ta-C) to improve the mechanical wear properties of the composite film. The ta-C deposition was performed by using pulsed filtered cathodic vacuum arc method resulting in the generation of C+ ions in the energy range of 40–60 eV which coalesce to form a ta-C film. The primary disadvantage of this process is a significant increase in the electrical resistance of the SWCNTN post coating. The increase in the SWCNTN resistance is attributed primarily to the intrinsic stress of the ta-C coating which affects the inter-bundle junction resistance between the SWCNTN bundles. E-beam evaporated carbon was deposited on the SWCNTNs prior to the ta-C deposition in order to protect the SWCNTN from the intrinsic stress of the ta-C film. The causes of changes in electrical resistance and the effect of evaporated carbon thickness on the changes in electrical resistance and mechanical wear properties have been studied.

  17. Multifunctional Flexible Composites Based on Continuous Carbon Nanotube Fiber (United States)


    emitters, solid-phase microextraction and catalysis . Different from graphene- based aerogels (GBAs) and membranes (GBMs), GBFs have demonstrated...nanotube dry-spun yarns, Carbon, 48, 2802–2811, 2010. 22. A. S. Wu and T. -W. Chou. Carbon nanotube fibers for advanced composites, Materials Today , 15...Applied Physics Letters, 100, 201908, 2012. 8. A. S. Wu and T. -W. Chou. Carbon nanotube fibers for advanced composites, Materials Today , 15, 302

  18. Cooperative UAV-Based Communications Backbone for Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, R S


    The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs are used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.

  19. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie


    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  20. Classification of complex networks based on similarity of topological network features (United States)

    Attar, Niousha; Aliakbary, Sadegh


    Over the past few decades, networks have been widely used to model real-world phenomena. Real-world networks exhibit nontrivial topological characteristics and therefore, many network models are proposed in the literature for generating graphs that are similar to real networks. Network models reproduce nontrivial properties such as long-tail degree distributions or high clustering coefficients. In this context, we encounter the problem of selecting the network model that best fits a given real-world network. The need for a model selection method reveals the network classification problem, in which a target-network is classified into one of the candidate network models. In this paper, we propose a novel network classification method which is independent of the network size and employs an alignment-free metric of network comparison. The proposed method is based on supervised machine learning algorithms and utilizes the topological similarities of networks for the classification task. The experiments show that the proposed method outperforms state-of-the-art methods with respect to classification accuracy, time efficiency, and robustness to noise.

  1. Formation of interfacial network structure via photo-crosslinking in carbon fiber/epoxy composites

    Directory of Open Access Journals (Sweden)

    S. H. Deng


    Full Text Available A series of diblock copolymers (poly(n-butylacrylate-co-poly(2-hydroxyethyl acrylate-b-poly(glycidyl methacrylate ((PnBA-co-PHEA-b-PGMA, containing a random copolymer block PnBA-co-PHEA, were successfully synthesized by atom transfer radical polymerization (ATRP. After being chemically grafted onto carbon fibers, the photosensitive methacrylic groups were introduced into the random copolymer, giving a series of copolymers (poly(n-butylacrylate-co-poly(2-methacryloyloxyethyl acrylate-b-poly(glycidyl methacrylate((PnBA-co-PMEA-b-PGMA. Dynamic mechanical analysis indicated that the random copolymer block after ultraviolet (UV irradiation was a lightly crosslinked polymer and acted as an elastomer, forming a photo-crosslinked network structure at the interface of carbon fiber/epoxy composites. Microbond test showed that such an interfacial network structure greatly improved the cohesive strength and effectively controlled the deformation ability of the flexible interlayer. Furthermore, three kinds of interfacial network structures, i physical crosslinking by H-bonds, ii chemical crosslinking by photopolymerization, and iii interpenetrating crosslinked network by photopolymerization and epoxy curing reaction were received in carbon fiber/epoxy composite, depending on the various preparation processes.

  2. Analysis of Computer Network Information Based on "Big Data" (United States)

    Li, Tianli


    With the development of the current era, computer network and large data gradually become part of the people's life, people use the computer to provide convenience for their own life, but at the same time there are many network information problems has to pay attention. This paper analyzes the information security of computer network based on "big data" analysis, and puts forward some solutions.

  3. On Emulation-Based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Abbasi, Ali; Wetzel, Jos; Bokslag, Wouter; Zambon, Emmanuele; Etalle, Sandro


    Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an in- strumented environment and checking the execution traces for signs of shellcode activity.

  4. Survey-Based Measurement of Public Management and Policy Networks (United States)

    Henry, Adam Douglas; Lubell, Mark; McCoy, Michael


    Networks have become a central concept in the policy and public management literature; however, theoretical development is hindered by a lack of attention to the empirical properties of network measurement methods. This paper compares three survey-based methods for measuring organizational networks: the roster, the free-recall name generator, and…

  5. Novel Ethernet Based Optical Local Area Networks for Computer Interconnection

    NARCIS (Netherlands)

    Radovanovic, Igor; van Etten, Wim; Taniman, R.O.; Kleinkiskamp, Ronny


    In this paper we present new optical local area networks for fiber-to-the-desk application. Presented networks are expected to bring a solution for having optical fibers all the way to computers. To bring the overall implementation costs down we have based our networks on short-wavelength optical

  6. Network Medicine: A Network-based Approach to Human Disease (United States)

    Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph


    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

  7. A Cascade-Based Emergency Model for Water Distribution Network

    Directory of Open Access Journals (Sweden)

    Qing Shuang


    Full Text Available Water distribution network is important in the critical physical infrastructure systems. The paper studies the emergency resource strategies on water distribution network with the approach of complex network and cascading failures. The model of cascade-based emergency for water distribution network is built. The cascade-based model considers the network topology analysis and hydraulic analysis to provide a more realistic result. A load redistribution function with emergency recovery mechanisms is established. From the aspects of uniform distribution, node betweenness, and node pressure, six recovery strategies are given to reflect the network topology and the failure information, respectively. The recovery strategies are evaluated with the complex network indicators to describe the failure scale and failure velocity. The proposed method is applied by an illustrative example. The results showed that the recovery strategy considering the node pressure can enhance the network robustness effectively. Besides, this strategy can reduce the failure nodes and generate the least failure nodes per time.

  8. Catalytic Coupling of Carbon Dioxide with Terpene Scaffolds: Access to Challenging Bio-Based Organic Carbonates. (United States)

    Fiorani, Giulia; Stuck, Moritz; Martín, Carmen; Belmonte, Marta Martínez; Martin, Eddy; Escudero-Adán, Eduardo C; Kleij, Arjan W


    The challenging coupling of highly substituted terpene oxides and carbon dioxide into bio-based cyclic organic carbonates catalyzed by Al(aminotriphenolate) complexes is reported. Both acyclic as well as cyclic terpene oxides were used as coupling partners, showing distinct reactivity/selectivity behavior. Whereas cyclic terpene oxides showed excellent chemoselectivity towards the organic carbonate product, acyclic substrates exhibited poorer selectivities owing to concomitant epoxide rearrangement reactions and the formation of undesired oligo/polyether side products. Considering the challenging nature of these coupling reactions, the isolated yields of the targeted bio-carbonates are reasonable and in most cases in the range 50-60 %. The first crystal structures of tri-substituted terpene based cyclic carbonates are reported and their stereoconnectivity suggests that their formation proceeds through a double inversion pathway. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Arresting Strategy Based on Dynamic Criminal Networks Changing over Time

    Directory of Open Access Journals (Sweden)

    Junqing Yuan


    Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.

  10. Ultrathin single-walled carbon nanotube network framed graphene hybrids. (United States)

    Wang, Rui; Hong, Tu; Xu, Ya-Qiong


    Graphene and single-walled carbon nanotubes (SWNTs) have shown superior potential in electronics and optoelectronics because of their excellent thermal, mechanical, electronic, and optical properties. Here, a simple method is developed to synthesize ultrathin SWNT-graphene films through chemical vapor deposition. These novel two-dimensional hybrids show enhanced mechanical strength that allows them to float on water without polymer supporting layers. Characterizations by Raman spectroscopy and transmission electron microscopy indicate that SWNTs can interlace as a concrete backbone for the subsequent growth of monolayer graphene. Optical and electrical transport measurements further show that SWNT-graphene hybrids inherit high optical transparency and superior electrical conductivity from monolayer graphene. We also explore the local optoelectronic properties of SWNT-graphene hybrids through spatially resolved photocurrent microscopy and find that the interactions between SWNTs and graphene can induce a strong photocurrent response in the areas where SWNTs link different graphene domains together. These fundamental studies may open a door for engineering optoelectronic properties of SWNT-graphene hybrids by controlling the morphologies of the SWNT frames.

  11. Analysis of friendship network from MMORPG based data


    Črnigoj, Dean


    This work analyzes friendship network from a Massively Multiplayer Online Role-Playing Game (MMORPG). The network is based on data from a private server that was active from 2007 until 2011. The work conducts a standard analysis of the network and then divides players according to different groups based on their activity. Work checks how friendship network can be correlated to the clan (a self-organized group of players who often form a league and play on the same side in a match) network. Ma...

  12. Using an artificial neural network to predict carbon dioxide compressibility factor at high pressure and temperature

    Energy Technology Data Exchange (ETDEWEB)

    Mohagheghian, Erfan [Memorial University of Newfoundland, St. John' s (Canada); Zafarian-Rigaki, Habiballah; Motamedi-Ghahfarrokhi, Yaser; Hemmati-Sarapardeh, Abdolhossein [Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)


    Carbon dioxide injection, which is widely used as an enhanced oil recovery (EOR) method, has the potential of being coupled with CO{sub 2} sequestration and reducing the emission of greenhouse gas. Hence, knowing the compressibility factor of carbon dioxide is of a vital significance. Compressibility factor (Z-factor) is traditionally measured through time consuming, expensive and cumbersome experiments. Hence, developing a fast, robust and accurate model for its estimation is necessary. In this study, a new reliable model on the basis of feed forward artificial neural networks is presented to predict CO{sub 2} compressibility factor. Reduced temperature and pressure were selected as the input parameters of the proposed model. To evaluate and compare the results of the developed model with pre-existing models, both statistical and graphical error analyses were employed. The results indicated that the proposed model is more reliable and accurate compared to pre-existing models in a wide range of temperature (up to 1,273.15 K) and pressure (up to 140MPa). Furthermore, by employing the relevancy factor, the effect of pressure and temprature on the Z-factor of CO{sub 2} was compared for below and above the critical pressure of CO{sub 2}, and the physcially expected trends were observed. Finally, to identify the probable outliers and applicability domain of the proposed ANN model, both numerical and graphical techniques based on Leverage approach were performed. The results illustrated that only 1.75% of the experimental data points were located out of the applicability domain of the proposed model. As a result, the developed model is reliable for the prediction of CO{sub 2} compressibility factor.

  13. Repairable Woven Carbon Fiber Composites with Full Recyclability Enabled by Malleable Polyimine Networks. (United States)

    Taynton, Philip; Ni, Huagang; Zhu, Chengpu; Yu, Kai; Loob, Samuel; Jin, Yinghua; Qi, H Jerry; Zhang, Wei


    Carbon-fiber reinforced composites are prepared using catalyst-free malleable polyimine networks as binders. An energy neutral closed-loop recycling process has been developed, enabling recovery of 100% of the imine components and carbon fibers in their original form. Polyimine films made using >21% recycled content exhibit no loss of mechanical performance, therefore indicating all of the thermoset composite material can be recycled and reused for the same purpose. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. City-based Carbon Budgets for Buildings

    DEFF Research Database (Denmark)

    Lütken, Søren; Wretlind, Per Harry

    this restriction contingent upon documented compliance - leaving it up to the sector itself to document its carbon footprint. A parallel is drawn to the dissemination of ISO standards 9001 and 14001, where quality and environmental demands from decisive commercial actors spread through the supply chain. The paper...... emissions through carbon budgets for construction they would act in their own self-interest. Adopting the model they would and will ultimately deliver a ground breaking initiative for cutting global emissions at scale – beyond that of the construction sector. If the ISO experience has any merit, it suggests...

  15. The geometrical effect of single walled carbon nanotube network transistors on low frequency noise characteristics. (United States)

    Kim, Un Jeong; Kil, Joon Pyo; Park, Wanjun


    The noise characteristics of randomly networked single walled carbon nanotubes grown directly by plasma enhanced chemical vapor deposition with field effect transistor. Geometrical complexity due to the large number of tube-tube junctions in the nanotube network is expected to be one of the key factors for the noise power of 1/f dependence. We investigated low frequency noise as a function of channel length (2-10 microm) and found that increased with longer channel length. Percolational behaviors of nanotube network that differs from ordinary semiconducting and metallic materials can be characterized by a geometrical picture with electrical homo- and hetero-junctions. Fixed nanotube density provides a test conditions to evaluate the contributions of junctions as a noise center. Hooge's empirical law is applied to investigate the low frequency noise characteristics of single walled carbon nanotube random network transistors. The noise power shows the dependence of the transistor channel length. It is understood that nanotube/nanotube junctions act as a noise center. However, the differences induced by channel length in the noise power are observed as not so significant. We conclude that tolerance of low frequency noise is important property for SWNT networks as an electronic device application.

  16. Paintable Carbon-Based Perovskite Solar Cells with Engineered Perovskite/Carbon Interface Using Carbon Nanotubes Dripping Method. (United States)

    Ryu, Jaehoon; Lee, Kisu; Yun, Juyoung; Yu, Haejun; Lee, Jungsup; Jang, Jyongsik


    Paintable carbon electrode-based perovskite solar cells (PSCs) are of particular interest due to their material and fabrication process costs, as well as their moisture stability. However, printing the carbon paste on the perovskite layer limits the quality of the interface between the perovskite layer and carbon electrode. Herein, an attempt to enhance the performance of the paintable carbon-based PSCs is made using a modified solvent dripping method that involves dripping of the carbon nanotubes (CNTs), which is dispersed in chlorobenzene solution. This method allows CNTs to penetrate into both the perovskite film and carbon electrode, facilitating fast hole transport between the two layers. Furthermore, this method is results in increased open circuit voltage (Voc ) and fill factor (FF), providing better contact at the perovskite/carbon interfaces. The best devices made with CNT dripping show 13.57% power conversion efficiency and hysteresis-free performance. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Nenad Kojić


    Full Text Available The networking infrastructure of wireless mesh networks (WMNs is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—i.e., neural networks (NNs. This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission. The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

  18. A neural networks-based hybrid routing protocol for wireless mesh networks. (United States)

    Kojić, Nenad; Reljin, Irini; Reljin, Branimir


    The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

  19. Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks. (United States)

    Castet, Jean-Francois; Saleh, Joseph H


    This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the

  20. Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks.

    Directory of Open Access Journals (Sweden)

    Jean-Francois Castet

    Full Text Available This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also

  1. X-ray photoemission spectroscopy analysis of N-containing carbon-based cathode catalysts for polymer electrolyte fuel cells (United States)

    Niwa, Hideharu; Kobayashi, Masaki; Horiba, Koji; Harada, Yoshihisa; Oshima, Masaharu; Terakura, Kiyoyuki; Ikeda, Takashi; Koshigoe, Yuka; Ozaki, Jun-ichi; Miyata, Seizo; Ueda, Shigenori; Yamashita, Yoshiyuki; Yoshikawa, Hideki; Kobayashi, Keisuke

    We report on the electronic structure of three different types of N-containing carbon-based cathode catalysts for polymer electrolyte fuel cells observed by hard X-ray photoemission spectroscopy. Prepared samples are derived from: (1) melamine and poly(furfuryl alcohol), (2) nitrogen-doped carbon black and (3) cobalt phthalocyanine and phenolic resin. C 1 s spectra show the importance of sp 2 carbon network formation for the oxygen reduction reaction (ORR) activity. N 1 s spectra of the carbon-based cathode catalysts are decomposed into four components identified as pyridine-like, pyrrole- or cyanide-like, graphite-like, and oxide nitrogen. Samples having high oxygen reduction reaction activity in terms of oxygen reduction potential contain high concentration of graphite-like nitrogen. O 1 s spectra are similar among carbon-based cathode catalysts of different oxygen reduction reaction activity. There is no correlation between the ORR activity and oxygen content. Based on a quantitative analysis of our results, the oxygen reduction reaction activity of the carbon-based cathode catalysts will be improved by increasing concentration of graphite-like nitrogen in a developed sp 2 carbon network.

  2. X-ray photoemission spectroscopy analysis of N-containing carbon-based cathode catalysts for polymer electrolyte fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Niwa, Hideharu [Department of Applied Chemistry, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Kobayashi, Masaki; Horiba, Koji; Harada, Yoshihisa; Oshima, Masaharu [Department of Applied Chemistry, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Synchrotron Radiation Research Organization, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Terakura, Kiyoyuki [Research Center for Integrated Science, Japan Advanced Institute of Science Technology (JAIST), 1-1 Asahidai, Nomi Ishikawa 923-1292 (Japan); Ikeda, Takashi [Quantum Beam Science Directorate, Japan Atomic Energy Agency (JAEA), SPring-8, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Koshigoe, Yuka; Ozaki, Jun-ichi [Department of Chemical and Environmental Engineering, Graduate School of Engineering, Gunma University, 1-5-1 Tenjin-cho, Kiryu, Gunma 376-8515 (Japan); Miyata, Seizo [New Energy and Industrial Technology Development Organization, 1310 Omiya-cho, Saiwai-ku, Kawasaki, Kanagawa 212-8554 (Japan); Ueda, Shigenori; Yamashita, Yoshiyuki; Yoshikawa, Hideki; Kobayashi, Keisuke [National Institute for Materials Science (NIMS), SPring-8, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan)


    We report on the electronic structure of three different types of N-containing carbon-based cathode catalysts for polymer electrolyte fuel cells observed by hard X-ray photoemission spectroscopy. Prepared samples are derived from: (1) melamine and poly(furfuryl alcohol), (2) nitrogen-doped carbon black and (3) cobalt phthalocyanine and phenolic resin. C 1s spectra show the importance of sp{sup 2} carbon network formation for the oxygen reduction reaction (ORR) activity. N 1s spectra of the carbon-based cathode catalysts are decomposed into four components identified as pyridine-like, pyrrole- or cyanide-like, graphite-like, and oxide nitrogen. Samples having high oxygen reduction reaction activity in terms of oxygen reduction potential contain high concentration of graphite-like nitrogen. O 1s spectra are similar among carbon-based cathode catalysts of different oxygen reduction reaction activity. There is no correlation between the ORR activity and oxygen content. Based on a quantitative analysis of our results, the oxygen reduction reaction activity of the carbon-based cathode catalysts will be improved by increasing concentration of graphite-like nitrogen in a developed sp{sup 2} carbon network. (author)

  3. Neural network based system for equipment surveillance (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.


    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  4. Resorcinol–formaldehyde based carbon nanospheres by ...

    Indian Academy of Sciences (India)

    Carbon nanospheres were synthesized using sol–gel processing of organic and aqueous resorcinol formaldehyde (RF) sols combined with electrospraying technique. RF sol was electrosprayed to form nanodroplets which were collected on a Si wafer. After oven drying at 60°C for 12 h, RF nano-droplets were pyrolyzed at ...

  5. Biocompatibility of bio based calcium carbonate nanocrystals ...

    African Journals Online (AJOL)

    Material and Methods: Transmission and field emission scanning electron microscopy (TEM and FESEM) were used for the characterisation of CaCO3 nanocrystals. Cytotoxicity and genotoxic effect of calcium carbonate nanocrystals in cultured mouse embryonic fibroblast NIH 3T3 cell line using various bioassays including ...

  6. Carbon Nanotube Based Devices for Intracellular Analysis (United States)

    Singhal, Riju Mohan

    Scientific investigations on individual cells have gained increasing attention in recent years as efforts are being made to understand cellular functioning in complex processes, such as cell division during embryonic development, and owing to realization of heterogeneity amongst a population of a single cell type (for instance, certain individual cancer cells being immune to chemotherapy). Therefore devices enabling electrochemical detection, spectroscopy, optical observations, and separation techniques, along with cell piercing and fluid transfer capabilities at the intra-cellular level, are required. Glass pipettes have conventionally been used for single cell interrogation, however their poor mechanical properties and an intrusive conical geometry have led to limited precision and frequent cell damage or death, justifying research efforts to develop novel, non-intrusive cell probes. Carbon nanotubes (CNTs) are known for their superior physical properties and tunable chemical structure. They possess a high aspect ratio and offer minimally invasive thin carbon walls and tubular geometry. Moreover, possibility of chemical functionalization of CNTs enables multi-functional probes. In this dissertation, novel nanofluidic instruments that have nanostructured carbon tips will be presented along with techniques that utilize the exceptional physical properties of carbon nanotubes, to take miniature biomedical instrumentation to the next level. New methods for fabricating the probes were rigorously developed and their operation was extensively studied. The devices were mechanically robust and were used to inject liquids to a single cell, detect electrochemical signals and enable surface enhanced Raman spectroscopy (SERS) while inducing minimal harm to the cell. Particular attention was focused on the CVD process-which was used to deposit carbon, fluid flow through the nanotubes, and separation of chemical species (atto-liter chromatography) at the nanometer scale that

  7. Carbon nanotube thin film transistors based on aerosol methods. (United States)

    Zavodchikova, Marina Y; Kulmala, Tero; Nasibulin, Albert G; Ermolov, Vladimir; Franssila, Sami; Grigoras, Kestutis; Kauppinen, Esko I


    We demonstrate a fabrication method for high-performance field-effect transistors (FETs) based on dry-processed random single-walled carbon nanotube networks (CNTNs) deposited at room temperature. This method is an advantageous alternative to solution-processed and direct CVD grown CNTN FETs, which allows using various substrate materials, including heat-intolerant plastic substrates, and enables an efficient, density-controlled, scalable deposition of as-produced single-walled CNTNs on the substrate directly from the aerosol (floating catalyst) synthesis reactor. Two types of thin film transistor (TFT) structures were fabricated to evaluate the FET performance of dry-processed CNTNs: bottom-gate transistors on Si/SiO2 substrates and top-gate transistors on polymer substrates. Devices exhibited on/off ratios up to 10(5) and field-effect mobilities up to 4 cm(2) V(-1) s(-1). The suppression of hysteresis in the bottom-gate device transfer characteristics by means of thermal treatment in vacuum and passivation by an atomic layer deposited Al(2)O(3) film was investigated. A 32 nm thick Al(2)O(3) layer was found to be able to eliminate the hysteresis.

  8. Optimized network of multi-walled carbon nanotubes for chemical sensing (United States)

    Gohier, A.; Chancolon, J.; Chenevier, P.; Porterat, D.; Mayne-L'Hermite, M.; Reynaud, C.


    This work reports the design of a resistive gas sensor based on 2D mats of multi-walled carbon nanotubes (MWCNTs) grown by aerosol-assisted chemical vapour deposition. The sensor sensitivity was optimized using chlorine as analyte by tuning both CNT network morphology and CNT electronic properties. Optimized devices, operating at room temperature, have been calibrated over a large range of concentration and are shown to be sensitive down to 27 ppb of chlorine. The as-grown MWCNT response is compared with responses of 2000 °C annealed CNTs, as well as of nitrogen-doped CNTs and CNTs functionalized with polyethyleneimine (PEI). Under chlorine exposure, the resistance decrease of as-grown and annealed CNTs is attributed to charge transfer from chlorine to CNTs and demonstrates their p-type semiconductor behaviour. XPS analysis of CNTs exposed to chlorine shows the presence of chloride species that confirms electron charge transfer from chlorine to CNTs. By contrast, the resistance of nitrogen-doped and PEI functionalized CNTs exposed to chlorine increases, in agreement with their n-type semiconductor nature. The best response is obtained using annealed CNTs and is attributed to their higher degree of crystallinity.

  9. Dynamics of subway networks based on vehicles operation timetable (United States)

    Xiao, Xue-mei; Jia, Li-min; Wang, Yan-hui


    In this paper, a subway network is represented as a dynamic, directed and weighted graph, in which vertices represent subway stations and weights of edges represent the number of vehicles passing through the edges by considering vehicles operation timetable. Meanwhile the definitions of static and dynamic metrics which can represent vertices' and edges' local and global attributes are proposed. Based on the model and metrics, standard deviation is further introduced to study the dynamic properties (heterogeneity and vulnerability) of subway networks. Through a detailed analysis of the Beijing subway network, we conclude that with the existing network structure, the heterogeneity and vulnerability of the Beijing subway network varies over time when the vehicle operation timetable is taken into consideration, and the distribution of edge weights affects the performance of the network. In other words, although the vehicles operation timetable is restrained by the physical structure of the network, it determines the performances and properties of the Beijing subway network.

  10. The guitar chord-generating algorithm based on complex network (United States)

    Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais


    This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.

  11. Fabrication of network films of conducting polymer-linked polyoxometallate-stabilized carbon nanostructures

    Energy Technology Data Exchange (ETDEWEB)

    Kulesza, Pawel J.; Skunik, Magdalena; Baranowska, Beata; Miecznikowski, Krzysztof; Chojak, Malgorzata; Karnicka, Katarzyna; Starobrzynska, Barbara; Ernst, Andrzej [Department of Chemistry, University of Warsaw, Pasteura 1, PL-02-093 Warsaw (Poland); Frackowiak, Elzbieta [ICTE, Poznan University of Technology, Piotrowo 3, PL-60-965 Poznan (Poland); Beguin, Francois [CRMD, CNRS-University, 1B, rue de la Ferollerie, F-45071 Orleans Cedex 02 (France); Kuhn, Alexander [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire Ecole Nationale Superieure de Chimie et de Physique de Bordeaux, 16 avenue Pey Berland, 33607 Pessac (France); Delville, Marie-Helene [Institut de Chimie de la Matiere Condensee de Bordeaux, 87 Avenue du Dr. Schweitzer, 33608 Pessac Cedex (France)


    The ability of a Keggin-type polyoxometallate, phosphododecamolybdate (PMo{sub 12}O{sub 40}{sup 3-}), to form stable anionic monolayers on carbon nanoparticles and multi-wall nanotubes is explored here to produce stable colloidal solutions of polyoxometallate covered carbon nanostructures and to disperse them within conducting polymer, poly(3,4-ethylenedioxythiophene), i.e. PEDOT, or polyaniline multilayer films. By repeated alternate treatments in the colloidal suspension of PMo{sub 12}O{sub 40}{sup 3-}-protected carbon nanoparticles or nanotubes, and in the acid solution of a monomer (3,4-ethylenedioxythiophene or aniline), the amount of the material can be increased systematically (layer-by-layer) to form stable three-dimensional organized arrangements (networks) of interconnected organic and inorganic layers on electrode (e.g. glassy carbon) surfaces. In hybrid films, the negatively charged polyoxometallate-covered carbon nanostructures interact electrostatically with positively charged conducting polymer ultra-thin layers. Consequently, the attractive electrochemical charging properties of conducting polymers, reversible redox behavior of polyoxometallate, as well as the mechanical and electrical properties of carbon nanoparticles or nanotubes can be combined. The films are characterized by fast dynamics of charge transport, and they are of potential importance to electrocatalysis and charge storage in redox capacitors. (author)

  12. Three dimensional (3D percolation network structure: Key to form stable carbon nano grease

    Directory of Open Access Journals (Sweden)

    Hammad Younes


    Full Text Available Nano grease is found to be stable and homogeneous (wherein carbon nanotubes act as sole thickeners and oil is polyalphaolefin (PAO. This is a good indication that three dimensional (3D percolation network structures among carbon nanotubes (single wall and multi wall play a crucial role in stabilization. To better understand this assumption and provide further evidence, some additional carbon nanomaterials, such as carbon nanofiber (CNF, graphene, fullerene (C60, Ni-coated single wall carbon nanotube (SWNT, are selected to make the grease. Unfortunately, CNF, graphene, fullerene (C60 and Ni-coated SWNT do not form stable greases as nanotubes do. In addition, SWNTs were mixed with CNF and Ni-coated SWNT respectively to see if stable grease could be formed. The results indicate that the CNF/SWNT did not form the stable grease, while Ni-coated SWNT/SWNT did. Inter molecular Van der Waals forces could reasonably explain these experimental results. Appropriate tube size (nanotube and nanofiber, stereo structure (nanotube, graphene and fullerene, surface energy (nanotube and Ni-coated nanotube are critical factors that determine if Van der Waals forces could take effect or not. The scientific merit of this paper is that we understand in what manner stable greases are formed and what kinds of carbon materials are appropriate for acting as sole thickener.

  13. Evidence That Calls-Based and Mobility Networks Are Isomorphic.

    Directory of Open Access Journals (Sweden)

    Michele Coscia

    Full Text Available Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable.

  14. Networks as Power Bases for School Improvement (United States)

    Moore, Tessa A.; Kelly, Michael P.


    Although there is limited research into the success of primary school networking initiatives in the UK, there is a drive at national government level for promoting school collaborative working arrangements as a catalyst for whole-school improvement. This paper discusses the findings from research into two such initiatives: "Networked Learning…

  15. A novel multi-walled carbon nanotube (MWNT)-based ...

    Indian Academy of Sciences (India)

    walled carbon nanotube (MWNT)-based nanocomposite for PEFC electrodes ... A novel nanocomposite comprising MWNTs and mixed-conducting polymeric components (electronic and ionic) is prepared, characterized and investigated as a ...

  16. High-Conductance Thermal Interfaces Based on Carbon Nanotubes Project (United States)

    National Aeronautics and Space Administration — We propose to develop a novel thermal interface material (TIM) that is based on an array of vertical carbon nanotubes (CNTs) for high heat flux applications. For...

  17. Electrochemical Biosensors Based on Nanostructured Carbon Black: A Review

    National Research Council Canada - National Science Library

    Tiago Almeida Silva; Fernando Cruz Moraes; Bruno Campos Janegitz; Orlando Fatibello-Filho


    .... Several studies have explored the applicability of CB in electrochemical fields. Recent data showed that modified electrodes based on CB present fast charge transfer and high electroactive surface area, comparable to carbon nanotubes and graphene...

  18. Certificate Based Security Services in Adhoc Sensor Network


    Shahin Fatima; Shish Ahmad; P. M. Khan


    The paper entitled “CERTIFICATE BASED SECURITY SERVICES IN ADHOC SENSOR NETWORK” proposed an approach in which the aim is to find the method for authentication which is more energy efficient and reduces the transmission time of the network. MANETs are of dynamic topology and have no predefined infrastructure. Due to its dynamic topology this network is prone to various kinds of vulnerable attacks. Sensor networks are battery operated and is a major concern. Methods on ID based Authentication ...

  19. Greening radio access networks using distributed base station architectures

    DEFF Research Database (Denmark)

    Kardaras, Georgios; Soler, José; Dittmann, Lars


    . However besides this, increasing energy efficiency represents a key factor for reducing operating expenses and deploying cost effective mobile networks. This paper presents how distributed base station architectures can contribute in greening radio access networks. More specifically, the advantages...... energy saving. Different subsystems have to be coordinated real-time and intelligent network nodes supporting complicated functionalities are necessary. Distributed base station architectures are ideal for this purpose mainly because of their high degree of configurability and self...

  20. Energy Constraint Node Cache Based Routing Protocol For Adhoc Network


    Dhiraj Nitnaware; Ajay Verma


    Mobile Adhoc Networks (MANETs) is a wireless infrastructureless network, where nodes are free to move independently in any direction. The nodes have limited battery power; hence we require energy efficient routing protocols to optimize network performance. This paper aims to develop a new routing algorithm based on the energy status of the node cache. We have named this algorithm as ECNC_AODV (Energy Constraint Node Cache) based routing protocol which is derived from the AODV protocol. The al...

  1. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani


    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  2. A Network Formation Model Based on Subgraphs

    CERN Document Server

    Chandrasekhar, Arun


    We develop a new class of random-graph models for the statistical estimation of network formation that allow for substantial correlation in links. Various subgraphs (e.g., links, triangles, cliques, stars) are generated and their union results in a network. We provide estimation techniques for recovering the rates at which the underlying subgraphs were formed. We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure is used to enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics. We also establish asymptotic properties of the models and various estimators, which requires proving a new Central Limit Theorem for correlated random variables.

  3. Biofunctionalized 3-D Carbon Nano-Network Platform for Enhanced Fibroblast Cell Adhesion (United States)

    Chowdhury, A. K. M. Rezaul Haque; Tavangar, Amirhossein; Tan, Bo; Venkatakrishnan, Krishnan


    Carbon nanomaterials have been investigated for various biomedical applications. In most cases, however, these nanomaterials must be functionalized biologically or chemically due to their biological inertness or possible cytotoxicity. Here, we report the development of a new carbon nanomaterial with a bioactive phase that significantly promotes cell adhesion. We synthesize the bioactive phase by introducing self-assembled nanotopography and altered nano-chemistry to graphite substrates using ultrafast laser. To the best of our knowledge, this is the first time that such a cytophilic bio-carbon is developed in a single step without requiring subsequent biological/chemical treatments. By controlling the nano-network concentration and chemistry, we develop platforms with different degrees of cell cytophilicity. We study quantitatively and qualitatively the cell response to nano-network platforms with NIH-3T3 fibroblasts. The findings from the in vitro study indicate that the platforms possess excellent biocompatibility and promote cell adhesion considerably. The study of the cell morphology shows a healthy attachment of cells with a well-spread shape, overextended actin filaments, and morphological symmetry, which is indicative of a high cellular interaction with the nano-network. The developed nanomaterial possesses great biocompatibility and considerably stimulates cell adhesion and subsequent cell proliferation, thus offering a promising path toward engineering various biomedical devices. PMID:28287138

  4. Synergistic effect in conductive networks constructed with carbon nanofillers in different dimensions

    Directory of Open Access Journals (Sweden)

    Q. Fu


    Full Text Available Herein, investigation on synergistic effect during network formation for conductive network constructed with carbon nanofillers in different dimensions is conducted. Multi-walled carbon nanotubes (MWNTs and carbon black (CB are employed as conductive fillers in this system. Morphological control of the conductive network is realized by adjusting the ratio between different fillers. Classical percolation threshold theory and adjusted excluded volume theory are used to analyze the electrical percolating behavior of these systems. It is observed that the percolation threshold of hybrid fillers filled conductive polymer composites (CPCs is much lower than that of MWNTs or CB filled CPCs, and it can be reduced from 2.4 to 0.21 wt% by replacing half of the MWNTs with CB. Possible mechanism of this phenomenon is discussed together with morphological observation. A model is proposed to understand the mechanism of the percolation behavior in the composites containing various proportions of nanofillers. Our work is important for the design and preparation of low cost conductive polymer composites with novel electrical property.

  5. Network capacity with probit-based stochastic user equilibrium problem. (United States)

    Lu, Lili; Wang, Jian; Zheng, Pengjun; Wang, Wei


    Among different stochastic user equilibrium (SUE) traffic assignment models, the Logit-based stochastic user equilibrium (SUE) is extensively investigated by researchers. It is constantly formulated as the low-level problem to describe the drivers' route choice behavior in bi-level problems such as network design, toll optimization et al. The Probit-based SUE model receives far less attention compared with Logit-based model albeit the assignment result is more consistent with drivers' behavior. It is well-known that due to the identical and irrelevant alternative (IIA) assumption, the Logit-based SUE model is incapable to deal with route overlapping problem and cannot account for perception variance with respect to trips. This paper aims to explore the network capacity with Probit-based traffic assignment model and investigate the differences of it is with Logit-based SUE traffic assignment models. The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers' route choice. A heuristic algorithm based on sensitivity analysis of SUE problem is detailed presented to solve the proposed bi-level program. Three numerical example networks are used to discuss the differences of network capacity between Logit-based SUE constraint and Probit-based SUE constraint. This study finds that while the network capacity show different results between Probit-based SUE and Logit-based SUE constraints, the variation pattern of network capacity with respect to increased level of travelers' information for general network under the two type of SUE problems is the same, and with certain level of travelers' information, both of them can achieve the same maximum network capacity.

  6. Carbon Nanotube Tower-Based Supercapacitor (United States)

    Meyyappan, Meyya (Inventor)


    A supercapacitor system, including (i) first and second, spaced apart planar collectors, (ii) first and second arrays of multi-wall carbon nanotube (MWCNT) towers or single wall carbon nanotube (SWCNT) towers, serving as electrodes, that extend between the first and second collectors where the nanotube towers are grown directly on the collector surfaces without deposition of a catalyst and without deposition of a binder material on the collector surfaces, and (iii) a porous separator module having a transverse area that is substantially the same as the transverse area of at least one electrode, where (iv) at least one nanotube tower is functionalized to permit or encourage the tower to behave as a hydrophilic structure, with increased surface wettability.

  7. A Spectrum Handoff Scheme for Optimal Network Selection in NEMO Based Cognitive Radio Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Krishan Kumar


    Full Text Available When a mobile network changes its point of attachments in Cognitive Radio (CR vehicular networks, the Mobile Router (MR requires spectrum handoff. Network Mobility (NEMO in CR vehicular networks is concerned with the management of this movement. In future NEMO based CR vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. The CR vehicular node may have the capability to make call for two or more types of nonsafety services such as voice, video, and best effort simultaneously. Hence, it becomes difficult for MR to select optimal network for the spectrum handoff. This can be done by performing spectrum handoff using Multiple Attributes Decision Making (MADM methods which is the objective of the paper. The MADM methods such as grey relational analysis and cost based methods are used. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results reveal that the proposed scheme is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.

  8. Wireless and embedded carbon nanotube networks for damage detection in concrete structures. (United States)

    Saafi, Mohamed


    Concrete structures undergo an uncontrollable damage process manifesting in the form of cracks due to the coupling of fatigue loading and environmental effects. In order to achieve long-term durability and performance, continuous health monitoring systems are needed to make critical decisions regarding operation, maintenance and repairs. Recent advances in nanostructured materials such as carbon nanotubes have opened the door for new smart and advanced sensing materials that could effectively be used in health monitoring of structures where wireless and real time sensing could provide information on damage development. In this paper, carbon nanotube networks were embedded into a cement matrix to develop an in situ wireless and embedded sensor for damage detection in concrete structures. By wirelessly measuring the change in the electrical resistance of the carbon nanotube networks, the progress of damage can be detected and monitored. As a proof of concept, wireless cement-carbon nanotube sensors were embedded into concrete beams and subjected to monotonic and cyclic loading to evaluate the effect of damage on their response. Experimental results showed that the wireless response of the embedded nanotube sensors changes due to the formation of cracks during loading. In addition, the nanotube sensors were able to detect the initiation of damage at an early stage of loading.

  9. Engineering highly organized and aligned single walled carbon nanotube networks for electronic device applications: Interconnects, chemical sensor, and optoelectronics (United States)

    Kim, Young Lae

    For 20 years, single walled carbon nanotubes (SWNTs) have been studied actively due to their unique one-dimensional nanostructure and superior electrical, thermal, and mechanical properties. For these reasons, they offer the potential to serve as building blocks for future electronic devices such as field effect transistors (FETs), electromechanical devices, and various sensors. In order to realize these applications, it is crucial to develop a simple, scalable, and reliable nanomanufacturing process that controllably places aligned SWNTs in desired locations, orientations, and dimensions. Also electronic properties (semiconducting/metallic) of SWNTs and their organized networks must be controlled for the desired performance of devices and systems. These fundamental challenges are significantly limiting the use of SWNTs for future electronic device applications. Here, we demonstrate a strategy to fabricate highly controlled micro/nanoscale SWNT network structures and present the related assembly mechanism to engineer the SWNT network topology and its electrical transport properties. A method designed to evaluate the electrical reliability of such nano- and microscale SWNT networks is also presented. Moreover, we develop and investigate a robust SWNT based multifunctional selective chemical sensor and a range of multifunctional optoelectronic switches, photo-transistors, optoelectronic logic gates and complex optoelectronic digital circuits.

  10. Improving Student Engagement Using Course-Based Social Networks (United States)

    Imlawi, Jehad Mohammad


    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  11. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole


    of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...

  12. J2EE-based integrated telecom network management (United States)

    Xia, Zhongwu; Wei, Guo


    The paper will present a J2EE-based architecture of integrated telecom network management system, and also will introduce the MVC(Model, View and Control) design pattern in the architecture. Using J2EE and MVC design pattern, we can easily build multiple user interfaces (included Web-based), flexible, manageable, and extensible network management system.

  13. Electrical characterization and microwave application of polyacrylonitrile/carbon nanotube-based carbon fibers (United States)

    Sano, Eiichi; Watanuki, Takehito; Ikebe, Masayuki; Fugetsu, Bunshi


    The addition of carbon nanotubes (CNTs) in polyacrylonitrile (PAN) precursor is an effective way to increase the electrical conductivity of derived carbon fibers. The electrical conductivity of 4.9 × 104 S/m for a PAN-based carbon fiber at room temperature increases to 9.4 × 104 S/m by adding 0.5 wt % CNTs. The measured conductivity for both PAN/CNT- and PAN-based carbon fibers monotonically increases as the temperature increases from 10 and 300 K. An attempt to explain the measured temperature dependences of electrical conductivities by various carrier transport models showed that a simple two-carrier model can give reasonable electron and hole mobility. A monopole antenna fabricated with PAN/CNT-based carbon fibers shows a gain of 2.3 dBi at 2.4 GHz, which is only 0.2 dB smaller than that of a reference (Cu-wire) monopole antenna. This result suggests the possibility of using PAN/CNT-based carbon fibers as antenna elements.

  14. Environment Parameters Control Based on Wireless Sensor Network in Livestock Buildings


    Zhang, Yu; Chen, Qiyu; Liu, Guanting; Shen, Weizheng; Wang, Guanlin


    The products quality and welfare of animals are closely related to the environment parameters in livestock buildings. A monitoring and control method of environment parameters in livestock buildings based on wireless sensor network is proposed in this paper. Temperature, humidity, light, carbon dioxide concentration, ammonia concentration, and hydrogen sulfide concentration can be monitored in real time by this method. The above six parameters will be adjusted and controlled through WLS algor...

  15. Effects of Carbonization Parameters of Moso-Bamboo-Based Porous Charcoal on Capturing Carbon Dioxide

    Directory of Open Access Journals (Sweden)

    Pei-Hsing Huang


    Full Text Available This study experimentally analyzed the carbon dioxide adsorption capacity of Moso-bamboo- (Phyllostachys edulis- based porous charcoal. The porous charcoal was prepared at various carbonization temperatures and ground into powders with 60, 100, and 170 meshes, respectively. In order to understand the adsorption characteristics of porous charcoal, its fundamental properties, namely, charcoal yield, ash content, pH value, Brunauer-Emmett-Teller (BET surface area, iodine number, pore volume, and powder size, were analyzed. The results show that when the carbonization temperature was increased, the charcoal yield decreased and the pH value increased. Moreover, the bamboo carbonized at a temperature of 1000°C for 2 h had the highest iodine sorption value and BET surface area. In the experiments, charcoal powders prepared at various carbonization temperatures were used to adsorb 1.854% CO2 for 120 h. The results show that the bamboo charcoal carbonized at 1000°C and ground with a 170 mesh had the best adsorption capacity, significantly decreasing the CO2 concentration to 0.836%. At room temperature and atmospheric pressure, the Moso-bamboo-based porous charcoal exhibited much better CO2 adsorption capacity compared to that of commercially available 350-mesh activated carbon.

  16. Effects of carbonization parameters of Moso-bamboo-based porous charcoal on capturing carbon dioxide. (United States)

    Huang, Pei-Hsing; Jhan, Jhih-Wei; Cheng, Yi-Ming; Cheng, Hau-Hsein


    This study experimentally analyzed the carbon dioxide adsorption capacity of Moso-bamboo- (Phyllostachys edulis-) based porous charcoal. The porous charcoal was prepared at various carbonization temperatures and ground into powders with 60, 100, and 170 meshes, respectively. In order to understand the adsorption characteristics of porous charcoal, its fundamental properties, namely, charcoal yield, ash content, pH value, Brunauer-Emmett-Teller (BET) surface area, iodine number, pore volume, and powder size, were analyzed. The results show that when the carbonization temperature was increased, the charcoal yield decreased and the pH value increased. Moreover, the bamboo carbonized at a temperature of 1000(°)C for 2 h had the highest iodine sorption value and BET surface area. In the experiments, charcoal powders prepared at various carbonization temperatures were used to adsorb 1.854% CO2 for 120 h. The results show that the bamboo charcoal carbonized at 1000(°)C and ground with a 170 mesh had the best adsorpt on capacity, significantly decreasing the CO2 concentration to 0.836%. At room temperature and atmospheric pressure, the Moso-bamboo-based porous charcoal exhibited much better CO2 adsorption capacity compared to that of commercially available 350-mesh activated carbon.

  17. Neural Network Based Intelligent Sootblowing System

    Energy Technology Data Exchange (ETDEWEB)

    Mark Rhode


    . Due to the composition of coal, particulate matter is also a by-product of coal combustion. Modern day utility boilers are usually fitted with electrostatic precipitators to aid in the collection of particulate matter. Although extremely efficient, these devices are sensitive to rapid changes in inlet mass concentration as well as total mass loading. Traditionally, utility boilers are equipped with devices known as sootblowers, which use, steam, water or air to dislodge and clean the surfaces within the boiler and are operated based upon established rule or operator's judgment. Poor sootblowing regimes can influence particulate mass loading to the electrostatic precipitators. The project applied a neural network intelligent sootblowing system in conjunction with state-of-the-art controls and instruments to optimize the operation of a utility boiler and systematically control boiler slagging/fouling. This optimization process targeted reduction of NOx of 30%, improved efficiency of 2% and a reduction in opacity of 5%. The neural network system proved to be a non-invasive system which can readily be adapted to virtually any utility boiler. Specific conclusions from this neural network application are listed below. These conclusions should be used in conjunction with the specific details provided in the technical discussions of this report to develop a thorough understanding of the process.

  18. Named data networking-based smart home


    Syed Hassan Ahmed; Dongkyun Kim


    Named data networking (NDN) treats content/data as a “first class citizen” of the network by giving it a “name”. This content “name” is used to retrieve any information, unlike in device-centric networks (i.e., the current Internet), which depend on physical IP addresses. Meanwhile, the smart home concept has been gaining attention in academia and industries; various low-cost embedded devices are considered that can sense, process, store, and communicate data autonomously. In this paper, we s...

  19. Visualization of Complex Networks Based on Dyadic Curvelet Transform

    Directory of Open Access Journals (Sweden)

    Kaoru Hirota


    Full Text Available A visualization method is proposed for understanding the structure of complex networks based on an extended Curvelet transform named Dyadic Curvelet Transform (DClet. The proposed visualization method comes to answer specific questions about structures of complex networks by mapping data into orthogonal localized events with a directional component via the Cartesian sampling sets of detail coefficients. It behaves in the same matter as human visual system, seeing in terms of segments and distinguishing them by scale and orientation. Compressing the network is another fact. The performance of the proposed method is evaluated by two different networks with structural properties of small world networks with N = 16 vertices, and a globally coupled network with size N = 1024 and 523 776 edges. As the most large scale real networks are not fully connected, it is tested on the telecommunication network of Iran as a real extremely complex network with 92 intercity switching vertices, 706 350 E1 traffic channels and 315 525 transmission channels. It is shown that the proposed method performs as a simulation tool for successfully design of network and establishing the necessary group sizes. It can clue the network designer in on all structural properties that network has.

  20. Effects of Carbonization Parameters of Moso-Bamboo-Based Porous Charcoal on Capturing Carbon Dioxide


    Pei-Hsing Huang; Jhih-Wei Jhan; Yi-Ming Cheng; Hau-Hsein Cheng


    This study experimentally analyzed the carbon dioxide adsorption capacity of Moso-bamboo- (Phyllostachys edulis-) based porous charcoal. The porous charcoal was prepared at various carbonization temperatures and ground into powders with 60, 100, and 170 meshes, respectively. In order to understand the adsorption characteristics of porous charcoal, its fundamental properties, namely, charcoal yield, ash content, pH value, Brunauer-Emmett-Teller (BET) surface area, iodine number, pore volume, a...

  1. A Hybrid Reliable Heuristic Mapping Method Based on Survivable Virtual Networks for Network Virtualization

    Directory of Open Access Journals (Sweden)

    Qiang Zhu


    Full Text Available The reliable mapping of virtual networks is one of the hot issues in network virtualization researches. Unlike the traditional protection mechanisms based on redundancy and recovery mechanisms, we take the solution of the survivable virtual topology routing problem for reference to ensure that the rest of the mapped virtual networks keeps connected under a single node failure condition in the substrate network, which guarantees the completeness of the virtual network and continuity of services. In order to reduce the cost of the substrate network, a hybrid reliable heuristic mapping method based on survivable virtual networks (Hybrid-RHM-SVN is proposed. In Hybrid-RHM-SVN, we formulate the reliable mapping problem as an integer linear program. Firstly, we calculate the primary-cut set of the virtual network subgraph where the failed node has been removed. Then, we use the ant colony optimization algorithm to achieve the approximate optimal mapping. The links in primary-cut set should select a substrate path that does not pass through the substrate node corresponding to the virtual node that has been removed first. The simulation results show that the acceptance rate of virtual networks, the average revenue of mapping, and the recovery rate of virtual networks are increased compared with the existing reliable mapping algorithms, respectively.

  2. Reliability based rehabilitation of water distribution networks by means of Bayesian networks

    Directory of Open Access Journals (Sweden)

    Lakehal Abdelaziz


    Full Text Available Water plays an essential role in the everyday lives of the people. To supply subscribers with good quality of water and to ensure continuity of service, the operators use water distribution networks (WDN. The main elements of water distribution network (WDN are: pipes and valves. The work developed in this paper focuses on a water distribution network rehabilitation in the short and long term. Priorities for rehabilitation actions were defined and the information system consolidated, as well as decision-making. The reliability data were conjugated in decision making tools on water distribution network rehabilitation in a forecasting context. As the pipes are static elements and the valves are dynamic elements, a Bayesian network (static-dynamic has been developed, which can help to predict the failure scenario regarding water distribution. A relationship between reliability and prioritization of rehabilitation actions has been investigated. Modelling based on a Static Bayesian Network (SBN is implemented to analyse qualitatively and quantitatively the availability of water in the different segments of the network. Dynamic Bayesian networks (DBN are then used to assess the valves reliability as function of time, which allows management of water distribution based on water availability assessment in different segments. Before finishing the paper by giving some conclusions, a case study of a network supplying a city was presented. The results show the importance and effectiveness of the proposed Bayesian approach in the anticipatory management and for prioritizing rehabilitation of water distribution networks.

  3. Mining human mobility in location-based social networks

    CERN Document Server

    Gao, Huiji


    In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook Places, which have attracted an increasing number of users and greatly enriched their urban experience. Typical location-based social networking sites allow a user to ""check in"" at a real-world POI (point of interest, e.g., a hotel, restaurant, theater, etc.), leave tips toward the POI, and share the check-in with their online friends. The check-in action bridges the gap between real world and online social networks, resulting in a new type of social networks, namely l

  4. Epoxy based photoresist/carbon nanoparticle composites

    DEFF Research Database (Denmark)

    Lillemose, Michael; Gammelgaard, Lauge; Richter, Jacob


    We have fabricated composites of SU-8 polymer and three different types of carbon nanoparticles (NPs) using ultrasonic mixing. Structures of composite thin films have been patterned on a characterization chip with standard UV photolithography. Using a four-point bending probe, a well defined stress...... is applied to the composite thin film and we have demonstrated that the composites are piezoresistive. Stable gauge factors of 5-9 have been measured, but we have also observed piezoresistive responses with gauge factors as high as 50. As SU-8 is much softer than silicon and the gauge factor of the composite...

  5. Cointegration-based financial networks study in Chinese stock market (United States)

    Tu, Chengyi


    We propose a method based on cointegration instead of correlation to construct financial complex network in Chinese stock market. The network is obtained starting from the matrix of p-value calculated by Engle-Granger cointegration test between all pairs of stocks. Then some tools for filtering information in complex network are implemented to prune the complete graph described by the above matrix, such as setting a level of statistical significance as a threshold and Planar Maximally Filtered Graph. We also calculate Partial Correlation Planar Graph of these stocks to compare the above networks. Last, we analyze these directed, weighted and non-symmetric networks by using standard methods of network analysis, including degree centrality, PageRank, HITS, local clustering coefficient, K-shell and strongly and weakly connected components. The results shed a new light on the underlying mechanisms and driving forces in a financial market and deepen our understanding of financial complex network.

  6. Multiagent Based Information Dissemination in Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    S.S. Manvi


    Full Text Available Vehicular Ad hoc Networks (VANETs are a compelling application of ad hoc networks, because of the potential to access specific context information (e.g. traffic conditions, service updates, route planning and deliver multimedia services (Voice over IP, in-car entertainment, instant messaging, etc.. This paper proposes an agent based information dissemination model for VANETs. A two-tier agent architecture is employed comprising of the following: 1 'lightweight', network-facing, mobile agents; 2 'heavyweight', application-facing, norm-aware agents. The limitations of VANETs lead us to consider a hybrid wireless network architecture that includes Wireless LAN/Cellular and ad hoc networking for analyzing the proposed model. The proposed model provides flexibility, adaptability and maintainability for traffic information dissemination in VANETs as well as supports robust and agile network management. The proposed model has been simulated in various network scenarios to evaluate the effectiveness of the approach.

  7. Selective detection of SO2 at room temperature based on organoplatinum functionalized single-walled carbon nanotube field effect transistors

    NARCIS (Netherlands)

    Cid, C.C.; Jimenez-Cadena, G.; Riu, J.; Maroto, A.; Rius, F.X.; Batema, G.D.; van Koten, G.


    We report a field effect transistor (FET) based on a network of single-walled carbon nanotubes (SWCNTs) that for the first time can selectively detect a single gaseous molecule in air by chemically functionalizing the SWCNTs with a selective molecular receptor. As a target model we used SO2. The

  8. Carbon nanoparticle-based fluorescent bioimaging probes

    National Research Council Canada - National Science Library

    Bhunia, Susanta Kumar; Saha, Arindam; Maity, Amit Ranjan; Ray, Sekhar C; Jana, Nikhil R


    Fluorescent nanoparticle-based imaging probes have advanced current labelling technology and are expected to generate new medical diagnostic tools based on their superior brightness and photostability...

  9. Modeling forest ecosystem responses to elevated carbon dioxide and ozone using artificial neural networks. (United States)

    Larsen, Peter E; Cseke, Leland J; Miller, R Michael; Collart, Frank R


    Rising atmospheric levels of carbon dioxide and ozone will impact productivity and carbon sequestration in forest ecosystems. The scale of this process and the potential economic consequences provide an incentive for the development of models to predict the types and rates of ecosystem responses and feedbacks that result from and influence of climate change. In this paper, we use phenotypic and molecular data derived from the Aspen Free Air CO2 Enrichment site (Aspen-FACE) to evaluate modeling approaches for ecosystem responses to changing conditions. At FACE, it was observed that different aspen clones exhibit clone-specific responses to elevated atmospheric levels of carbon dioxide and ozone. To identify the molecular basis for these observations, we used artificial neural networks (ANN) to examine above and below-ground community phenotype responses to elevated carbon dioxide, elevated ozone and gene expression profiles. The aspen community models generated using this approach identified specific genes and subnetworks of genes associated with variable sensitivities for aspen clones. The ANN model also predicts specific co-regulated gene clusters associated with differential sensitivity to elevated carbon dioxide and ozone in aspen species. The results suggest ANN is an effective approach to predict relevant gene expression changes resulting from environmental perturbation and provides useful information for the rational design of future biological experiments. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method. (United States)

    Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui


    Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli, and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

  11. Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon (United States)

    Nelson, Ross


    ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.

  12. Dynamical complexity in the perception-based network formation model (United States)

    Jo, Hang-Hyun; Moon, Eunyoung


    Many link formation mechanisms for the evolution of social networks have been successful to reproduce various empirical findings in social networks. However, they have largely ignored the fact that individuals make decisions on whether to create links to other individuals based on cost and benefit of linking, and the fact that individuals may use perception of the network in their decision making. In this paper, we study the evolution of social networks in terms of perception-based strategic link formation. Here each individual has her own perception of the actual network, and uses it to decide whether to create a link to another individual. An individual with the least perception accuracy can benefit from updating her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. As for initial actual networks, we consider both homogeneous and heterogeneous cases. The homogeneous initial actual network is modeled by Erdős-Rényi (ER) random networks, while we take a star network for the heterogeneous case. In any cases, individual perceptions of the actual network are modeled by ER random networks with controllable linking probability. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. As the number of jumps is the consequence of the dynamical complexity, we discuss the effect of initial conditions on the number of jumps to find that the dynamical complexity strongly depends on how much individuals initially overestimate or underestimate the link density of the actual network. For the heterogeneous case, the role of the highly connected individual as an information spreader is also discussed.

  13. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...... patches are localized, ABSN designs a completely distributed, hybrid discovery protocol which is proactive in a neighbourhood zone and reactive outside, tailored so that any query among the sensors of one activity is routed through the network with minimum overhead, guided by the bounds of that activity...

  14. Topic-based Social Influence Measurement for Social Networks

    Directory of Open Access Journals (Sweden)

    Asso Hamzehei


    Full Text Available Social science studies have acknowledged that the social influence of individuals is not identical. Social networks structure and shared text can reveal immense information about users, their interests, and topic-based influence. Although some studies have considered measuring user influence, less has been on measuring and estimating topic-based user influence. In this paper, we propose an approach that incorporates network structure, user-generated content for topic-based influence measurement, and user’s interactions in the network. We perform experimental analysis on Twitter data and show that our proposed approach can effectively measure topic-based user influence.

  15. Recent developments in capillary EKC based on carbon nanoparticles. (United States)

    Moliner-Martínez, Yolanda; Cárdenas, Soledad; Simonet, Bartolome M; Valcárcel, Miguel


    This paper provides an overview of the use of carbon nanoparticles (CNPs) as pseudo-stationary phases (PSPs) in EKC. Specifically, it describes the characteristics and properties of the major types of CNPs used as PSPs in EKC separations, namely C(60) fullerenes, carbon nanotubes and covalently modified carbon nanotubes. Based on such properties, a plausible mechanism for the interactions governing EKC separation with these materials is proposed. Also, the most salient uses of CNPs as PSPs are outlined. Finally, CNPs are compared in terms of performance with other well-established types of nanostructures used to enhance selectivity in EKC over the past decade.

  16. Resistance-based biosensor of Multi-Walled Carbon Nanotubes. (United States)

    Kolosovas-Machuca, E S; Vera-Reveles, G; Rodríguez-Aranda, M C; Ortiz-Dosal, L C; Segura-Cardenas, Emmanuel; Gonzalez, Francisco J


    Multi-Walled Carbon Nanotubes (MWNTs) are a good choice for resistive biosensors due to their great resistance changes when immunoreactions take place, they are also low-cost, more biocompatible than single-walled carbon nanotubes, and resistive measurement equipment is usually not expensive and readily available. In this work a novel resistive biosensor based on the immobilization of an antigen through a silanization process over the surface of Multi-Walled Carbon Nanotubes (MWNTs) is reported. Results show that the biosensor increases its conductivity when adding the antigen and decreases when adding the antibody making them good candidates for disease diagnosis.

  17. A Neural Network-Based Interval Pattern Matcher

    Directory of Open Access Journals (Sweden)

    Jing Lu


    Full Text Available One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches 100% and that is promising.

  18. Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring (United States)


    conventional WSN . VSN enabled closed loop system consumes more energy than the VSN only system, because of the commands that are send to the nodes. Energy ...predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless Sensor Network ( WSN ) to...Network ( WSN ) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based monitoring

  19. Long-term stability of superhydrophilic oxygen plasma-modified single-walled carbon nanotube network surfaces and the influence on ammonia gas detection

    Energy Technology Data Exchange (ETDEWEB)

    Min, Sungjoon [Department of Biomicrosystem Technology, Korea University, Seoul 136-713 (Korea, Republic of); Kim, Joonhyub [Department of Control and Instrumentation Engineering, Korea University, 2511 Sejong-ro, Sejong City 339-770 (Korea, Republic of); Park, Chanwon [Department of Electrical and Electronic Engineering, Kangwon National University, Chuncheon 200-701 (Korea, Republic of); Jin, Joon-Hyung, E-mail: [Department of Chemical Engineering, Kyonggi University, 154-42 Gwanggyosan-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do 16227 (Korea, Republic of); Min, Nam Ki, E-mail: [Department of Biomicrosystem Technology, Korea University, Seoul 136-713 (Korea, Republic of)


    Graphical abstract: Superhydrophilic single-walled carbon nanotube obtained by O{sub 2} plasma treatment voluntarily and non-reversibly reverts to a metastable state. This aerobic aging is an essential process to develop a stable carbon nanotube-based sensor. - Highlights: • Superhydrophilic single-walled carbon nanotube network can be obtained by O{sub 2} plasma-based surface modification. • The modified carbon nanotube surface invariably reverts to a metastable state in a non-reversible manner. • Aerobic aging is essential to stabilize the modified carbon nanotube and the carbon nanotube-based sensing device due to minimized sensor-to-sensor variation. - Abstract: Single-walled carbon nanotube (SWCNT) networks are subjected to a low-powered oxygen plasma for the surface modification. Changes in the surface chemical composition and the stability of the plasma-treated SWCNT (p-SWCNT) with aging in air for up to five weeks are studied using X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The contact angle decreases from 120° of the untreated hydrophobic SWCNT to 0° for the superhydrophilic p-SWCNT. Similarly, the ratio of oxygen to carbon (O:C) based on the XPS spectra increases from 0.25 to 1.19, indicating an increase in surface energy of the p-SWCNT. The enhanced surface energy is gradually dissipated and the p-SWCNT network loses the superhydrophilic surface property. However, it never revert to the original hydrophobic surface state but to a metastable hydrophilic state. The aging effect on sensitivity of the p-SWCNT network-based ammonia sensor is investigated to show the importance of the aging process for the stabilization of the p-SWCNT. The best sensitivity for monitoring NH{sub 3} gas is observed with the as-prepared p-SWCNT, and the sensitivity decreases as similar as the p-SWCNT loses its hydrophilicity with time goes by. After a large performance degradation during the aging time for about two weeks, the response

  20. A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

    Directory of Open Access Journals (Sweden)

    Raúl Eusebio-Grande


    Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

  1. Representations in neural network based empirical potentials (United States)

    Cubuk, Ekin D.; Malone, Brad D.; Onat, Berk; Waterland, Amos; Kaxiras, Efthimios


    Many structural and mechanical properties of crystals, glasses, and biological macromolecules can be modeled from the local interactions between atoms. These interactions ultimately derive from the quantum nature of electrons, which can be prohibitively expensive to simulate. Machine learning has the potential to revolutionize materials modeling due to its ability to efficiently approximate complex functions. For example, neural networks can be trained to reproduce results of density functional theory calculations at a much lower cost. However, how neural networks reach their predictions is not well understood, which has led to them being used as a "black box" tool. This lack of understanding is not desirable especially for applications of neural networks in scientific inquiry. We argue that machine learning models trained on physical systems can be used as more than just approximations since they had to "learn" physical concepts in order to reproduce the labels they were trained on. We use dimensionality reduction techniques to study in detail the representation of silicon atoms at different stages in a neural network, which provides insight into how a neural network learns to model atomic interactions.


    Directory of Open Access Journals (Sweden)



    Full Text Available In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack detected by dynamic neural network. The results indicate that dynamic neural nets (Distributed Time-Delay Artificial Neural Network can achieve a high detection rate, where the overall accuracy classification rate average is equal to 97.24%.



    Michael Chien-Wei Chen


    Lignin is a rich renewable source of aromatic compounds. As a potentialpetroleum feedstock replacement, lignin can reduce environmental impacts such ascarbon emission. Due to its complex chemical structure, lignin is currently underutilized.Exploiting lignin as a precursor for carbon fibre adds high economic value to lignin andencourages further development in lignin extraction technology. This report includes apreliminary cost analysis and identifies the key aspects of lignin-based carbon fi...

  4. Humidity Sensitivity of Multi-Walled Carbon Nanotube Networks Deposited by Dielectrophoresis

    Directory of Open Access Journals (Sweden)

    Tianhong Cui


    Full Text Available This paper presents an investigation on the humidity sensitivity of deposited multi-walled carbon nanotube (MWCNT networks using ac dielectrophoresis (DEP between interdigitated electrodes (IDEs. MWCNTs dispersed in ethanol were trapped and enriched between IDEs on a Si/SiO2 substrate under a positive DEP force. After the DEP process, the ethanol was evaporated and the MWCNT network on a substrate with IDEs was put into a furnace for repeated thermal annealing. It was found that the resistance stability of the network was effectively improved through thermal annealing. The humidity sensitivity was obtained by measuring the resistance of the MWCNT network with different relative humidity at room temperature. The experimental results show the resistance increases linearly with increasing the relative humidity from 25% to 95% RH with a sensitivity of 0.5%/%RH. The MWCNT networks have a reversible humidity sensing capacity with response time and recovery time of about 3 s and 25 s, respectively. The resistance is dependent on temperature with a negative coefficient of about -0.33%/K in a temperature range from 293 K to 393 K.

  5. Structure and properties of triolein-based polyurethane networks. (United States)

    Zlatanić, Alisa; Petrović, Zoran S; Dusek, Karel


    Polyurethane networks based on vegetable oils have very heterogeneous composition, and it is difficult to find a close correlation between their structure and properties. To establish benchmark structure-properties relationships, we have prepared model polyurethane networks based on triolein and 4,4'-diphenylmethane diisocyanate (MDI). Cross-linking in the middle of fatty acid chains leaves significant parts of the triglyceride as dangling chains. To examine their effect on properties, we have synthesized another polyurethane network using triolein without dangling chains (removed by metathesis). The structure of polyols was studied in detail since it affects the structure of polyurethane networks. The network structure was analyzed from swelling and mechanical measurements and by applying network and rubber elasticity theories. The cross-linking density in both networks was found to be close to theoretical. The triolein-based model network displayed modulus (around 6 MPa), tensile strength (8.7 MPa), and elongation at break (136%), characteristic of hard rubbers. Glass transition temperatures of the networks from triolein and its metathesis analogue were 25 and 31.5 degrees C, respectively.

  6. Carbon-Based Compounds and Exobiology (United States)

    Kerridge, John; DesMarais, David; Khanna, R. K.; Mancinelli, Rocco; McDonald, Gene; diBrozollo, Fillipo Radicati; Wdowiak, Tom


    The Committee for Planetary and Lunar Explorations (COMPLEX) posed questions related to exobiological exploration of Mars and the possibility of a population of carbonaceous materials in cometary nuclei to be addressed by future space missions. The scientific objectives for such missions are translated into a series of measurements and/or observations to be performed by Martian landers. These are: (1) A detailed mineralogical, chemical, and textural assessment of rock diversity at a landing site; (2) Chemical characterization of the materials at a local site; (3) Abundance of Hydrogen at any accessible sites; (4) Identification of specific minerals that would be diagnostic of aqueous processes; (5) Textual examination of lithologies thought to be formed by aqueous activity; (6) Search for minerals that might have been produced as a result of biological processes; (7) Mapping the distribution, in three dimensions, of the oxidant(s) identified on the Martian surface by the Viking mission; (8) Definition of the local chemical environment; (9) Determination of stable-isotopic ratios for the biogenic elements in surface mineral deposits; (10) Quantitative analysis of organic (non-carbonate) carbon; (11) Elemental and isotopic composition of bulk organic material; (12) Search for specific organic compounds that would yield information about synthetic mechanisms, in the case of prebiotic evolution, and about possible bio-markers, in the case of extinct or extant life; (13) and Coring, sampling, and detection of entrained gases and cosmic-ray induced reaction products at the polar ice cap. A discussion of measurements and/or observations required for cometary landers is included as well.

  7. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud


    Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

  8. Named data networking-based smart home

    Directory of Open Access Journals (Sweden)

    Syed Hassan Ahmed


    Full Text Available Named data networking (NDN treats content/data as a “first class citizen” of the network by giving it a “name”. This content “name” is used to retrieve any information, unlike in device-centric networks (i.e., the current Internet, which depend on physical IP addresses. Meanwhile, the smart home concept has been gaining attention in academia and industries; various low-cost embedded devices are considered that can sense, process, store, and communicate data autonomously. In this paper, we study NDN in the context of smart-home communications, discuss the preliminary evaluations, and describe the future challenges of applying NDN in smart-home applications.

  9. Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Ameli


    Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.

  10. Red Fluorescent Carbon Nanoparticle-Based Cell Imaging Probe. (United States)

    Ali, Haydar; Bhunia, Susanta Kumar; Dalal, Chumki; Jana, Nikhil R


    Fluorescent carbon nanoparticle-based probes with tunable visible emission are biocompatible, environment friendly and most suitable for various biomedical applications. However, synthesis of red fluorescent carbon nanoparticles and their transformation into functional nanoparticles are very challenging. Here we report red fluorescent carbon nanoparticle-based nanobioconjugates of application as fluorescent cell labels. Hydrophobic carbon nanoparticles are synthesized via high temperature colloid-chemical approach and transformed into water-soluble functional nanoparticles via coating with amphiphilic polymer followed by covalent linking with desired biomolecules. Following this approach, carbon nanoparticles are functionalized with polyethylene glycol, primary amine, glucose, arginine, histidine, biotin and folic acid. These functional nanoparticles can be excited with blue/green light (i.e., 400-550 nm) to capture their emission spanning from 550 to 750 nm. Arginine and folic acid functionalized nanoparticles have been demonstrated as fluorescent cell labels where blue and green excitation has been used for imaging of labeled cells. The presented method can be extended for the development of carbon nanoparticle-based other bioimaging probes.

  11. Recent advances in carbon based nanosystems for cancer theranostics. (United States)

    Augustine, Shine; Singh, Jay; Srivastava, Manish; Sharma, Monica; Das, Asmita; Malhotra, Bansi D


    One of the major challenges in our contemporary society is to facilitate healthy life for all human beings. In this context, cancer has become one of the most deadly diseases around the world, and despite many advances in theranostics techniques the treatment of cancer still remains an important problem. With recent advances made in the field of nano-biotechnology, carbon-based nanostructured materials have drawn special attention because of their unique physicochemical properties, giving rise to great potential for the diagnosis and therapy of cancer. This review deals with four different types of carbon allotrope including carbon nanotubes, graphene, fullerenes and nanodiamonds and summarizes the results of recent studies that are likely to have implications in cancer theranostics. We discuss the applications of these carbon allotropes for cancer imaging and drug delivery, hyperthermia, photodynamic therapy and acoustic wave assisted theranostics. We focus on the results of different studies conducted on functionalized/conjugated carbon nanotubes, graphene, fullerenes and nanodiamond based nanostructured materials reported in the literature in the current decade. The emphasis has been placed on the synthesis strategies, structural design, properties and possible mechanisms that are perhaps responsible for their improved theranostic characteristics. Finally, we discuss the critical issues that may accelerate the development of carbon-based nanostructured materials for application in cancer theranostics.

  12. Evaluating the mechanical properties of E-Glass fiber/carbon fiber reinforced interpenetrating polymer networks

    Directory of Open Access Journals (Sweden)

    G. Suresh


    Full Text Available A series of vinyl ester and polyurethane interpenetrating polymer networks were prepared by changing the component ratios of VER (Vinyl ester and PU (Polyurethane and the polymerization process was confirmed with Fourier Transform infrared spectroscopy. IPN (Inter Penetrating Polymer Network - VER/PU reinforced Glass and carbon fiber composite laminates were made using the Hand lay up technique. The Mechanical properties of the E-glass and carbon fiber specimens were compared from tests including Tensile, Compressive, Flexural, ILSS (Inter Laminar Shear Strength, Impact & Head Deflection Test (HDT. The IPN Reinforced Carbon fiber specimen showed better results in all the tests than E-Glass fibre reinforced IPN laminate with same thickness of the specimen, according to ASTM standards. It was found that the combination of 60%VER and 40%PU IPN exhibits better impact strength and maximum elongation at break, but at the slight expense of mechanical properties such as tensile, compressive, flexural, ILSS properties. The morphology of the unreinforced and reinforced composites was analyzed with help of scanning electron microscopy.

  13. Image Restoration Technology Based on Discrete Neural network

    Directory of Open Access Journals (Sweden)

    Zhou Duoying


    Full Text Available With the development of computer science and technology, the development of artificial intelligence advances rapidly in the field of image restoration. Based on the MATLAB platform, this paper constructs a kind of image restoration technology of artificial intelligence based on the discrete neural network and feedforward network, and carries out simulation and contrast of the restoration process by the use of the bionic algorithm. Through the application of simulation restoration technology, this paper verifies that the discrete neural network has a good convergence and identification capability in the image restoration technology with a better effect than that of the feedforward network. The restoration technology based on the discrete neural network can provide a reliable mathematical model for this field.

  14. DNA sequence analysis using hierarchical ART-based classification networks

    Energy Technology Data Exchange (ETDEWEB)

    LeBlanc, C.; Hruska, S.I. [Florida State Univ., Tallahassee, FL (United States); Katholi, C.R.; Unnasch, T.R. [Univ. of Alabama, Birmingham, AL (United States)


    Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in real-time, and require no retraining to classify novel sequences. We have adapted ART networks to provide support to scientists attempting to categorize tandem repeat DNA fragments from Onchocerca volvulus. In this approach, sequences of DNA fragments are presented to multiple ART-based networks which are linked together into two (or more) tiers; the first provides coarse sequence classification while the sub- sequent tiers refine the classifications as needed. The overall rating of the resulting classification of fragments is measured using statistical techniques based on those introduced to validate results from traditional phylogenetic analysis. Tests of the Hierarchical ART-based Classification Network, or HABclass network, indicate its value as a fast, easy-to-use classification tool which adapts to new data without retraining on previously classified data.

  15. Friend suggestion in social network based on user log (United States)

    Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.


    Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

  16. Effective information spreading based on local information in correlated networks

    CERN Document Server

    Gao, Lei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng


    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks, which will benefit the promotion of technical innovations, healthy behaviors, new products, etc. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and moderate correlation coefficients result in most efficient info...

  17. Learning from a carbon dioxide capture system dataset: Application of the piecewise neural network algorithm

    Directory of Open Access Journals (Sweden)

    Veronica Chan


    Full Text Available This paper presents the application of a neural network rule extraction algorithm, called the piece-wise linear artificial neural network or PWL-ANN algorithm, on a carbon capture process system dataset. The objective of the application is to enhance understanding of the intricate relationships among the key process parameters. The algorithm extracts rules in the form of multiple linear regression equations by approximating the sigmoid activation functions of the hidden neurons in an artificial neural network (ANN. The PWL-ANN algorithm overcomes the weaknesses of the statistical regression approach, in which accuracies of the generated predictive models are often not satisfactory, and the opaqueness of the ANN models. The results show that the generated PWL-ANN models have accuracies that are as high as the originally trained ANN models of the four datasets of the carbon capture process system. An analysis of the extracted rules and the magnitude of the coefficients in the equations revealed that the three most significant parameters of the CO2 production rate are the steam flow rate through reboiler, reboiler pressure, and the CO2 concentration in the flue gas.

  18. Highly sensitive integrated pressure sensor with horizontally oriented carbon nanotube network. (United States)

    Mohammad Haniff, Muhammad Aniq Shazni; Lee, Hing Wah; Bien, Daniel Chia Sheng; Teh, Aun Shih; Azid, Ishak Abdul


    This paper presents a functionalized, horizontally oriented carbon nanotube network as a sensing element to enhance the sensitivity of a pressure sensor. The synthesis of horizontally oriented nanotubes from the AuFe catalyst and their deposition onto a mechanically flexible substrate via transfer printing are studied. Nanotube formation on thermally oxidized Si (100) substrates via plasma-enhanced chemical vapor deposition controls the nanotube coverage and orientation on the flexible substrate. These nanotubes can be simply transferred to the flexible substrate without changing their physical structure. When tested under a pressure range of 0 to 50 kPa, the performance of the fabricated pressure sensor reaches as high as approximately 1.68%/kPa, which indicates high sensitivity to a small change of pressure. Such sensitivity may be induced by the slight contact in isolated nanotubes. This nanotube formation, in turn, enhances the modification of the contact and tunneling distance of the nanotubes upon the deformation of the network. Therefore, the horizontally oriented carbon nanotube network has great potential as a sensing element for future transparent sensors.

  19. Neural Network-Based Segmentation of Textures Using Gabor Features


    Ramakrishnan, AG; Raja, Kumar S; Ram, Ragu HV


    The effectiveness of Gabor filters for texture segmentation is well known. In this paper, we propose a texture identification scheme, based on a neural network (NN) using Gabor features. The features are derived from both the Gabor cosine and sine filters. Through experiments, we demonstrate the effectiveness of a NN based classifier using Gabor features for identifying textures in a controlled environment. The neural network used for texture identification is based on the multilayer perceptr...

  20. Relative Contributions of Fossil and Contemporary Carbon sources to PM 2.5 Aerosols at Nine IMPROVE Network Sites

    Energy Technology Data Exchange (ETDEWEB)

    Bench, G; Fallon, S; Schichtel, B; Malm, W; McDade, C


    Particulate matter aerosols contribute to haze diminishing vistas and scenery at National Parks and Wilderness Areas within the United States. To increase understanding of the sources of carbonaceous aerosols at these settings, the total carbon loading and {sup 14}C/C ratio of PM 2.5 aerosols at nine IMPROVE (Interagency Monitoring for Protection Of Visual Environments) network sites were measured. Aerosols were collected weekly in the summer and winter at one rural site, two urban sites, five sites located in National Parks and one site located in a Wildlife Preserve. The carbon measurements together with the absence of {sup 14}C in fossil carbon materials and the known {sup 14}C/C levels in contemporary carbon materials were used to derive contemporary and fossil carbon contents of the particulate matter. Contemporary and fossil carbon aerosol loadings varied across the sites and suggest different percentages of carbon source inputs. The urban sites had the highest fossil carbon loadings that comprised around 50% of the total carbon aerosol loading. The Wildlife Preserve and National Park sites together with the rural site had much lower fossil carbon loading components. At these sites, variations in the total carbon aerosol loading were dominated by non-fossil carbon sources. This suggests that reduction of anthroprogenic sources of fossil carbon aerosols may result in little decrease in carbonaceous aerosol loading at many National Parks and rural areas.

  1. Identifying key nodes in multilayer networks based on tensor decomposition (United States)

    Wang, Dingjie; Wang, Haitao; Zou, Xiufen


    The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.

  2. Connected Dominating Set Based Topology Control in Wireless Sensor Networks (United States)

    He, Jing


    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  3. The harmonics detection method based on neural network applied ...

    African Journals Online (AJOL)


    Consequently, many structures based on artificial neural network (ANN) have been developed in the literature, The most significant ... Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total Harmonic Distortion. 1. ..... and pure shunt active fitters, IEEE 38th Conf on Industry Applications, Vol. 2, pp.

  4. Distributed network generation based on preferential attachment in ABS

    NARCIS (Netherlands)

    K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank)


    textabstractGeneration of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the

  5. All carbon coaxial supercapacitors based on hollow carbon nanotube sleeve structure (United States)

    Zang, Xiaobei; Xu, Ruiqiao; Zhang, Yangyang; Li, Xinming; Zhang, Li; Wei, Jinquan; Wang, Kunlin; Zhu, Hongwei


    All carbon coaxial supercapacitors based on hollow carbon nanotube (CNT) sleeve structure are assembled and tested. The key advantage of the structure is that the inner core electrode is variable from CNT sleeve sponges, to CNT fibers, reduced graphene oxide fibers, and graphene woven fabrics. By changing core electrodes from sleeve sponges to CNT fibers, the electrochemical performance has been significantly enhanced. The capacitance based on sleeve sponge + CNT fiber double the capacitances of double-sleeve sponge supercapacitors thanks to reduction of the series and internal resistances. Besides, the coaxial sleeve structure possesses many other features, including high rate capacitance, long cycle life, and good flexibility.

  6. Optical-Correlator Neural Network Based On Neocognitron (United States)

    Chao, Tien-Hsin; Stoner, William W.


    Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

  7. Two port network analysis for three impedance based oscillators

    KAUST Repository

    Said, Lobna A.


    Two-port network representations are applied to analyze complex networks which can be dissolved into sub-networks connected in series, parallel or cascade. In this paper, the concept of two-port network has been studied for oscillators. Three impedance oscillator based on two port concept has been analyzed using different impedance structures. The effect of each structure on the oscillation condition and the frequency of oscillation have been introduced. Two different implementations using MOS and BJT have been introduced. © 2011 IEEE.

  8. Material procedure quality forecast based on genetic BP neural network (United States)

    Zheng, Bao-Hua


    Material procedure quality forecast plays an important role in quality control. This paper proposes a prediction model based on genetic algorithm (GA) and back propagation (BP) neural network. It can obtain the initial weights and thresholds of optimized BP neural network with the GA global search ability. A material process quality prediction model with the optimized BP neural network is adopted to predict the error of future process to measure the accuracy of process quality. The results show that the proposed method has the advantages of high accuracy and fast convergence rate compared with BP neural network.

  9. Epidemic spreading on networks based on stress response (United States)

    Nian, Fuzhong; Yao, Shuanglong


    Based on the stress responses of individuals, the susceptible-infected-susceptible epidemic model was improved on the small-world networks and BA scale-free networks and the simulations were implemented and analyzed. Results indicate that the behaviors of individual’s stress responses could induce the epidemic spreading resistance and adaptation at the network level. This phenomenon showed that networks were learning how to adapt to the disease and the evolution process could improve their immunization to future infectious diseases and would effectively prevent the spreading of infectious diseases.

  10. An image segmentation method based on network clustering model (United States)

    Jiao, Yang; Wu, Jianshe; Jiao, Licheng


    Network clustering phenomena are ubiquitous in nature and human society. In this paper, a method involving a network clustering model is proposed for mass segmentation in mammograms. First, the watershed transform is used to divide an image into regions, and features of the image are computed. Then a graph is constructed from the obtained regions and features. The network clustering model is applied to realize clustering of nodes in the graph. Compared with two classic methods, the algorithm based on the network clustering model performs more effectively in experiments.

  11. In Situ Carbon Dioxide and Methane Measurements from a Tower Network in Los Angeles (United States)

    Verhulst, K. R.; Karion, A.; Kim, J.; Sloop, C.; Salameh, P.; Yadav, V.; Mueller, K.; Pongetti, T.; Newman, S.; Wong, C.; Hopkins, F. M.; Rao, P.; Miller, J. B.; Keeling, R. F.; Weiss, R. F.; Miller, C. E.; Duren, R. M.; Andrews, A. E.


    Urbanization has concentrated a significant fraction of the world's anthropogenic greenhouse gas (GHG) emissions into a relatively small fraction of the earth's land surface. Concern about rising GHG levels has motivated many nations to begin regulating and/or mitigating emissions, motivating the need for robust, consistent, traceable GHG observation methods in complex urban domains. The Los Angeles Megacity Carbon Project involves continuous and flask sampling of GHGs, trace gases, and isotopes at surface sites situated throughout the greater Los Angeles (LA) area. There are three signals of interest for utilizing urban GHG measurements in local or regional inverse modeling studies: (1) changes in the measured mole fraction at one location within a 24-hour period, (2) gradients in the measured mole fraction between locations within the surface measurement network, (3) local enhancements, or the difference between a measurement at one location and an inferred local "background" mole fraction. We report CO2 and CH4 measurements collected from eleven wavelength-scanned cavity ring-down analyzers (Picarro, Inc.). All sites use an internally consistent sampling protocol and calibration strategy. We show that the LA observation sites exhibit significant GHG enhancements relative to background, with evidence of systematic diurnal, weekly, and monthly variability. In Los Angeles, the "ideal" background sampling location could vary substantially depending on the time of year and local meteorology. Use of a single site for background determination may not be sufficient for reliable determination of GHG enhancements. We estimate the total uncertainty in the enhancement and examine how the choice of background influences the GHG enhancement signal. Uncertainty in GHG enhancements will ultimately translate into uncertainty in the fluxes derived from inverse modeling studies. In future work, the LA surface observations will be incorporated into an inverse-modeling framework to

  12. TRICALCAR : Weaving Community Based Wireless Networks in ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    This grant will support a capacity-building and applied research project on community wireless networking in Latin America and the Caribbean (LAC). Researchers will review, update and adapt 18 existing online thematic modules, and design seven new ones. A group of wireless experts with expertise in the social impacts ...

  13. Based on BP Neural Network Stock Prediction (United States)

    Liu, Xiangwei; Ma, Xin


    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

  14. Social networking for web-based communities

    NARCIS (Netherlands)

    Issa, T.; Kommers, Petrus A.M.


    In the 21st century, a new technology was introduced to facilitate communication, collaboration, and interaction between individuals and businesses. This technology is called social networking; this technology is now part of Internet commodities like email, browsing and blogging. From the 20th

  15. Simultaneous characterization of elemental segregation and cementite networks in high carbon steel products by spatially-resolved laser-induced breakdown spectroscopy (United States)

    Boué-Bigne, Fabienne


    The reliable characterization of the level of elemental segregation and of the extent of grain-boundary cementite networks in high carbon steel products is a prerequisite for checking product quality, for the purpose of product release to customers, and to investigate the presence of defects that may have led to mechanical property failure of the product. Current methods for the characterization of segregation and cementite networks rely on two different methods of sample etching followed by visual observation, where quality scores are given based on human perception and judgment. With the continuous demand on increasing quality, some of the conventional characterization methods and their associated scoring boards have lost relevance for the precision of characterization that is required today to distinguish between a product that will perform well and one that will not. In order to move away from a qualitative, human perception based situation for the scoring of the severity of segregation and cementite networks, a new method of data evaluation based on spatially-resolved LIBS measurements was developed to provide quantitative and simultaneous characterization of both types of defects. The quantitative assessment of segregation and cementite networks is based on the acquisition of carbon concentration maps. The ability to produce rapid scanning measurements of micro and macro-scale features with adequate spatial resolution makes LIBS the measurement method of preference for this purpose. The characterization of both different defects is extracted simultaneously and from the same carbon concentration map following a series of statistical treatment and data extraction rules. LIBS results were validated against recognized methods and were applied to a significant number of routine samples. The new LIBS method offers a step change improvement in reliability for the characterization of segregation and cementite networks in steel products over the conventional methods

  16. Hybrid network defense model based on fuzzy evaluation. (United States)

    Cho, Ying-Chiang; Pan, Jen-Yi


    With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.

  17. Physical parameters collection based on wireless senor network (United States)

    Chen, Xin; Wu, Hong; Ji, Lei


    With the development of sensor technology, wireless senor network has been applied in the medical, military, entertainment field and our daily life. But the existing available wireless senor networks applied in human monitoring system still have some problems, such as big power consumption, low security and so on. To improve senor network applied in health monitoring system, the paper introduces a star wireless senor networks based on msp430 and DSP. We design a low-cost heart-rate monitor senor node. The communication between senor node and sink node is realized according to the newest protocol proposed by the IEEE 802.15.6 Task Group. This wireless senor network will be more energy-efficient and faster compared to traditional senor networks.

  18. Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Mohammed Alkhawlani


    Full Text Available In the next generation of heterogeneous wireless networks (HWNs, a large number of different radio access technologies (RATs will be integrated into a common network. In this type of networks, selecting the most optimal and promising access network (AN is an important consideration for overall networks stability, resource utilization, user satisfaction, and quality of service (QoS provisioning. This paper proposes a general scheme to solve the access network selection (ANS problem in the HWN. The proposed scheme has been used to present and design a general multicriteria software assistant (SA that can consider the user, operator, and/or the QoS view points. Combined fuzzy logic (FL and genetic algorithms (GAs have been used to give the proposed scheme the required scalability, flexibility, and simplicity. The simulation results show that the proposed scheme and SA have better and more robust performance over the random-based selection.

  19. Rumor Diffusion in an Interests-Based Dynamic Social Network

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang


    Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

  20. Carbon Dot Based Sensing of Dopamine and Ascorbic Acid

    Directory of Open Access Journals (Sweden)

    Upama Baruah


    Full Text Available We demonstrate carbon dot based sensor of catecholamine, namely, dopamine and ascorbic acid. Carbon dots (CDs were prepared from a green source: commercially available Assam tea. The carbon dots prepared from tea had particle sizes of ∼0.8 nm and are fluorescent. Fluorescence of the carbon dots was found to be quenched in the presence of dopamine and ascorbic acid with greater sensitivity for dopamine. The minimum detectable limits were determined to be 33 μM and 98 μM for dopamine and ascorbic acid, respectively. The quenching constants determined from Stern-Volmer plot were determined to be 5 × 10−4 and 1 × 10−4 for dopamine and ascorbic acid, respectively. A probable mechanism of quenching has been discussed in the paper.

  1. [The interaction between nerve cells and carbon nanotube networks made by CVD process investigation]. (United States)

    Bobrinetskiĭ, I I; Seleznev, A S; Gaĭduchenko, I A; Fedorov, G E; Domantovskiĭ, A G; Presniakov, M Iu; Podcherniaeva, R Ia; Mikhaĭlova, G R; Suetina, I A


    In this research we investigate neuroblastoma cells cultivated on single-walled carbon nanotubes networks made by CVD method on silicon substrates. The complex analysis of grown cells made by atomic force, electron microscopy and Raman spectroscopy was carried out and the effect of nanotube growth process on proliferation factor was investigated. It is shown that despite of a weak decrease in proliferation, cell morphology remains unchanged and no physical or chemical interaction between carbon nanotubes and cells is observed. The results of the research can be used to investigate the interaction between conductive nanomaterials and cells for the development of neural replacement implants. Also they can be useful in bio-electronic interface investigation of signal propagation in neurons.

  2. Free-Standing Porous Carbon Nanofiber Networks from Electrospinning Polyimide for Supercapacitors

    Directory of Open Access Journals (Sweden)

    Bo Wang


    Full Text Available Free-standing porous carbon nanofiber networks (CFNs were synthesized by electrospinning method and carbonization procedure. We study the implementation of porous CFNs as supercapacitor electrodes and electrochemical measurements demonstrated that porous CFNs exhibit a specific capacitance (205 F/g at the scan rate of 5 mV/s with high flexibility and good rate capability performance (more than 70% of its initial capacitance from 5 mV/s to 200 mV/s. Furthermore, porous CFNs exhibited an excellent cycling stability (just 12% capacitance loss after 10,000 cycles. These results suggest that porous CFNs are very promising candidates as flexible supercapacitor electrodes.

  3. Electric Characteristics of the Carbon Nanotube Network Transistor with Directly Grown ZnO Nanoparticles. (United States)

    Kim, Un Jeong; Bae, Gi Yoon; Suh, Dong Ik; Park, Wanjun


    We report on the electrical characteristics of field effect transistors fabricated with random networks of single-walled carbon nanotubes with surfaces modified by ZnO nanoparticles. ZnO nanoparticles are directly grown on single-walled carbon nanotubes by atomic layer deposition using diethylzinc (DEZ) and water. Electrical observations show that ZnO nanoparticles act as charge transfer sources that provide electrons to the nanotube channel. The valley position in ambipolar transport of nanotube transistors is negatively shifted for 3V due to the electronic n-typed property of ZnO nanoparticles. However, the Raman resonance remains invariant despite the charge transfer effect produced by ZnO nanoparticles.

  4. Evaluating conducting network based transparent electrodes from geometrical considerations

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Ankush [Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, 560064 Bangalore (India); Kulkarni, G. U., E-mail: [Centre for Nano and Soft Matter Sciences, 560013 Bangalore (India)


    Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained from conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in

  5. Carbon dioxide and methane dynamics in a human-dominated lowland coastal river network (Shanghai, China) (United States)

    Yu, Zhongjie; Wang, Dongqi; Li, Yangjie; Deng, Huanguang; Hu, Beibei; Ye, Mingwu; Zhou, Xuhui; Da, Liangjun; Chen, Zhenlou; Xu, Shiyuan


    Evasion of carbon dioxide (CO2) and methane (CH4) in streams and rivers play a critical role in global carbon (C) cycle, offsetting the C uptake by terrestrial ecosystems. However, little is known about CO2 and CH4 dynamics in lowland coastal rivers profoundly modified by anthropogenic perturbations. Here we report results from a long-term, large-scale study of CO2 and CH4 partial pressures (pCO2 and pCH4) and evasion rates in the Shanghai river network. The spatiotemporal variabilities of pCO2 and pCH4 were examined along a land use gradient, and the annual CO2 and CH4 evasion were estimated to assess its role in regional C budget. During the study period (August 2009 to October 2011), the overall mean pCO2 and median pCH4 from 87 surveyed rivers were 5846 ± 2773 μatm and 241 μatm, respectively. Internal metabolic CO2 production and dissolved inorganic carbon input via upstream runoff were the major sources sustaining the widespread CO2 supersaturation, coupling pCO2 to biogeochemical and hydrological controls, respectively. While CH4 was oversaturated throughout the river network, CH4 hot spots were concentrated in the small urban rivers and highly discharge-dependent. The Shanghai river network played a disproportionately important role in regional C budget, offsetting up to 40% of the regional terrestrial net ecosystem production and 10% of net C uptake in the river-dominated East China Sea fueled by anthropogenic nutrient input. Given the rapid urbanization in global coastal areas, more research is needed to quantify the role of lowland coastal rivers as a major landscape C source in global C budget.

  6. Bioinspired evolutionary algorithm based for improving network coverage in wireless sensor networks. (United States)

    Abbasi, Mohammadjavad; Bin Abd Latiff, Muhammad Shafie; Chizari, Hassan


    Wireless sensor networks (WSNs) include sensor nodes in which each node is able to monitor the physical area and send collected information to the base station for further analysis. The important key of WSNs is detection and coverage of target area which is provided by random deployment. This paper reviews and addresses various area detection and coverage problems in sensor network. This paper organizes many scenarios for applying sensor node movement for improving network coverage based on bioinspired evolutionary algorithm and explains the concern and objective of controlling sensor node coverage. We discuss area coverage and target detection model by evolutionary algorithm.

  7. No longer simply a Practice-based Research Network (PBRN) health improvement networks. (United States)

    Williams, Robert L; Rhyne, Robert L


    While primary care Practice-based Research Networks are best known for their original, research purpose, evidence accumulating over the last several years is demonstrating broader values of these collaborations. Studies have demonstrated their role in quality improvement and practice change, in continuing professional education, in clinician retention in medically underserved areas, and in facilitating transition of primary care organization. A role in informing and facilitating health policy development is also suggested. Taking into account this more robust potential, we propose a new title, the Health Improvement Network, and a new vision for Practice-based Research Networks.

  8. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

    National Research Council Canada - National Science Library

    Antonio Artuñedo; Raúl M del Toro; Rodolfo E Haber


    .... The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks...

  9. Selectivity of Chemoresistive Sensors Made of Chemically Functionalized Carbon Nanotube Random Networks for Volatile Organic Compounds (VOC

    Directory of Open Access Journals (Sweden)

    Jean-François Feller


    Full Text Available Different grades of chemically functionalized carbon nanotubes (CNT have been processed by spraying layer-by-layer (sLbL to obtain an array of chemoresistive transducers for volatile organic compound (VOC detection. The sLbL process led to random networks of CNT less conductive, but more sensitive to vapors than filtration under vacuum (bucky papers. Shorter CNT were also found to be more sensitive due to the less entangled and more easily disconnectable conducting networks they are making. Chemical functionalization of the CNT’ surface is changing their selectivity towards VOC, which makes it possible to easily discriminate methanol, chloroform and tetrahydrofuran (THF from toluene vapors after the assembly of CNT transducers into an array to make an e-nose. Interestingly, the amplitude of the CNT transducers’ responses can be enhanced by a factor of five (methanol to 100 (chloroform by dispersing them into a polymer matrix, such as poly(styrene (PS, poly(carbonate (PC or poly(methyl methacrylate (PMMA. COOH functionalization of CNT was found to penalize their dispersion in polymers and to decrease the sensors’ sensitivity. The resulting conductive polymer nanocomposites (CPCs not only allow for a more easy tuning of the sensors’ selectivity by changing the chemical nature of the matrix, but they also allow them to adjust their sensitivity by changing the average gap between CNT (acting on quantum tunneling in the CNT network. Quantum resistive sensors (QRSs appear promising for environmental monitoring and anticipated disease diagnostics that are both based on VOC analysis.

  10. Software-defined Radio Based Measurement Platform for Wireless Networks. (United States)

    Chao, I-Chun; Lee, Kang B; Candell, Richard; Proctor, Frederick; Shen, Chien-Chung; Lin, Shinn-Yan


    End-to-end latency is critical to many distributed applications and services that are based on computer networks. There has been a dramatic push to adopt wireless networking technologies and protocols (such as WiFi, ZigBee, WirelessHART, Bluetooth, ISA100.11a, etc.) into time-critical applications. Examples of such applications include industrial automation, telecommunications, power utility, and financial services. While performance measurement of wired networks has been extensively studied, measuring and quantifying the performance of wireless networks face new challenges and demand different approaches and techniques. In this paper, we describe the design of a measurement platform based on the technologies of software-defined radio (SDR) and IEEE 1588 Precision Time Protocol (PTP) for evaluating the performance of wireless networks.

  11. A network-based dynamical ranking system for competitive sports (United States)

    Motegi, Shun; Masuda, Naoki


    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  12. A network-based dynamical ranking system for competitive sports. (United States)

    Motegi, Shun; Masuda, Naoki


    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.


    Directory of Open Access Journals (Sweden)



    Full Text Available Problem statement Among the developed technologies metal-composites production,a special place takes powder metallurgy, having fundamental differences from conventionally used foundry technologies. The main advantages of this technology are: the possibility of sensitive control, the structure and phase composition of the starting components, and ultimately the possibility of obtaining of bulk material in nanostructured state with a minimum of processing steps. The potential reinforcers metals include micro and nano-sized oxides, carbides, nitrides, whiskers. The special position is occupied with carbon nanostructures (CNS: С60 fullerenes, single-layer and multi-layer nanotubes, onions (spherical "bulbs", nano-diamonds and graphite,their properties are being intensively studied in recent years. These objects have a high thermal and electrical conductivity values, superelasticity, and have a strength approximate to the theoretical value, which can provide an obtaining composite nanomaterial with a unique set of physical and mechanical properties. In creation of a metal matrix composite nanomaterials (CM, reinforced by various CNS, a special attention should be given to mechanical activation processes (MA already at the stage of preparation of the starting components affecting the structure, phase composition and properties of aluminum-matrix composites. Purpose. To investigate the influence of mechanical activation on the structure and phase composition of aluminum-matrix composites. Conclusion. The results of the study of the structure and phase composition of the initial and mechanically activated powders and bulk-modified metal-composites are shown, depending on the type and concentration of modifying varieties CNS, regimes of MA and parameters of compaction. The study is conducted of tribological properties of Al-CNS OF nanostructured materials.

  14. Design, Implementation and Optimization of Innovative Internet Access Networks, based on Fog Computing and Software Defined Networking


    Iotti, Nicola


    1. DESIGN In this dissertation we introduce a new approach to Internet access networks in public spaces, such as Wi-Fi network commonly known as Hotspot, based on Fog Computing (or Edge Computing), Software Defined Networking (SDN) and the deployment of Virtual Machines (VM) and Linux containers, on the edge of the network. In this vision we deploy specialized network elements, called Fog Nodes, on the edge of the network, able to virtualize the physical infrastructure and expose APIs to e...

  15. Novel self-sensing carbon nanotube-based composites for rehabilitation of structural steel members (United States)

    Ahmed, Shafique; Doshi, Sagar; Schumacher, Thomas; Thostenson, Erik T.; McConnell, Jennifer


    Fatigue and fracture are among the most critical forms of damage in metal structures. Fatigue damage can initiate from microscopic defects (e.g., surface scratches, voids in welds, and internal defects) and initiate a crack. Under cyclic loading, these cracks can grow and reach a critical level to trigger fracture of the member which leads to compromised structural integrity and, in some cases, catastrophic failure of the entire structure. In our research, we are investigating a solution using carbon nanotube-based sensing composites, which have the potential to simultaneously rehabilitate and monitor fatigue-cracked structural members. These composites consist of a fiber-reinforced polymer (FRP) layer and a carbon nanotube-based sensing layer, which are integrated to form a novel structural self-sensing material. The sensing layer is composed of a non-woven aramid fabric that is coated with carbon nanotubes (CNT) to form an electrically conductive network that is extremely sensitive to detecting deformation as well as damage accumulation via changes in the resistance of the CNT network. In this paper, we introduce the sensing concept, describe the manufacturing of a model sensing prototype, and discuss a set of small-scale laboratory experiments to examine the load-carrying capacity and damage sensing response.

  16. An FPGA-based torus communication network

    Energy Technology Data Exchange (ETDEWEB)

    Pivanti, Marcello; Schifano, Sebastiano Fabio [INFN, Ferrara (Italy); Ferrara Univ. (Italy); Simma, Hubert [DESY, Zeuthen (Germany). John von Neumann-Institut fuer Computing NIC


    We describe the design and FPGA implementation of a 3D torus network (TNW) to provide nearest-neighbor communications between commodity multi-core processors. The aim of this project is to build up tightly interconnected and scalable parallel systems for scientific computing. The design includes the VHDL code to implement on latest FPGA devices a network processor, which can be accessed by the CPU through a PCIe interface and which controls the external PHYs of the physical links. Moreover, a Linux driver and a library implementing custom communication APIs are provided. The TNW has been successfully integrated in two recent parallel machine projects, QPACE and AuroraScience. We describe some details of the porting of the TNW for the AuroraScience system and report performance results. (orig.)

  17. Network-based in silico drug efficacy screening

    National Research Council Canada - National Science Library

    Guney, Emre; Menche, Jörg; Vidal, Marc; Barábasi, Albert-László


    .... Here, we take advantage of our increasing understanding of the network-based origins of diseases to introduce a drug-disease proximity measure that quantifies the interplay between drugs targets and diseases...

  18. Interpenetrating polymer network hydrogels based on polysaccharides for biomedical applications

    NARCIS (Netherlands)

    Pescosolido, L.


    The main theme of this thesis is the development and the characterization of interpenetrating polymer network hydrogels (IPNs) based on biodegradable and biocompatible polysaccharides, in particular alginate, hyaluronic acid and dextran. The suitability of these novel systems as pharmaceutical and

  19. Super square carbon nanotube network: a new promising water desalination membrane (United States)

    Sun, Ligang; He, Xiaoqiao; Lu, Jian


    Super square (SS) carbon nanotube (CNT) networks, acting as a new kind of nanoporous membrane, manifest excellent water desalination performance. Nanopores in SS CNT network can efficiently filter NaCl from water. The water desalination ability of such nanoporous membranes critically depends on the pore diameter, permitting water molecule permeatration while salt ion obstruction. On the basis of the systematical analysis on the interaction among water permeability, salt concentration limit and pressure on the membranes, an empirical formula is developed to describe the relationship between pressure and concentration limit. In the meantime, the nonlinear relationship between pressure and water permeability is examined. Hence, by controlling pressure, optimal plan can be easily made to efficiently filter the saltwater. Moreover, steered molecular dynamics (MD) method uncovers bending and local buckling of SS CNT network that leads to salt ions passing through membranes. These important mechanical behaviours are neglected in most MD simulations, which may overestimate the filtration ability. Overall, water permeability of such material is several orders of magnitude higher than the conventional reverse osmosis membranes and several times higher than nanoporous graphene membranes. SS CNT networks may act as a new kind of membrane developed for water desalination with excellent filtration ability.

  20. Size effect on brittle and ductile fracture of two-dimensional interlinked carbon nanotube network (United States)

    Jing, Yuhang; Aluru, N. R.


    The mechanical properties of two-dimensional (2D) interlinked carbon nanotube (CNT) network are investigated using ab initio calculation and molecular dynamics simulations (MD) with Reaxff force field. The simulation results show that bulk 2D interlinked CNT network has good mechanical properties along the axial direction which can be comparable to that of single-walled CNT and graphene, but has better ductility along the radial direction than single-walled CNT and graphene. In addition, the mechanical properties of 2D interlinked CNT network ribbon along the radial direction depend strongly on the size of the ribbon. The Young's modulus and Poisson's ratio decrease as the size increases while the fracture strain increases with the size increasing. By analyzing the atomic structural (both bond length and atomic von Mises stress) evolution of the ribbons, the mechanism of a brittle-to-ductile transition is revealed. The exploration of the mechanical properties of the 2D interlinked CNT network paves the way for application of the relevant devices that can benefit from the high Young's modulus, high tensile strength, and good ductility.

  1. Electrical properties of carbon-nanotube-network transistors in air after gamma irradiation (United States)

    Ishii, Satoshi; Yabe, Daisuke; Enomoto, Shotaro; Koshio, Shigeru; Konishi, Teruaki; Hamano, Tsuyoshi; Hirao, Toshio


    We experimentally evaluate the electrical properties of carbon nanotube (CNT)-network transistors before and after 60Co gamma-ray irradiation up to 50 kGy in an air environment. When the total dose is increased, the degree of the threshold voltage (Vth) shift towards positive gate voltages in the drain current-gate voltage (ID-VGS) characteristics decreases for total irradiation doses above 30 kGy, although it is constant below 30 kGy. From our analysis of the ID-VGS characteristics along with micro-Raman spectroscopy, the gamma-ray irradiation does not change the structure of the CNT network channel for total doses up to 50 kGy; it instead generates charge traps near the CNT/SiO2 gate insulator interfaces. These traps are located within the SiO2 layer and/or the adsorbate on the device surface. The positively charged traps near the CNT/SiO2 interface contribute less to the Vth shift than the interface dipoles at the CNT/metal electrode interfaces and the segment of the CNT network channel below doses of 30 kGy, while the contribution of the charge traps increases for total doses above 30 kGy. Our findings indicate the possibility of the application of CNT-network transistors as radiation detectors suitable for use in air for radiation doses above 30 kGy.

  2. Carbon-based nanomaterials: multifunctional materials for biomedical engineering. (United States)

    Cha, Chaenyung; Shin, Su Ryon; Annabi, Nasim; Dokmeci, Mehmet R; Khademhosseini, Ali


    Functional carbon-based nanomaterials (CBNs) have become important due to their unique combinations of chemical and physical properties (i.e., thermal and electrical conductivity, high mechanical strength, and optical properties), and extensive research efforts are being made to utilize these materials for various industrial applications, such as high-strength materials and electronics. These advantageous properties of CBNs are also actively investigated in several areas of biomedical engineering. This Perspective highlights different types of carbon-based nanomaterials currently used in biomedical applications.

  3. Surface characterization and functional properties of carbon-based materials



    Carbon-based materials are poised to be an important class of 21st century materials, for bio-medical, bio-electronic, and bio-sensing applications. Diamond and polymers are two examples of carbon-based materials of high interest to the bio-materials community. Diamond, in its conductive form, can be used as an electrochemical bio-sensor, whilst its nanoparticle form is considered a non-inflammatory platform to deliver drugs or to grow neuronal cells. Polymers, especially when chemically m...

  4. Ionic liquid based multifunctional double network gel (United States)

    Ahmed, Kumkum; Higashihara, Tomoya; Arafune, Hiroyuki; Kamijo, Toshio; Morinaga, Takashi; Sato, Takaya; Furukawa, Hidemitsu


    Gels are a promising class of soft and wet materials with diverse application in tissue engineering and bio-medical purpose. In order to accelerate the development of gels, it is required to synthesize multi-functional gels of high mechanical strength, ultra low surface friction and suitable elastic modulus with a variety of methods and new materials. Among many types of gel ionic gel made from ionic liquids (ILs) could be used for diverse applications in electrochemical devices and in the field of tribology. IL, a promising materials for lubrication, is a salt with a melting point lower than 100 °C. As a lubricant, ILs are characterized by an extremely low vapor pressure, high thermal stability and high ion conductivity. In this work a novel approach of making double network DN ionic gel using IL has been made utilizing photo polymerization process. A hydrophobic monomer Methyl methacrylate (MMA) has been used as a first network and a hydrophobic IL monomer, N,N-diethyl-N-(2-mthacryloylethyl)-N-methylammonium bistrifluoromethylsulfonyl)imide (DEMM-TFSI) has been used as a second network using photo initiator benzophenon and crosslinker triethylene glycol dimethacrylate (TEGDMA). The resulting DN ionic gel shows transparency, flexibility, high thermal stability, good mechanical toughness and low friction coefficient value which can be a potential candidate as a gel slider in different mechanical devices and can open a new area in the field of gel tribology.


    Directory of Open Access Journals (Sweden)

    Petrişor JALBĂ


    Full Text Available Within the framework of the current revolution in military affairs, at the End of the Cold War a new concept was born: the concept of War Based on Computer Networking or NCW Network Centric-Warfare which was established as a central element of modern military operations. Determined by theprogress recorded in the field of communication systems of all types, technology of information (HI-Tech, IT, war based on computer networking brings a change in the war paradigm and its inherent components In this respect, logistics based on computer networking represents one of the ways in which the reality of the battlefield is preserved which enhances the joint perspective upon the military forces.

  6. Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties. (United States)

    Salahinejad, Maryam


    Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

  7. Carbon-Nanotube-Based Thermoelectric Materials and Devices

    Energy Technology Data Exchange (ETDEWEB)

    Blackburn, Jeffrey L. [Chemistry and Nanoscience Center, National Renewable Energy Laboratory, Golden CO 80401-3305 USA; Ferguson, Andrew J. [Chemistry and Nanoscience Center, National Renewable Energy Laboratory, Golden CO 80401-3305 USA; Cho, Chungyeon [Department of Mechanical Engineering, Texas A& M University, College Station TX 77843-3003 USA; Grunlan, Jaime C. [Department of Mechanical Engineering, Texas A& M University, College Station TX 77843-3003 USA


    Conversion of waste heat to voltage has the potential to significantly reduce the carbon footprint of a number of critical energy sectors, such as the transportation and electricity-generation sectors, and manufacturing processes. Thermal energy is also an abundant low-flux source that can be harnessed to power portable/wearable electronic devices and critical components in remote off-grid locations. As such, a number of different inorganic and organic materials are being explored for their potential in thermoelectric-energy-harvesting devices. Carbon-based thermoelectric materials are particularly attractive due to their use of nontoxic, abundant source-materials, their amenability to high-throughput solution-phase fabrication routes, and the high specific energy (i.e., W g-1) enabled by their low mass. Single-walled carbon nanotubes (SWCNTs) represent a unique 1D carbon allotrope with structural, electrical, and thermal properties that enable efficient thermoelectric-energy conversion. Here, the progress made toward understanding the fundamental thermoelectric properties of SWCNTs, nanotube-based composites, and thermoelectric devices prepared from these materials is reviewed in detail. This progress illuminates the tremendous potential that carbon-nanotube-based materials and composites have for producing high-performance next-generation devices for thermoelectric-energy harvesting.

  8. Carbon-Nanotube-Based Thermoelectric Materials and Devices. (United States)

    Blackburn, Jeffrey L; Ferguson, Andrew J; Cho, Chungyeon; Grunlan, Jaime C


    Conversion of waste heat to voltage has the potential to significantly reduce the carbon footprint of a number of critical energy sectors, such as the transportation and electricity-generation sectors, and manufacturing processes. Thermal energy is also an abundant low-flux source that can be harnessed to power portable/wearable electronic devices and critical components in remote off-grid locations. As such, a number of different inorganic and organic materials are being explored for their potential in thermoelectric-energy-harvesting devices. Carbon-based thermoelectric materials are particularly attractive due to their use of nontoxic, abundant source-materials, their amenability to high-throughput solution-phase fabrication routes, and the high specific energy (i.e., W g -1 ) enabled by their low mass. Single-walled carbon nanotubes (SWCNTs) represent a unique 1D carbon allotrope with structural, electrical, and thermal properties that enable efficient thermoelectric-energy conversion. Here, the progress made toward understanding the fundamental thermoelectric properties of SWCNTs, nanotube-based composites, and thermoelectric devices prepared from these materials is reviewed in detail. This progress illuminates the tremendous potential that carbon-nanotube-based materials and composites have for producing high-performance next-generation devices for thermoelectric-energy harvesting. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network. (United States)

    Lin, Kai; Wang, Di; Hu, Long


    With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods.

  10. Design and Simulation Analysis for Integrated Vehicle Chassis-Network Control System Based on CAN Network

    Directory of Open Access Journals (Sweden)

    Wei Yu


    Full Text Available Due to the different functions of the system used in the vehicle chassis control, the hierarchical control strategy also leads to many kinds of the network topology structure. According to the hierarchical control principle, this research puts forward the integrated control strategy of the chassis based on supervision mechanism. The purpose is to consider how the integrated control architecture affects the control performance of the system after the intervention of CAN network. Based on the principle of hierarchical control and fuzzy control, a fuzzy controller is designed, which is used to monitor and coordinate the ESP, AFS, and ARS. And the IVC system is constructed with the upper supervisory controller and three subcontrol systems on the Simulink platform. The network topology structure of IVC is proposed, and the IVC communication matrix based on CAN network communication is designed. With the common sensors and the subcontrollers as the CAN network independent nodes, the network induced delay and packet loss rate on the system control performance are studied by simulation. The results show that the simulation method can be used for designing the communication network of the vehicle.

  11. Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

    Directory of Open Access Journals (Sweden)

    Kai Lin


    Full Text Available With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC. The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods.

  12. Theory of fractional order elements based impedance matching networks

    KAUST Repository

    Radwan, Ahmed G.


    Fractional order circuit elements (inductors and capacitors) based impedance matching networks are introduced for the first time. In comparison to the conventional integer based L-type matching networks, fractional matching networks are much simpler and versatile. Any complex load can be matched utilizing a single series fractional element, which generally requires two elements for matching in the conventional approach. It is shown that all the Smith chart circles (resistance and reactance) are actually pairs of completely identical circles. They appear to be single for the conventional integer order case, where the identical circles completely overlap each other. The concept is supported by design equations and impedance matching examples. © 2010 IEEE.

  13. A Mobile Network Planning Tool Based on Data Analytics

    Directory of Open Access Journals (Sweden)

    Jessica Moysen


    Full Text Available Planning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity of layers, applications, and Radio Access Technologies (RAT. In this context, a network planning tool capable of dealing with this complexity is highly convenient. The objective is to exploit the information produced by and already available in the network to properly deploy, configure, and optimise network nodes. This work presents such a smart network planning tool that exploits Machine Learning (ML techniques. The proposed approach is able to predict the Quality of Service (QoS experienced by the users based on the measurement history of the network. We select Physical Resource Block (PRB per Megabit (Mb as our main QoS indicator to optimise, since minimizing this metric allows offering the same service to users by consuming less resources, so, being more cost-effective. Two cases of study are considered in order to evaluate the performance of the proposed scheme, one to smartly plan the small cell deployment in a dense indoor scenario and a second one to timely face a detected fault in a macrocell network.

  14. Carbon based magnetism an overview of the magnetism of metal free carbon-based compounds and materials

    CERN Document Server

    Makarova, Tatiana


    Magnetism is one of the most intriguing phenomena observed in nature. Magnetism is relevant to physics and geology, biology and chemistry. Traditional magnets, an ubiquitous part of many everyday gadgets, are made of heavy iron- or nickel based materials. Recently there have been reports on the observation of magnetism in carbon, a very light and biocompatible element. Metal-free carbon structures exhibiting magnetic ordering represent a new class of materials and open a novel field of research that could lead to many new technologies. · The most complete, detailed, and accurate Guide in the magnetism of carbon · Dynamically written by the leading experts · Deals with recent scientific highlights · Gathers together chemists and physicists, theoreticians and experimentalists · Unified treatment rather than a series of individually authored papers · Description of genuine organic molecular ferromagnets · Unique description of new carbon materials with Curie temperatures well above ambient.

  15. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    CERN Document Server

    Csermely, Peter


    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  16. Event-driven approach of layered multicast to network adaptation in RED-based IP networks (United States)

    Nahm, Kitae; Li, Qing; Kuo, C.-C. J.


    In this work, we investigate the congestion control problem for layered video multicast in IP networks of active queue management (AQM) using a simple random early detection (RED) queue model. AQM support from networks improves the visual quality of video streaming but makes network adaptation more di+/-cult for existing layered video multicast proticols that use the event-driven timer-based approach. We perform a simplified analysis on the response of the RED algorithm to burst traffic. The analysis shows that the primary problem lies in the weak correlation between the network feedback and the actual network congestion status when the RED queue is driven by burst traffic. Finally, a design guideline of the layered multicast protocol is proposed to overcome this problem.

  17. Mutual information-based LPI optimisation for radar network (United States)

    Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun


    Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

  18. Topological Embedding Feature Based Resource Allocation in Network Virtualization

    Directory of Open Access Journals (Sweden)

    Hongyan Cui


    Full Text Available Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.

  19. The competitive dynamics of network-based businesses. (United States)

    Coyne, K P; Dye, R


    Telecommunications carriers, transportation companies, and banks are among the many network-based businesses--companies that move people, goods, or information from various points to various other points. Managers have long assumed that customers valued all links in these networks equally. It was thought that banking customers, for example, sought access to all of the branches throughout the network or that shipping customers wanted to be able to send packages everywhere. Intuitively, managers thought that many of their customers' needs were, in reality, narrower, but they had no way of knowing which links were most important. New computing power and robust mapping software now make it possible to understand network customers better. In applying this technology, the authors, both consultants from McKinsey & Company, have uncovered three distinct usage patterns: one in which all links are, indeed, valued equally; another in which customers concentrate their use in particular zones; and a third in which customers value only individual links. Each of these patterns requires a different strategy to direct executives in making the decisions fundamental to managing any network-based business: whether to open or close outlets, whether to connect their network to others, and how to organize business units so that they reflect the network's structure. Those who don't spot the patterns or understand their strategic implications will find themselves on the losing end of the network battle.

  20. Combining Host-based and network-based intrusion detection system

    African Journals Online (AJOL)

    These attacks were simulated using hping. The proposed system is implemented in Java. The results show that the proposed system is able to detect attacks both from within (host-based) and outside sources (network-based). Key Words: Intrusion Detection System (IDS), Host-based, Network-based, Signature, Security log.

  1. Use of neutron radiography and tomography to identify fracture network connectivity in low permeability carbonates (United States)

    Lewis, Helen; Zihms, Stephanie; Couples, Gary; Charalampidou, Elma-Maria; Hall, Stephen; Tudisco, Erika; Edlmann, Katriona; Ando, Edward; Etxegarai, Maddi; Tengattini, Alessandro; Atkins, Duncan


    For low permeability rocks, open fractures have the potential to provide a dominant flow pathway, but determining effective connectivity, and associated single or multi-phase flow characteristics within an intact sample, is not simple. Flow tests can provide bulk values for any one sample, but general predictability requires considerably more information. X-ray tomography (XRT) has been used to identify fracture patterns and apertures in 3D. Here, in addition to XRT of experimentally-fractured low-permeability laminites, neutron beam radiography and tomography have been used to image flow via sensitivity to protons. To our knowledge this is the first identification of fluid front movement through fracture arrays using neutron tomography. Specifically, samples of a very fine-grained laminite, a layered carbonate rock deposited in a lake bed environment, with a "grain" size of approximately 5µm, were deformed experimentally under conditions representing 1 to 2 km burial depth, creating a series of shear- and extension- fractures that XRT indicated were at least partly open (Fig 1). But only destructive assessment (e.g. SEM) could verify this, destroying the ability to test flow capabilities in the process. Neutron tomography, using deuterated and then distilled water (which have slightly different densities and significantly different Neutron absorption) are introduced into the sample base, under pressure control, enabling observation of the progression of deuterated water into the air-filled laminite matrix- and fracture space-network, following by distilled water that mainly flows in the fractures (Fig. 2). Radiography and tomography identify a complex but rational pattern of initial water movement into the matrix laminae that suggests that in unfractured laminite, the fluid front would progress stepwise from one lamina to the next with a relatively fast filling across an entered lamina and relatively slow progression across the overlying lamina. But in the

  2. Neutron irradiation studies on low density pan fiber based carbon/carbon composites (United States)

    Venugopalan, Ramani; Sathiyamoorthy, D.; Acharya, R.; Tyagi, A. K.


    Carbon has been extensively used in nuclear reactors and there has been growing interest to develop carbon-based materials for high-temperature nuclear and fusion reactors. Carbon-carbon composite materials as against conventional graphite material are now being looked into as the promising materials for the high temperature reactor due their ability to have high thermal conductivity and high thermal resistance. Research on the development of such materials and their irradiation stability studies are scant. In the present investigations carbon-carbon composite has been developed using polyacrylonitrile (PAN) fiber. Two samples denoted as Sample-1 and Sample-2 have been prepared by impregnation using phenolic resin at pressure of 30 bar for time duration 10 h and 20 h respectively, and they have been irradiated by neutrons. The samples were irradiated in a flux of 10 12 n/cm 2/s at temperature of 40 °C. The fluence was 2.52 × 10 16 n/cm 2. These samples have been characterized by XRD and Raman spectroscopy before and after neutron irradiation. DSC studies have also been carried out to quantify the stored energy release behavior due to irradiation. The XRD analysis of the irradiated and unirradiated samples indicates that the irradiated samples show the tendency to get ordered structure, which was inferred from the Raman spectroscopy. The stored energy with respect to the fluence level was obtained from the DSC. The stored energy from these carbon composites is very less compared to irradiated graphite under ambient conditions.

  3. Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

    Directory of Open Access Journals (Sweden)

    M. E. Migabo


    Full Text Available Despite its low computational cost, the Gradient Based Routing (GBR broadcast of interest messages in Wireless Sensor Networks (WSNs causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2S at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC techniques.

  4. Passivity-based control and estimation in networked robotics

    CERN Document Server

    Hatanaka, Takeshi; Fujita, Masayuki; Spong, Mark W


    Highlighting the control of networked robotic systems, this book synthesizes a unified passivity-based approach to an emerging cross-disciplinary subject. Thanks to this unified approach, readers can access various state-of-the-art research fields by studying only the background foundations associated with passivity. In addition to the theoretical results and techniques,  the authors provide experimental case studies on testbeds of robotic systems  including networked haptic devices, visual robotic systems,  robotic network systems and visual sensor network systems. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The main body of the book consists of three parts. The first examines how passivity can be utilized for bilateral teleoperation and demonstrates the inherent robustness of the passivity-based controller against communication delays. The second part emphasizes passivity’s usefulness for visual feedback control ...

  5. Supercapacitors based on carbon nanotube fuzzy fabric structural composites (United States)

    Alresheedi, Bakheet Awad

    Supercapacitors used in conjunction with batteries offer a solution to energy storage and delivery problems in systems where high power output is required, such as in fully electric cars. This project aimed to enhance current supercapacitor technology by fabricating activated carbon on a substrate consisting of carbon nanotubes (CNTs) grown on a carbon fiber fabric (fuzzy fabric). The fuzzy surface of CNTs lowers electrical resistance and increases porosity, resulting in a flexible fabric with high specific capacitance. Experimental results confirm that the capacitance of activated carbon fabricated on the fuzzy fiber composite is significantly higher than when activated carbon is formed simply on a bare carbon fiber substrate, indicating the usefulness of CNTs in supercapacitor technology. The fabrication of the fuzzy fiber based carbon electrode was fairly complex. The processing steps included composite curing, stabilization, carbonization and activation. Ratios of the three basic ingredients for the supercapacitor (fiber, CNT and polymer matrix) were investigated through experimentation and Grey relational analysis. The aim of Grey relational analysis was to examine factors that affect the overall performance of the supercapacitor. It is based on finding relationships in both independent and interrelated data series (parameters). Using this approach, it was determined that the amount of CNTs on the fiber surface plays a major role in the capacitor properties. An increased amount of CNTs increases the surface area and electrical conductivity of the substrate, while also reducing the required time of activation. Technical advances in the field of Materials and Structures are usually focused on attaining superior performance while reducing weight and cost. To achieve such combinations, multi-functionality has become essential; namely, to reduce weight by imparting additional functions simultaneously to a single material. In this study, a structural composite with

  6. Atmospheric carbon diooxide mixing ratios from the NOAA Climate Monitoring and Diagnostics Laboratory cooperative flask sampling network, 1967-1993

    Energy Technology Data Exchange (ETDEWEB)

    Conway, T.J.; Tans, P.P. [National Oceanic and Atmospheric Administration, Boulder, CO (United States); BBoden, T.A. [Oak Ridge National Lab., TN (United States)


    This data report documents monthly atmospheric CO{sub 2} mixing ratios and measurements obtained by analyzing individual flask air samples for the NOAA/CMDL global cooperative flask sampling network. Measurements include land-based sampling sites and shipboard measurements covering 14 latitude bands in the Pacific Ocean and South China Sea. Analysis of the NOAA/CMDL flask CO{sub 2} database shows a long-term increase in atmospheric CO{sub 2} mixing ratios since the late 1960s. This report describes how the samples are collected and analyzed and how the data are processed, defines limitations, and restrictions of the data, describes the contents and format of the data files, and provides tabular listings of the monthly carbon dioxide records.

  7. Efficient Vector-Based Forwarding for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Xie


    Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.


    Directory of Open Access Journals (Sweden)

    Zhan Wei Siew


    Full Text Available Wireless sensor networks (WSNs have been vastly developed due to the advances in microelectromechanical systems (MEMS using WSN to study and monitor the environments towards climates changes. In environmental monitoring, sensors are randomly deployed over the interest area to periodically sense the physical environments for a few months or even a year. Therefore, to prolong the network lifetime with limited battery capacity becomes a challenging issue. Low energy adaptive cluster hierarchical (LEACH is the common clustering protocol that aim to reduce the energy consumption by rotating the heavy workload cluster heads (CHs. The CHs election in LEACH is based on probability model which will lead to inefficient in energy consumption due to least desired CHs location in the network. In WSNs, the CHs location can directly influence the network energy consumption and further affect the network lifetime. In this paper, factors which will affect the network lifetime will be presented and the demonstration of fuzzy logic based CH selection conducted in base station (BS will also be carried out. To select suitable CHs that will prolong the network first node dies (FND round and consistent throughput to the BS, energy level and distance to the BS are selected as fuzzy inputs.

  9. Enhanced Electrical Networks of Stretchable Conductors with Small Fraction of Carbon Nanotube/Graphene Hybrid Fillers. (United States)

    Oh, Jae Young; Jun, Gwang Hoon; Jin, Sunghwan; Ryu, Ho Jin; Hong, Soon Hyung


    Carbon nanotubes (CNTs) and graphene are known to be good conductive fillers due to their favorable electrical properties and high aspect ratios and have been investigated for application as stretchable composite conductors. A stretchable conducting nanocomposite should have a small fraction of conductive filler material to maintain stretchability. Here we demonstrate enhanced electrical networks of nanocomposites via the use of a CNT-graphene hybrid system using a small mass fraction of conductive filler. The CNT-graphene hybrid system exhibits synergistic effects that prevent agglomeration of CNTs and graphene restacking and reduce contact resistance by formation of 1D(CNT)-2D(graphene) interconnection. These effects resulted in nanocomposite materials formed of multiwalled carbon nanotubes (MWCNTs), thermally reduced graphene (TRG), and polydimethylsiloxane (PDMS), which had a higher electrical conductivity compared with MWCNT/PDMS or TRG/PDMS nanocomposites until specific fraction that is sufficient to form electrical network among conductive fillers. These nanocomposite materials maintained their electrical conductivity when 60% strained.

  10. The Ephemeral Signature of Permafrost Carbon in an Arctic Fluvial Network (United States)

    Spencer, R. G.; Drake, T.; Guillemette, F.; Chanton, J.; Podgorski, D. C.; Zimov, N.


    Arctic fluvial networks process, outgas, and transport significant quantities of terrestrial organic carbon (OC). The contribution from permafrost thaw, however, remains uncertain. A primary obstacle to quantifying the contribution of permafrost OC is its high biodegradability, since it is lost to microbial respiration soon after thaw. In this study, we investigate the by-product of respiration (dissolved inorganic carbon; DIC) at maximum late-summer thaw in sites spanning the fluvial network in order to assess whether the microbial consumption of permafrost imparts a persisting aged (14C-depleted) signature on the DIC pool. Using keeling-curve incubations, we show that water column bacteria respire different sources of dissolved OC (DOC) downstream. Evidence of permafrost respiration (production of aged DIC) was only present in permafrost-influenced sites. In the non-permafrost sites, ambient DIC was modern, which does not preclude respiration of permafrost OC upstream since depleted 14C in DIC can be easily overwhelmed by modern (14C-enriched) DIC. DOC compositional analysis via FT-ICR-MS showed that aliphatic and nitrogen containing compounds were associated with the production of aged DIC, which provides insight as to why permafrost OC is likely rapidly respired upon thaw. Overall, the results from this study demonstrate the complications of using 14C-DIC as a geochemical tracer for permafrost. We highlight the need for novel and unique conservative geochemical tracers to quantify the release and fate of permafrost OC in fluvial systems.

  11. Surface Modification of Carbon Nanotube Networked Films with Au Nanoclusters for Enhanced NO2 Gas Sensing Applications

    Directory of Open Access Journals (Sweden)

    M. Penza


    Full Text Available Multiwalled carbon nanotube (MWCNT films have been deposited by using plasma-enhanced chemical vapor deposition (PECVD system onto alumina substrates, provided with 6 nm thick cobalt (Co growth catalyst for remarkably improved NO2 gas sensing, at working temperature in the range of 100–250∘C. Functionalization of the MWCNTs with nanoclusters of gold (Au sputtering has been performed to modify the surface of carbon nanotube networked films for enhanced and specific NO2 gas detection up to sub-ppm level. It is demonstrated that the NO2 gas sensitivity of the MWCNT-based sensors depends on Au-loading used as surface-catalyst. The gas response of MWCNT-based chemiresistor is attributed to p-type conductivity in the Au-modified semiconducting MWCNTs with a very good short-term repeatability and faster recovery. The sensor temperature of maximum NO2 sensitivity of the Au-functionalized MWCNTs is found to decrease with increasing Au-loading on their surface, and continuous gas monitoring at ppb level of NO2 is effectively performed with Au-modified MWCNT chemiresistors.


    Directory of Open Access Journals (Sweden)

    Ashish Jain


    Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

  13. Incentive-Based Voltage Regulation in Distribution Networks

    Energy Technology Data Exchange (ETDEWEB)

    Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhou, Xinyang [University of Colorado; Chen, Lijun [University of Colorado


    This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltage constraints. Stability of the proposed schemes is analytically established and numerically corroborated.

  14. A complex network-based importance measure for mechatronics systems (United States)

    Wang, Yanhui; Bi, Lifeng; Lin, Shuai; Li, Man; Shi, Hao


    In view of the negative impact of functional dependency, this paper attempts to provide an alternative importance measure called Improved-PageRank (IPR) for measuring the importance of components in mechatronics systems. IPR is a meaningful extension of the centrality measures in complex network, which considers usage reliability of components and functional dependency between components to increase importance measures usefulness. Our work makes two important contributions. First, this paper integrates the literature of mechatronic architecture and complex networks theory to define component network. Second, based on the notion of component network, a meaningful IPR is brought into the identifying of important components. In addition, the IPR component importance measures, and an algorithm to perform stochastic ordering of components due to the time-varying nature of usage reliability of components and functional dependency between components, are illustrated with a component network of bogie system that consists of 27 components.

  15. Incentive-Based Voltage Regulation in Distribution Networks: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Xinyang; Chen, Lijun; Dall' Anese, Emiliano; Baker, Kyri


    This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltage constraints. Stability of the proposed schemes is analytically established and numerically corroborated.

  16. Network Security Risk Assessment Based on Item Response Theory

    Directory of Open Access Journals (Sweden)

    Fangwei Li


    Full Text Available Owing to the traditional risk assessment method has one-sidedness and is difficult to reflect the real network situation, a risk assessment method based on Item Response Theory (IRT is put forward in network security. First of all, the novel algorithms of calculating the threat of attack and the successful probability of attack are proposed by the combination of IRT model and Service Security Level. Secondly, the service weight of importance is calculated by the three-demarcation analytic hierarchy process. Finally, the risk situation graph of service, host and network logic layer could be generated by the improved method. The simulation results show that this method can be more comprehensive consideration of factors which are affecting network security, and a more realistic network risk situation graph in real-time will be obtained.

  17. Energy savings in mobile broadband network based on load predictions

    DEFF Research Database (Denmark)

    Samulevicius, Saulius; Pedersen, Torben Bach; Sørensen, Troels Bundgaard


    in wireless networks. To save energy in MBNs, one of the options is to turn off parts of the network equipment in areas where traffic falls below a specific predefined threshold. This paper looks at a methodology for identifying periods of the day when cells or sites carrying low traffic are candidates...... for being totally or partly switched off, given that the decrease in service quality can be controlled gracefully when the sites are switched off. Based on traffic data from an operational network, potential average energy savings of approximately 30% with some few low traffic cells/sites reaching up to 99......Abstract—The deployment of new network equipment is resulting in increasing energy consumption in mobile broadband networks (MBNs). This contributes to higher CO2 emissions. Over the last 10 years MBNs have grown considerably, and are still growing to meet the evolution in traffic volume carried...

  18. Realization of Broadband Matched Filter Structures Based on Dual Networks

    Directory of Open Access Journals (Sweden)

    M. Gerding


    Full Text Available This paper deals with the basic electrical properties of dual networks and with their application in broadband matched filter structures. Starting with the main characteristics and different realization methods of dual networks, a filter structure is presented, which is based on a combination of dual networks and which provides a broadband matched input and two decoupled output ports. This filter synthesis focuses on the design of high pass filters, which are suitable to be used as differentiating stages in electrical pulse generators as a part of the so-called pulse shaping network. In order to achieve a proper pulse shape and for the prevention of multiple reflections between the switching circuit and the differentiating network, a broadband matched filter is a basic requirement.

  19. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy


    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  20. Molecularly Imprinted Polymer-Carbon Nanotube based Cotinine sensor

    NARCIS (Netherlands)

    Abbas, Yawar; Bomer, Johan G.; Brusse-Keizer, M.G.J.; Movig, K; van der Valk, P.D.L.P.M.; Pieterse, Marcel E.; Segerink, Loes Irene; Olthuis, Wouter; van den Berg, Albert


    A cotinine sensor based on the dc resistance of a polymer composite films is presented. The composite film comprises a cotinine selective molecularly imprinted polymer and carbon nanotube particles. This polymer film is deposited over a gold interdigitated electrode array to measure its electrical

  1. Synthesis of novel carbon/silica composites based strong acid ...

    Indian Academy of Sciences (India)

    The acidity of the novel carbon/silica composites based solid acid was 2 mmol/g, which was determined through the neu- tralization titration. The titration was carried out as follows: carbonaceous material (40 mg) and 2 N aqueous NaCl (4 ml) were stirred at room temperature for 24 h. The solids were filtered off and washed ...

  2. Reducing carbon transaction costs in community-based forest management

    NARCIS (Netherlands)

    Skutsch, Margaret


    The article considers the potential for community-based forest management (of existing forests) in developing countries, as a future CDM strategy, to sequester and mitigate carbon and to claim credits in future commitment periods. This kind of forestry is cost-effective, and should bring many more

  3. Reducing carbon transaction costs in community based forest management

    NARCIS (Netherlands)

    Skutsch, Margaret

    The paper considers the potential for community based forest management (of existing forests) in developing countries, as a future CDM strategy, to sequester carbon and claim credits in future commitment periods. This kind of forestry is cost effective, and should bring many more benefits to local

  4. VoIP attacks detection engine based on neural network (United States)

    Safarik, Jakub; Slachta, Jiri


    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  5. An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection. (United States)

    Xing, Linlin; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Wang, Lei; Zhang, Yin


    The reconstruction of gene regulatory network (GRN) from gene expression data can discover regulatory relationships among genes and gain deep insights into the complicated regulation mechanism of life. However, it is still a great challenge in systems biology and bioinformatics. During the past years, numerous computational approaches have been developed for this goal, and Bayesian network (BN) methods draw most of attention among these methods because of its inherent probability characteristics. However, Bayesian network methods are time consuming and cannot handle large-scale networks due to their high computational complexity, while the mutual information-based methods are highly effective but directionless and have a high false-positive rate. To solve these problems, we propose a Candidate Auto Selection algorithm (CAS) based on mutual information and breakpoint detection to restrict the search space in order to accelerate the learning process of Bayesian network. First, the proposed CAS algorithm automatically selects the neighbor candidates of each node before searching the best structure of GRN. Then based on CAS algorithm, we propose a globally optimal greedy search method (CAS + G), which focuses on finding the highest rated network structure, and a local learning method (CAS + L), which focuses on faster learning the structure with little loss of quality. Results show that the proposed CAS algorithm can effectively reduce the search space of Bayesian networks through identifying the neighbor candidates of each node. In our experiments, the CAS + G method outperforms the state-of-the-art method on simulation data for inferring GRNs, and the CAS + L method is significantly faster than the state-of-the-art method with little loss of accuracy. Hence, the CAS based methods effectively decrease the computational complexity of Bayesian network and are more suitable for GRN inference.

  6. Density-Based and Transport-Based Core-Periphery Structures in Networks

    CERN Document Server

    Lee, Sang Hoon; Porter, Mason A


    Networks often possess mesoscale structures, and studying them can yield insights into both structure and function. It is most common to study community structure, but numerous other types of mesoscale structures also exist. In this paper, we examine core-periphery structures based on both density and transportation. In such structures, core network components are well-connected both among themselves and to peripheral components, which are not well-connected to anything. We examine core-periphery structures in a wide range of examples of transportation, social, and financial networks---including road networks in large urban areas, a rabbit warren, a dolphin social network, a European interbank network, and a migration network between counties in the United States. We illustrate that a recently developed transport-based notion of node coreness is very useful for characterizing transportation networks. We also generalize this notion to examine core versus peripheral edges, and we show that this new diagnostic i...

  7. Nanoporous Carbide-Derived Carbon Material-Based Linear Actuators

    Directory of Open Access Journals (Sweden)

    Janno Torop


    Full Text Available Devices using electroactive polymer-supported carbon material can be exploited as alternatives to conventional electromechanical actuators in applications where electromechanical actuators have some serious deficiencies. One of the numerous examples is precise microactuators. In this paper, we show for first time the dilatometric effect in nanocomposite material actuators containing carbide-derived carbon (CDC and polytetrafluoroetylene polymer (PTFE. Transducers based on high surface area carbide-derived carbon electrode materials are suitable for short range displacement applications, because of the proportional actuation response to the charge inserted, and high Coulombic efficiency due to the EDL capacitance. The material is capable of developing stresses in the range of tens of N cm-2. The area of an actuator can be dozens of cm2, which means that forces above 100 N are achievable. The actuation mechanism is based on the interactions between the high-surface carbon and the ions of the electrolyte. Electrochemical evaluations of the four different actuators with linear (longitudinal action response are described. The actuator electrodes were made from two types of nanoporous TiC-derived carbons with surface area (SA of 1150 m2 g-1 and 1470 m2 g-1, respectively. Two kinds of electrolytes were used in actuators: 1.0 M tetraethylammonium tetrafluoroborate (TEABF4 solution in propylene carbonate and pure ionic liquid 1-ethyl-3-methylimidazolium trifluoromethanesulfonate (EMITf. It was found that CDC based actuators exhibit a linear movement of about 1% in the voltage range of 0.8 V to 3.0 V at DC. The actuators with EMITf electrolyte had about 70% larger movement compared to the specimen with TEABF4 electrolyte.

  8. Antimony nanoparticles anchored in three-dimensional carbon network as promising sodium-ion battery anode (United States)

    Luo, Wen; Zhang, Pengfei; Wang, Xuanpeng; Li, Qidong; Dong, Yifan; Hua, Jingchen; Zhou, Liang; Mai, Liqiang


    A novel composite with antimony (Sb) nanoparticles anchored in three-dimensional carbon network (denoted as SbNPs@3D-C) is successfully synthesized via a NaCl template-assisted self-assembly strategy, followed by freeze-drying and one-step in-situ carbonization. The three-dimensional interconnected macroporous carbon framework can not only stabilize the architecture and buffer the volume expansion for Sb nanoparticles, but also provide high electrical conductivity for the whole electrode. Consequently, as a sodium-ion battery anode, the SbNPs@3D-C delivers a high reversible capacity (456 mAh g-1 at 100 mA g-1), stable cycling performance (94.3% capacity retention after 500 cycles at 100 mA g-1) as well as superior rate capability (270 mAh g-1 at 2000 mA g-1). When compared with commercial Sb particles, the SbNPs@3D-C exhibits dramatically enhanced electrochemical performance. Free from expensive template sources and complex manipulation, this work might shed some light on the synthesis of low-cost and high-performance materials for the next ;beyond lithium; battery generation.

  9. Improved lithium-ion battery anode capacity with a network of easily fabricated spindle-like carbon nanofibers. (United States)

    Liu, Mengting; Xie, Wenhe; Gu, Lili; Qin, Tianfeng; Hou, Xiaoyi; He, Deyan


    A novel network of spindle-like carbon nanofibers was fabricated via a simplified synthesis involving electrospinning followed by preoxidation in air and postcarbonization in Ar. Not only was the as-obtained carbon network comprised of beads of spindle-like nanofibers but the cubic MnO phase and N elements were successfully anchored into the amorphous carbon matrix. When directly used as a binder-free anode for lithium-ion batteries, the network showed excellent electrochemical performance with high capacity, good rate capacity and reliable cycling stability. Under a current density of 0.2 A g-1, it delivered a high reversible capacity of 875.5 mAh g-1 after 200 cycles and 1005.5 mAh g-1 after 250 cycles with a significant coulombic efficiency of 99.5%.

  10. A Concept of Location-Based Social Network Marketing

    DEFF Research Database (Denmark)

    Tussyadiah, Iis


    A stimulus-response model of location-based social network marketing is conceptualized based on an exploratory investigation. Location-based social network applications are capable of generating marketing stimuli from merchant, competition-based, and connection-based rewards resulted from relevance...... and connectivity. Depending on consumption situations, consumer characteristics, and social network structure, these rewards lead to actual behavior that manifests in variety behavior (i.e., patronage to new places) and loyalty behavior (i.e., increased frequency of patronage to familiar places). This behavior...... implies changes in patterns of mobility, making this marketing approach particularly relevant for tourism and hospitality businesses. Managerial implications and recommendations for further studies are provided....



    East. As globalism has produced hot spots in the Middle East Turkey’s geographic location is advantageous to the US. Turkey’s infrastructure of ports...basing concept. Overseas basing as a subset of the global force posture has totally transformed U.S. thinking about international security and its...basing concept. Overseas basing as a subset of the global force posture has totally transformed U.S. thinking about international security and its

  12. Mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogels

    Energy Technology Data Exchange (ETDEWEB)

    Worsley, Marcus A.; Baumann, Theodore F.; Satcher, Jr., Joe H.


    Disclosed here is a device comprising a porous carbon aerogel or composite thereof as an energy storage material, catalyst support, sensor or adsorbent, wherein the porous carbon aerogel comprises a network of interconnected struts comprising carbon nanotube bundles covalently crosslinked by graphitic carbon nanoparticles, wherein the carbon nanotubes account for 5 to 95 wt. % of the aerogel and the graphitic carbon nanoparticles account for 5 to 95 wt. % of the aerogel, and wherein the aerogel has an electrical conductivity of at least 10 S/m and is capable of withstanding strains of more than 10% before fracture.

  13. Focused Ion Beam Nanopatterning for Carbon Nanotube Ropes Based Sensor

    Directory of Open Access Journals (Sweden)



    Full Text Available Focused Ion Beam (FIB technology has been used to realize electrode patterns for contacting Single Walled Carbon Nanotubes (SWCNTs ropes for chemical gas sensor applications. Two types of transducers, based on a single rope and on bundles, have been realized starting from silicon/Si3N4 substrate. Electrical behaviour, at room temperature, in toxic gas environments, has been investigated and compared to evaluate contribution of a single rope based sensor respect to bundles one. For all the devices, upon exposure to NO2 and NH3, the conductance has been found to increase or decrease respectively. Conductance signal is stronger for sensor based on bundles, but it also evident that response time in NO2 is faster for device based on a single rope. FIB technology offers, then, the possibility to contact easily a single sensitive nanowire, as carbon nanotube rope.

  14. Non-covalently functionalized carbon nanostructures for synthesizing carbon-based hybrid nanomaterials. (United States)

    Li, Haiqing; Song, Sing I; Song, Ga Young; Kim, Il


    Carbon nanostructures (CNSs) such as carbon nanotubes, graphene sheets, and nanodiamonds provide an important type of substrate for constructing a variety of hybrid nanomaterials. However, their intrinsic chemistry-inert surfaces make it indispensable to pre-functionalize them prior to immobilizing additional components onto their surfaces. Currently developed strategies for functionalizing CNSs include covalent and non-covalent approaches. Conventional covalent treatments often damage the structure integrity of carbon surfaces and adversely affect their physical properties. In contrast, the non-covalent approach offers a non-destructive way to modify CNSs with desired functional surfaces, while reserving their intrinsic properties. Thus far, a number of surface modifiers including aromatic compounds, small-molecular surfactants, amphiphilic polymers, and biomacromolecules have been developed to non-covalently functionalize CNS surfaces. Mediated by these surface modifiers, various functional components such as organic species and inorganic nanoparticles were further decorated onto their surfaces, resulting in versatile carbon-based hybrid nanomaterials with broad applications in chemical engineering and biomedical areas. In this review, the recent advances in the generation of such hybrid nanostructures based on non-covalently functionalized CNSs will be reviewed.

  15. Cluster Analysis Based on Bipartite Network

    Directory of Open Access Journals (Sweden)

    Dawei Zhang


    Full Text Available Clustering data has a wide range of applications and has attracted considerable attention in data mining and artificial intelligence. However it is difficult to find a set of clusters that best fits natural partitions without any class information. In this paper, a method for detecting the optimal cluster number is proposed. The optimal cluster number can be obtained by the proposal, while partitioning the data into clusters by FCM (Fuzzy c-means algorithm. It overcomes the drawback of FCM algorithm which needs to define the cluster number c in advance. The method works by converting the fuzzy cluster result into a weighted bipartite network and then the optimal cluster number can be detected by the improved bipartite modularity. The experimental results on artificial and real data sets show the validity of the proposed method.

  16. Quantum-dot based photonic quantum networks (United States)

    Lodahl, Peter


    Quantum dots (QDs) embedded in photonic nanostructures have in recent years proven to be a very powerful solid-state platform for quantum optics experiments. The combination of near-unity radiative coupling of a single QD to a photonic mode and the ability to eliminate decoherence processes imply that an unprecedent light–matter interface can be obtained. As a result, high-cooperativity photon-emitter quantum interfaces can be constructed opening a path-way to deterministic photonic quantum gates for quantum-information processing applications. In the present manuscript, I review current state-of-the-art on QD devices and their applications for quantum technology. The overarching long-term goal of the research field is to construct photonic quantum networks where remote entanglement can be distributed over long distances by photons.

  17. Numerical study on the perception-based network formation model

    CERN Document Server

    Jo, Hang-Hyun


    In order to understand the evolution of social networks in terms of perception-based strategic link formation, we numerically study a perception-based network formation model. Here each individual is assumed to have his/her own perception of the actual network, and use it to decide whether to create a link to other individual. An individual with the least perception accuracy can benefit from updating his/her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. The initial actual network and initial perceptions are modeled by Erd\\H{o}s-R\\'enyi random networks but with different linking probabilities. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. The effect of initial conditions on the complexity o...

  18. Node-Dependence-Based Dynamic Incentive Algorithm in Opportunistic Networks

    Directory of Open Access Journals (Sweden)

    Ruiyun Yu


    Full Text Available Opportunistic networks lack end-to-end paths between source nodes and destination nodes, so the communications are mainly carried out by the “store-carry-forward” strategy. Selfish behaviors of rejecting packet relay requests will severely worsen the network performance. Incentive is an efficient way to reduce selfish behaviors and hence improves the reliability and robustness of the networks. In this paper, we propose the node-dependence-based dynamic gaming incentive (NDI algorithm, which exploits the dynamic repeated gaming to motivate nodes relaying packets for other nodes. The NDI algorithm presents a mechanism of tolerating selfish behaviors of nodes. Reward and punishment methods are also designed based on the node dependence degree. Simulation results show that the NDI algorithm is effective in increasing the delivery ratio and decreasing average latency when there are a lot of selfish nodes in the opportunistic networks.

  19. In silico network topology-based prediction of gene essentiality

    CERN Document Server

    da Silva, Joao Paulo Muller; Mombach, Jose Carlos Merino; Vieira, Renata; da Silva, Jose Guliherme Camargo; Lemke, Ney; Sinigaglia, Marialva


    The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision tree-based machine learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes...

  20. A family of quantization based piecewise linear filter networks

    DEFF Research Database (Denmark)

    Sørensen, John Aasted


    A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...

  1. Agent Based Modeling on Organizational Dynamics of Terrorist Network

    Directory of Open Access Journals (Sweden)

    Bo Li


    Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

  2. Bulk Restoration for SDN-Based Transport Network

    Directory of Open Access Journals (Sweden)

    Yang Zhao


    Full Text Available We propose a bulk restoration scheme for software defined networking- (SDN- based transport network. To enhance the network survivability and improve the throughput, we allow disrupted flows to be recovered synchronously in dynamic order. In addition backup paths are scheduled globally by applying the principles of load balance. We model the bulk restoration problem using a mixed integer linear programming (MILP formulation. Then, a heuristic algorithm is devised. The proposed algorithm is verified by simulation and the results are analyzed comparing with sequential restoration schemes.

  3. Facial expression recognition based on improved deep belief networks (United States)

    Wu, Yao; Qiu, Weigen


    In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

  4. Rewiring Chemical Networks Based on Dynamic Dithioacetal and Disulfide Bonds. (United States)

    Orrillo, A Gastón; La-Venia, Agustina; Escalante, Andrea M; Furlan, Ricardo L E


    The control of the connectivity between nodes of synthetic networks is still largely unexplored. To address this point we take advantage of a simple dynamic chemical system with two exchange levels that are mutually connected and can be activated simultaneously or sequentially. Dithioacetals and disulfides can be exchanged simultaneously under UV light in the presence of a sensitizer. Crossover reactions between both exchange processes produce a fully connected chemical network. On the other hand, the use of acid, base or UV light connects different nodes allowing network rewiring. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Fast, moment-based estimation methods for delay network tomography

    Energy Technology Data Exchange (ETDEWEB)

    Lawrence, Earl Christophre [Los Alamos National Laboratory; Michailidis, George [U OF MICHIGAN; Nair, Vijayan N [U OF MICHIGAN


    Consider the delay network tomography problem where the goal is to estimate distributions of delays at the link-level using data on end-to-end delays. These measurements are obtained using probes that are injected at nodes located on the periphery of the network and sent to other nodes also located on the periphery. Much of the previous literature deals with discrete delay distributions by discretizing the data into small bins. This paper considers more general models with a focus on computationally efficient estimation. The moment-based schemes presented here are designed to function well for larger networks and for applications like monitoring that require speedy solutions.

  6. Computational Framework for Optimal Carbon Taxes Based on Electric Supply Chain Considering Transmission Constraints and Losses

    Directory of Open Access Journals (Sweden)

    Yu-Chi Wu


    Full Text Available A modeling and computational framework is presented for the determination of optimal carbon taxes that apply to electric power plants in the context of electric power supply chain with consideration of transmission constraints and losses. In order to achieve this goal, a generalized electric power supply chain network equilibrium model is used. Under deregulation, there are several players in electrical market: generation companies, power suppliers, transmission service providers, and consumers. Each player in this model tries to maximize its own profit and competes with others in a noncooperative manner. The Nash equilibrium conditions of these players in this model form a finite-dimensional variational inequality problem (VIP. By solving this VIP via an extragradient method based on an interior point algorithm, the optimal carbon taxes of power plants can be determined. Numerical examples are provided to analyze the results of the presented modeling.

  7. Photodetectors based on single-walled carbon nanotubes and thiamonomethinecyanine J-aggregates on flexible substrates

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, I. V., E-mail:; Emel’yanov, A. V.; Romashkin, A. V.; Bobrinetskiy, I. I. [National Research University of Electronic Technology (MIET) (Russian Federation)


    The present paper is devoted to observations of the photoresistive effect in multilayer structures with a sensitive layer of J-aggregates of thiamonomethinecyanine polymethine dye and a transparent electrode of a conductive carbon-nanotube network on a flexible polyethylenenaphtalate substrate. The effect of narrow-band emission with a wavelength of 465 nm on a change in the conductivity of the fabricated structures is studied. The prepared samples are studied by atomic-force microscopy, Raman spectroscopy, and spectrophotometry methods. It is shown that these structures are photosensitive to the indicated spectral region, and the dye layer is a film of dye J-aggregates. The change in the sample conductivity upon exposure to light one hundred times exceeds the dark conductivity. In general, the principal possibility of developing a photoresistive detector based on J-aggregates of cyanine dyes on flexible supports on account of the use of transparent and conductive carbon-nanotube layers is shown.

  8. Carrier ethernet network control plane based on the Next Generation Network

    DEFF Research Database (Denmark)

    Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert


    architecture. The approaches to QoS mapping, label distribution and connection and admission control (CAC) are specified here. At last, a simple T-MPLS based Carrier Ethernet network model with three kinds of users (VoIP, VoD and HTTP) and a RACE based control module is simulated in OPNET. The model is aiming...

  9. Engineered Carbon-Nanomaterial-Based Electrochemical Sensors for Biomolecules. (United States)

    Tiwari, Jitendra N; Vij, Varun; Kemp, K Christian; Kim, Kwang S


    The study of electrochemical behavior of bioactive molecules has become one of the most rapidly developing scientific fields. Biotechnology and biomedical engineering fields have a vested interest in constructing more precise and accurate voltammetric/amperometric biosensors. One rapidly growing area of biosensor design involves incorporation of carbon-based nanomaterials in working electrodes, such as one-dimensional carbon nanotubes, two-dimensional graphene, and graphene oxide. In this review article, we give a brief overview describing the voltammetric techniques and how these techniques are applied in biosensing, as well as the details surrounding important biosensing concepts of sensitivity and limits of detection. Building on these important concepts, we show how the sensitivity and limit of detection can be tuned by including carbon-based nanomaterials in the fabrication of biosensors. The sensing of biomolecules including glucose, dopamine, proteins, enzymes, uric acid, DNA, RNA, and H2O2 traditionally employs enzymes in detection; however, these enzymes denature easily, and as such, enzymeless methods are highly desired. Here we draw an important distinction between enzymeless and enzyme-containing carbon-nanomaterial-based biosensors. The review ends with an outlook of future concepts that can be employed in biosensor fabrication, as well as limitations of already proposed materials and how such sensing can be enhanced. As such, this review can act as a roadmap to guide researchers toward concepts that can be employed in the design of next generation biosensors, while also highlighting the current advancements in the field.

  10. Rotational actuator of motor based on carbon nanotubes (United States)

    Zettl, Alexander K.; Fennimore, Adam M.; Yuzvinsky, Thomas D.


    A rotational actuator/motor based on rotation of a carbon nanotube is disclosed. The carbon nanotube is provided with a rotor plate attached to an outer wall, which moves relative to an inner wall of the nanotube. After deposit of a nanotube on a silicon chip substrate, the entire structure may be fabricated by lithography using selected techniques adapted from silicon manufacturing technology. The structures to be fabricated may comprise a multiwall carbon nanotube (MWNT), two in plane stators S1, S2 and a gate stator S3 buried beneath the substrate surface. The MWNT is suspended between two anchor pads and comprises a rotator attached to an outer wall and arranged to move in response to electromagnetic inputs. The substrate is etched away to allow the rotor to freely rotate. Rotation may be either in a reciprocal or fully rotatable manner.

  11. Metal–carbon nanocomposites based on pyrolysed polyacrylonitrile

    Directory of Open Access Journals (Sweden)

    Irina A. Zaporotskova


    Full Text Available The electronic structure and geometry of metal−carbon nanocomposites based on pyrolyzed polyacrylonitrile (PPAN with Cu, Si, Fe, Co and Ni atoms using the DFT method have been theoretically studied. The effect of nitrogen on the stability of PPAN and its conductivity has been determined. The electrophysical properties and structure of metal nanocomposites have been studied using the XFA method. The composites have been produced by IR heating. We suggest that metal−carbon nanocomposites form due to the special processing of the (PAN−MeR samples. Metal nanoparticles are regularly dispersed in the nanocrystalline matrix of PPAN. The conductivity of these metal−carbon nanocomposites has an activation character and varies from 10−1 to 103 Om/cm depending on synthesis temperature (T=600–900 °С. The results of theoretical and experimental research are in a good agreement.

  12. Gecko inspired carbon nanotube based thermal gap pads (United States)

    Sethi, Sunny; Dhinojwala, Ali


    Thermal management has become a critical factor in designing the next generation of microprocessors. The bottleneck in design of material for efficient heat transfer from electronic units to heat sinks is to enhance heat flow across interface between two dissimilar, rough surfaces. Carbon nanotubes (CNT) have been shown to be promising candidates for thermal transport. However, the heat transport across the interface continues to be a challenging hurdle. In the current work we designed free standing thermal pads based on gecko-inspired carbon nanotube adhesives. The pads were made of metallic carbon nanotubes and the structure was designed such that it would allow large area of intimate contact. We showed that these adhesive pads can be used as electrical and thermal interconnects.

  13. Carbon microelectromechanical systems (C-MEMS) based microsupercapacitors

    KAUST Repository

    Agrawal, Richa


    The rapid development in miniaturized electronic devices has led to an ever increasing demand for high-performance rechargeable micropower scources. Microsupercapacitors in particular have gained much attention in recent years owing to their ability to provide high pulse power while maintaining long cycle lives. Carbon microelectromechanical systems (C-MEMS) is a powerful approach to fabricate high aspect ratio carbon microelectrode arrays, which has been proved to hold great promise as a platform for energy storage. C-MEMS is a versatile technique to create carbon structures by pyrolyzing a patterned photoresist. Furthermore, different active materials can be loaded onto these microelectrode platforms for further enhancement of the electrochemical performance of the C-MEMS platform. In this article, different techniques and methods in order to enhance C-MEMS based various electrochemical capacitor systems have been discussed, including electrochemical activation of C-MEMS structures for miniaturized supercapacitor applications, integration of carbon nanostructures like carbon nanotubes onto C-MEMS structures and also integration of pseudocapacitive materials such as polypyrrole onto C-MEMS structures. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  14. Carbon microelectromechanical systems (C-MEMS) based microsupercapacitors (United States)

    Agrawal, Richa; Beidaghi, Majid; Chen, Wei; Wang, Chunlei


    The rapid development in miniaturized electronic devices has led to an ever increasing demand for high-performance rechargeable micropower scources. Microsupercapacitors in particular have gained much attention in recent years owing to their ability to provide high pulse power while maintaining long cycle lives. Carbon microelectromechanical systems (C-MEMS) is a powerful approach to fabricate high aspect ratio carbon microelectrode arrays, which has been proved to hold great promise as a platform for energy storage. C-MEMS is a versatile technique to create carbon structures by pyrolyzing a patterned photoresist. Furthermore, different active materials can be loaded onto these microelectrode platforms for further enhancement of the electrochemical performance of the C-MEMS platform. In this article, different techniques and methods in order to enhance C-MEMS based various electrochemical capacitor systems have been discussed, including electrochemical activation of C-MEMS structures for miniaturized supercapacitor applications, integration of carbon nanostructures like carbon nanotubes onto C-MEMS structures and also integration of pseudocapacitive materials such as polypyrrole onto C-MEMS structures.

  15. BGP-Based Routing Configuration Management for Multidomain Mobile Networks (United States)


    extend the network management system to exterior routing configuration in dynamically changed topology. 1.0 INTRODUCTION Routing in the Internet is mostly based on BGP protocol [1]. The Internet is in fact the composition of autonomous systems (AS), each of them is independently...Bruin, O. Bonaventure, Open Issues in Interdomain Routing: A Survey, IEEE Network Magazine,Volume 19, 11.2005 [7] D. Street, Global Information Grid

  16. Interoperability in wireless sensor networks based on IEEE 1451 standard


    Higuera Portilla, Jorge Eduardo; Polo Cantero, José


    The syntactic and semantic interoperability is a challenge of the Wireless Sensor Networks (WSN) with smart sensors in pervasive computing environments to increase their harmonization in a wide variety of applications. This chapter contains a detailed description of interoperability in heterogeneous WSN using the IEEE 1451 standard. This work focuses on personal area networks (PAN) with smart sensors and actuators. Also, a technical, syntactic and semantic levels of interoperability based on ...

  17. Cooperative Technique Based on Sensor Selection in Wireless Sensor Network


    ISLAM, M. R.; KIM, J.


    An energy efficient cooperative technique is proposed for the IEEE 1451 based Wireless Sensor Networks. Selected numbers of Wireless Transducer Interface Modules (WTIMs) are used to form a Multiple Input Single Output (MISO) structure wirelessly connected with a Network Capable Application Processor (NCAP). Energy efficiency and delay of the proposed architecture are derived for different combination of cluster size and selected number of WTIMs. Optimized constellation parameters are used for...



    Md. Humayun Kabir


    In this paper, we propose a novel SDN-based cellular network architecture that will be able to utilize the opportunities of centralized administration of today’s emerging mobile network. Our proposed architecture would not depend on a single controller, rather it divides the whole cellular area into clusters, and each cluster is controlled by a separate controller. A number of controller services are provided on top of each controller to manage all the major functionalities of the...

  19. Scalable Cluster-based Routing in Large Wireless Sensor Networks


    Jiandong Li; Xuelian Cai; Jin Yang; Lina Zhu


    Large control overhead is the leading factor limiting the scalability of wireless sensor networks (WSNs). Clustering network nodes is an efficient solution, and Passive Clustering (PC) is one of the most efficient clustering methods. In this letter, we propose an improved PC-based route building scheme, named Route Reply (RREP) Broadcast with Passive Clustering (in short RBPC). Through broadcasting RREP packets on an expanding ring to build route, sensor nodes cache their route to the sink no...

  20. A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks. (United States)

    Wang, Hao; Wang, Shilian; Bu, Renfei; Zhang, Eryang


    Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs.

  1. Data Dissemination Based on Fuzzy Logic and Network Coding in Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Xiaolan Tang


    Full Text Available Vehicular networks, as a significant technology in intelligent transportation systems, improve the convenience, efficiency, and safety of driving in smart cities. However, because of the high velocity, the frequent topology change, and the limited bandwidth, it is difficult to efficiently propagate data in vehicular networks. This paper proposes a data dissemination scheme based on fuzzy logic and network coding for vehicular networks, named SFN. It uses fuzzy logic to compute a transmission ability for each vehicle by comprehensively considering the effects of three factors: the velocity change rate, the velocity optimization degree, and the channel quality. Then, two nodes with high abilities are selected as primary backbone and slave backbone in every road segment, which propagate data to other vehicles in this segment and forward them to the backbones in the next segment. The backbone network helps to increase the delivery ratio and avoid invalid transmissions. Additionally, network coding is utilized to reduce transmission overhead and accelerate data retransmission in interbackbone forwarding and intrasegment broadcasting. Experiments show that, compared with existing schemes, SFN has a high delivery ratio and a short dissemination delay, while the backbone network keeps high reliability.

  2. A network security situation prediction model based on wavelet neural network with optimized parameters

    Directory of Open Access Journals (Sweden)

    Haibo Zhang


    Full Text Available The security incidents ion networks are sudden and uncertain, it is very hard to precisely predict the network security situation by traditional methods. In order to improve the prediction accuracy of the network security situation, we build a network security situation prediction model based on Wavelet Neural Network (WNN with optimized parameters by the Improved Niche Genetic Algorithm (INGA. The proposed model adopts WNN which has strong nonlinear ability and fault-tolerance performance. Also, the parameters for WNN are optimized through the adaptive genetic algorithm (GA so that WNN searches more effectively. Considering the problem that the adaptive GA converges slowly and easily turns to the premature problem, we introduce a novel niche technology with a dynamic fuzzy clustering and elimination mechanism to solve the premature convergence of the GA. Our final simulation results show that the proposed INGA-WNN prediction model is more reliable and effective, and it achieves faster convergence-speed and higher prediction accuracy than the Genetic Algorithm-Wavelet Neural Network (GA-WNN, Genetic Algorithm-Back Propagation Neural Network (GA-BPNN and WNN.

  3. Real time network traffic monitoring for wireless local area networks based on compressed sensing (United States)

    Balouchestani, Mohammadreza


    A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

  4. High-performance hydrogen production and oxidation electrodes with hydrogenase supported on metallic single-wall carbon nanotube networks. (United States)

    Svedružić, Draženka; Blackburn, Jeffrey L; Tenent, Robert C; Rocha, John-David R; Vinzant, Todd B; Heben, Michael J; King, Paul W


    We studied the electrocatalytic activity of an [FeFe]-hydrogenase from Clostridium acetobutylicum (CaH2ase) immobilized on single-wall carbon nanotube (SWNT) networks. SWNT networks were prepared on carbon cloth by ultrasonic spraying of suspensions with predetermined ratios of metallic and semiconducting nanotubes. Current densities for both proton reduction and hydrogen oxidation electrocatalytic activities were at least 1 order of magnitude higher when hydrogenase was immobilized onto SWNT networks with high metallic tube (m-SWNT) content in comparison to hydrogenase supported on networks with low metallic tube content or when SWNTs were absent. We conclude that the increase in electrocatalytic activities in the presence of SWNTs was mainly due to the m-SWNT fraction and can be attributed to (i) substantial increases in the active electrode surface area, and (ii) improved electronic coupling between CaH2ase redox-active sites and the electrode surface.

  5. Cloud-Centric and Logically Isolated Virtual Network Environment Based on Software-Defined Wide Area Network

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim


    Full Text Available Recent development of distributed cloud environments requires advanced network infrastructure in order to facilitate network automation, virtualization, high performance data transfer, and secured access of end-to-end resources across regional boundaries. In order to meet these innovative cloud networking requirements, software-defined wide area network (SD-WAN is primarily demanded to converge distributed cloud resources (e.g., virtual machines (VMs in a programmable and intelligent manner over distant networks. Therefore, this paper proposes a logically isolated networking scheme designed to integrate distributed cloud resources to dynamic and on-demand virtual networking over SD-WAN. The performance evaluation and experimental results of the proposed scheme indicate that virtual network convergence time is minimized in two different network models such as: (1 an operating OpenFlow-oriented SD-WAN infrastructure (KREONET-S which is deployed on the advanced national research network in Korea, and (2 Mininet-based experimental and emulated networks.

  6. Fibroblast-Cytophilic and HeLa-Cytotoxic Dual Function Carbon Nanoribbon Network Platform. (United States)

    Chowdhury, A K M Rezaul Haque; Tan, Bo; Venkatakrishnan, Krishnan


    Carbon nanomaterials have emerged as a promising material in cancer diagnosis and therapy. Carbon nanomaterials/nanostructures (C-C molecular structure) act as a carrier/skeleton and require further surface modification through functionalization with chemicals or biomolecules to attain cell response. We report the synthesis of a novel carbon nanoribbon network (CNRN) platform that possesses a combination of C-C and C-O bond architecture. The bioactive CNRN showed enhanced ability for cell adhesion. Most importantly, it induced opposite cell responses from healthy cells and cancerous cells, cytophilic to fibroblasts but cytotoxic to HeLa cells. Ultrafast laser ionization under ambient conditions transforms nonbioresponsive C-C bond of graphite to C-C and C-O bonds, forming a self-assembled CNRN platform. The morphology, nanochemistry, and functionality on modulating fibroblast and HeLa adhesion and proliferation of the fabricated CNRN platforms were investigated. The results of in vitro studies suggested that the CNRN platforms not only attracted but also actively accelerated the adhesion and proliferation of both fibroblasts and HeLa cells. The proliferation rate of fibroblasts and HeLa cells is 91 and 98 times greater compared with that of a native graphite substrate, respectively. The morphology of the cells over a period of 24 to 48 h revealed that the CNRN platform induced an apoptosis-like cytotoxic function on HeLa cells, whereas fibroblasts experienced a cytophilic effect and formed a tissuelike structure. The degree of cytotoxic or cytophilic effect can be further enhanced by adjusting parameters such as the ratio of C-C bonds to C-O bonds, the nanoribbon width, and the nanovoid porosity of the CNRN platforms, which could be tuned by careful control of laser ionization. In a nutshell, for the first time, pristine carbon nanostructures free from biochemical functionalization demonstrate dual function, cytophilic to fibroblast cells and cytotoxic to He

  7. Emissions of carbon dioxide and methane from a headwater stream network of interior Alaska (United States)

    Crawford, John T.; Striegl, Robert G.; Wickland, Kimberly P.; Dornblaser, Mark M.; Stanley, Emily H.


    Boreal ecosystems store significant quantities of organic carbon (C) that may be vulnerable to degradation as a result of a warming climate. Despite their limited coverage on the landscape, streams play a significant role in the processing, gaseous emission, and downstream export of C, and small streams are thought to be particularly important because of their close connection with the surrounding landscape. However, ecosystem carbon studies do not commonly incorporate the role of the aquatic conduit. We measured carbon dioxide (CO2) and methane (CH4) concentrations and emissions in a headwater stream network of interior Alaska underlain by permafrost to assess the potential role of stream gas emissions in the regional carbon balance. First-order streams exhibited the greatest variability in fluxes of CO2 and CH4,and the greatest mean pCO2. High-resolution time series of stream pCO2 and discharge at two locations on one first-order stream showed opposing pCO2 responses to storm events, indicating the importance of hydrologic flowpaths connecting CO2-rich soils with surface waters. Repeated longitudinal surveys on the stream showed consistent areas of elevated pCO2 and pCH4, indicative of discrete hydrologic flowpaths delivering soil water and groundwater having varying chemistry. Up-scaled basin estimates of stream gas emissions suggest that streams may contribute significantly to catchment-wide CH4 emissions. Overall, our results indicate that while stream-specific gas emission rates are disproportionately high relative to the terrestrial landscape, both stream surface area and catchment normalized emission rates were lower than those documented for the Yukon River Basin as a whole. This may be due to limitations of C sources and/or C transport to surface waters.

  8. Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks (United States)

    Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios


    Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate. PMID:25658394

  9. Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid


    Full Text Available Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs. Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS and Congestion adjusted PEGASIS (C-PEGASIS. Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate.

  10. Chain-based communication in cylindrical underwater wireless sensor networks. (United States)

    Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios


    Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate.

  11. On effectiveness of network sensor-based defense framework (United States)

    Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh


    Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

  12. Social-based autonomic routing in opportunistic networks (United States)

    Boldrini, Chiara; Conti, Marco; Passarella, Andrea

    In opportunistic networks end-to-end communication between users does not require a continuous end-to-end path between source and destination. Network protocols are designed to be extremely resilient to events such as long partitions, node disconnections, etc, which are very features of this type of self-organizing ad hoc networks. This is achieved by temporarily storing messages at intermediate nodes, waiting for future opportunities to forward them towards the destination. The mobility of users plays a key role in opportunistic networks. Thus, providing accurate models of mobility patterns is one of the key research areas. In this chapter we firstly focus on this issue, with special emphasis on a class of social-aware models. These models are based on the observation that people move because they are attracted towards other people they have social relationships with, or towards physical places that have special meaning with respect to their social behavior. Another key research area in opportunistic networks is clearly designing routing and forwarding schemes. In this chapter we provide a survey of the main approaches to routing in purely infrastructure-less opportunistic networks, by classifying protocols based on the amount of context information they exploit.We then provide an extensive quantitative comparison between representatives of protocols that do not use any context information, and protocols that manage and exploit a rich set of context information. We mainly focus on the suitability of protocols to adapt to the dynamically changing network features, as resulting from the user movement patterns that are driven by their social behavior. Our results show that context-aware routing is extremely adaptive to dynamic networking scenarios, and, with respect to protocols that do not use any context information, is able to provide similar performance in terms of delay and loss rate, by using just a small fraction of the network resources.

  13. Implementation of neural network based non-linear predictive

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole


    The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....

  14. Agent-Based Simulation Analysis for Network Formation


    神原, 李佳; 林田, 智弘; 西﨑, 一郎; 片桐, 英樹


    In the mathematical models for network formation by Bala and Goyal(2000), it is shown that a star network is the strict Nash equilibrium. However, the result of the experiments in a laboratory using human subjects by Berninghaus et al.(2007) basing on the model of Bala and Goyal indicates that players reach a strict Nash equilibrium and deviate it. In this paper, an agent-based simulation model in which artificial adaptive agents have mechanisms of decision making and learning based on nueral...

  15. Restoration in multi-domain GMPLS-based networks

    DEFF Research Database (Denmark)

    Manolova, Anna; Ruepp, Sarah Renée; Dittmann, Lars


    In this paper, we evaluate the efficiency of using restoration mechanisms in a dynamic multi-domain GMPLS network. Major challenges and solutions are introduced and two well-known restoration schemes (End-to-End and Local-to-End) are evaluated. Additionally, new restoration mechanisms...... are introduced: one based on the position of a failed link, called Location-Based, and another based on minimizing the additional resources consumed during restoration, called Shortest-New. A complete set of simulations in different network scenarios show where each mechanism is more efficient in terms, such as...


    Directory of Open Access Journals (Sweden)

    Parisa Bazmi


    Full Text Available Named Data Networking (NDN is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN Based Traffic-aware Forwarding strategy (NNTF is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.

  17. Network interventions on physical activity in an afterschool program: an agent-based social network study. (United States)

    Zhang, Jun; Shoham, David A; Tesdahl, Eric; Gesell, Sabina B


    We studied simulated interventions that leveraged social networks to increase physical activity in children. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children's physical activity. We tested 3 intervention strategies. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children's physical activity.

  18. Reconstruction of social group networks from friendship networks using a tag-based model (United States)

    Guan, Yuan-Pan; You, Zhi-Qiang; Han, Xiao-Pu


    Social group is a type of mesoscopic structure that connects human individuals in microscopic level and the global structure of society. In this paper, we propose a tag-based model considering that social groups expand along the edge that connects two neighbors with a similar tag of interest. The model runs on a real-world friendship network, and its simulation results show that various properties of simulated group network can well fit the empirical analysis on real-world social groups, indicating that the model catches the major mechanism driving the evolution of social groups and successfully reconstructs the social group network from a friendship network and throws light on digging of relationships between social functional organizations.

  19. Dynamics of riverine CO2 in the Yangtze River fluvial network and their implications for carbon evasion (United States)

    Ran, Lishan; Lu, Xi Xi; Liu, Shaoda


    Understanding riverine carbon dynamics is critical for not only better estimates of various carbon fluxes but also evaluating their significance in the global carbon budget. As an important pathway of global land-ocean carbon exchange, the Yangtze River has received less attention regarding its vertical carbon evasion compared with lateral transport. Using long-term water chemistry data, we calculated CO2 partial pressure (pCO2) from pH and alkalinity and examined its spatial and temporal dynamics and the impacts of environmental settings. With alkalinity ranging from 415 to > 3400 µeq L-1, the river waters were supersaturated with dissolved CO2, generally 2-20-fold the atmospheric equilibrium (i.e., 390 µatm). Changes in pCO2 were collectively controlled by carbon inputs from terrestrial ecosystems, hydrological regime, and rock weathering. High pCO2 values were observed spatially in catchments with abundant carbonate presence and seasonally in the wet season when recently fixed organic matter was exported into the river network. In-stream processing of organic matter facilitated CO2 production and sustained the high pCO2, although the alkalinity presented an apparent dilution effect with water discharge. The decreasing pCO2 from the smallest headwater streams through tributaries to the mainstem channel illustrates the significance of direct terrestrial carbon inputs in controlling riverine CO2. With a basin-wide mean pCO2 of 2662 ± 1240 µatm, substantial CO2 evasion from the Yangtze River fluvial network is expected. Future research efforts are needed to quantify the amount of CO2 evasion and assess its biogeochemical implications for watershed-scale carbon cycle. In view of the Yangtze River's relative importance in global carbon export, its CO2 evasion would be significant for global carbon budget.

  20. Constraining future terrestrial carbon cycle projections using observation-based water and carbon flux estimates. (United States)

    Mystakidis, Stefanos; Davin, Edouard L; Gruber, Nicolas; Seneviratne, Sonia I


    The terrestrial biosphere is currently acting as a sink for about a third of the total anthropogenic CO2  emissions. However, the future fate of this sink in the coming decades is very uncertain, as current earth system models (ESMs) simulate diverging responses of the terrestrial carbon cycle to upcoming climate change. Here, we use observation-based constraints of water and carbon fluxes to reduce uncertainties in the projected terrestrial carbon cycle response derived from simulations of ESMs conducted as part of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). We find in the ESMs a clear linear relationship between present-day evapotranspiration (ET) and gross primary productivity (GPP), as well as between these present-day fluxes and projected changes in GPP, thus providing an emergent constraint on projected GPP. Constraining the ESMs based on their ability to simulate present-day ET and GPP leads to a substantial decrease in the projected GPP and to a ca. 50% reduction in the associated model spread in GPP by the end of the century. Given the strong correlation between projected changes in GPP and in NBP in the ESMs, applying the constraints on net biome productivity (NBP) reduces the model spread in the projected land sink by more than 30% by 2100. Moreover, the projected decline in the land sink is at least doubled in the constrained ensembles and the probability that the terrestrial biosphere is turned into a net carbon source by the end of the century is strongly increased. This indicates that the decline in the future land carbon uptake might be stronger than previously thought, which would have important implications for the rate of increase in the atmospheric CO2 concentration and for future climate change. © 2016 John Wiley & Sons Ltd.

  1. Peculiarities of the initial stages of carbonization processes in polyimide-based nanocomposite films containing carbon nanoparticles

    Directory of Open Access Journals (Sweden)

    I.V. Gofman


    Full Text Available Carbonization of the polyimide-based composite films containing carbon nanoparticles, namely nanofibers and nanocones/disks, in the temperature range 500–550°C was studied and the kinetics of the initial stage of carbonization and the effect of the filler on the mechanical properties of the carbonized films were evaluated. Two polyimides (PIs characterized by different macrochains’ rigidity and different degrees of ordering of the intermolecular structure were used. The character of the nanofiller’s action on the kinetics of the carbonization process depends on the heating rate. In this work, the intensity of the destruction of the PI matrix of the composite films was shown to be slightly higher than that of films of the same polymers with no filler. The introduction of the carbon nanoparticles into both PIs provokes the increase in the ultimate deformation values of the partially carbonized films, while the carbonization of the unfilled PI films yields the brittle materials. The Young’s modulus values of the materials based on the rigid-rod PI do not increase after carbonization, while those for compositions based on the PI with semi-rigid chains increase substantially. Carbon nanocones/disks are characterized by the best compatibility with matrix PIs in comparison with carbon nanofibers.

  2. IPTV inter-destination synchronization: A network-based approach

    NARCIS (Netherlands)

    Stokking, H.M.; Deventer, M.O. van; Niamut, O.A.; Walraven, F.A.; Mekuria, R.N.


    This paper introduces a novel network-based approach to inter-destination media synchronization. The approach meets the need for synchronization in advanced TV concepts like social TV and offers high scalability, unlike conventional end-point based approaches. The solution for interdestination media

  3. Approaches in Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro

    Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

  4. Decoding signalling networks by mass spectrometry-based proteomics

    DEFF Research Database (Denmark)

    Choudhary, Chuna Ram; Mann, Matthias


    Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system...

  5. Toxicity induced enhanced extracellular matrix production in osteoblastic cells cultured on single-walled carbon nanotube networks

    Energy Technology Data Exchange (ETDEWEB)

    Tutak, Wojtek; Fanchini, Giovanni; Chhowalla, Manish [Materials Science and Engineering, School of Engineering, Rutgers, State University of New Jersey, Piscataway, NJ 08854 (United States); Park, Ki Ho; Vasilov, Anatoly; Cai Shiqing; Partridge, Nicola C; Sesti, Federico [Department of Physiology and Biophysics, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, NJ 08854 (United States); Starovoytov, Valentin [Department of Cell Biology and Neuroscience, Rutgers, State University of New Jersey, Piscataway, NJ 08855 (United States)], E-mail:, E-mail:


    A central effort in biomedical research concerns the development of materials for sustaining and controlling cell growth. Carbon nanotube based substrates have been shown to support the growth of different kinds of cells (Hu et al 2004 Nano Lett. 4 507-11; Kalbacova et al 2006 Phys. Status Solidi b 13 243; Zanello et al 2006 Nano Lett. 6 562-7); however the underlying molecular mechanisms remain poorly defined. To address the fundamental question of mechanisms by which nanotubes promote bone mitosis and histogenesis, primary calvariae osteoblastic cells were grown on single-walled carbon nanotube thin film (SWNT) substrates. Using a combination of biochemical and optical techniques we demonstrate here that SWNT networks promote cell development through two distinct steps. Initially, SWNTs are absorbed in a process that resembles endocytosis, inducing acute toxicity. Nanotube-mediated cell destruction, however, induces a release of endogenous factors that act to boost the activity of the surviving cells by stimulating the synthesis of extracellular matrix.

  6. A dense Black Carbon network in the region of Paris, France: Implementation, objectives, and first results (United States)

    Sciare, Jean; Petit, Jean-Eudes; Sarda-Esteve, Roland; Bonnaire, Nicolas; Gros, Valérie; Pernot, Pierre; Ghersi, Véronique; Ampe, Christophe; Songeur, Charlotte; Brugge, Benjamin; Debert, Christophe; Favez, Olivier; Le Priol, Tiphaine; Mocnik, Grisa


    Motivations. Road traffic and domestic wood burning emissions are two major contributors of particulate pollution in our cities. These two sources emit ultra-fine, soot containing, particles in the atmosphere, affecting health adversely, increasing morbidity and mortality from cardiovascular and respiratory conditions and casing lung cancer. A better characterization of soot containing aerosol sources in our major cities provides useful information for policy makers for assessment, implementation and monitoring of strategies to tackle air pollution issues affecting human health with additional benefits for climate change. Objectives. This study on local sources of primary Particulate Matter (PM) in the megacity of Paris is a follow-up of several programs (incl. EU-FP7-MEGAPOLI) that have shown that fine PM - in the Paris background atmosphere - is mostly secondary and imported. A network of 14 stations of Black Carbon has been implemented in the larger region of Paris to provide highly spatially resolved long term survey of local combustion aerosols. To our best knowledge, this is the first time that such densely BC network is operating over a large urban area, providing novel information on the spatial/temporal distribution of combustion aerosols within a post-industrialized megacity. Experimental. As part of the PRIMEQUAL "PREQUALIF" project, a dense Black Carbon network (of 14 stations) has been installed over the city of Paris beginning of 2012 in order to produce spatially resolved Equivalent Black Carbon (EBC) concentration maps with high time resolution through modeling and data assimilation. This network is composed of various real-time instruments (Multi-Angle Absorption Photometer, MAAP by THERMO; Multi-wavelength Aethalometers by MAGEE Scientific) implemented in contrasted sites (rural background, urban background, traffic) complementing the regulated measurements (PM, NOx) in the local air quality network AIRPARIF (http

  7. Dynamic QoS Provisioning for Ethernet-based Networks (United States)

    Angelopoulos, J.; Kanonakis, K.; Leligou, H. C.; Orfanoudakis, Th.; Katsigiannis, M.


    The evolution towards packet-based access networks and the importance of quality of experience brings the need for access networks that support the offer of a wide range of multimedia services not currently available to the desired extent. Legacy networks based on circuit switching used explicit signalling that travelled to all nodes along the path to book resources before the launce of the media stream. This approach does not scale well and is not in line with the philosophy of packet networks. Still, the need to reserve resources in advance remains since real-time services have limited if any means of adjusting their rates to the prevailing network conditions and to preserve customer satisfaction the traditional preventive approach that needs accurate estimates of resource needs for the duration of the session is the only option. The paper describes a possible CAC solution based on measuring flows and enriches the network with implicit admission control (without obviating explicit control if available) and can manage resource allocation to protect quality-demanding services from degradation. The basis is a flow measurement system, which will estimate the traffic load produced by the flow and activate admission control. However, because in most cases these initial indication may well be misleading, it will be cross checked against a database of previously recorded flows per customer interface which can provide long term data on the flows leaving only a few cases that have to be corrected on the fly. The overall product is a self-learning autonomic system that supports QoS in the access network for services that do not communicate with the network layer such as, for example, peer-to-peer real-time multimedia applications.

  8. Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns (United States)

    del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro


    Stable isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes), and (2) deriving precipitation maps from 13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally-dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex orography and climate (MAP=303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N=38; Quercus ilex L.; N=44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one 13C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding 13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE=84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE=80-83 mm, N=65), being only outperformed when using a much denser meteorological network (RMSE=56-57 mm, N=340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively.

  9. Optimized Carbonate and Ester-Based Li-Ion Electrolytes (United States)

    Smart, Marshall; Bugga, Ratnakumar


    To maintain high conductivity in low temperatures, electrolyte co-solvents have been designed to have a high dielectric constant, low viscosity, adequate coordination behavior, and appropriate liquid ranges and salt solubilities. Electrolytes that contain ester-based co-solvents in large proportion (greater than 50 percent) and ethylene carbonate (EC) in small proportion (less than 20 percent) improve low-temperature performance in MCMB carbon-LiNiCoO2 lithium-ion cells. These co-solvents have been demonstrated to enhance performance, especially at temperatures down to 70 C. Low-viscosity, ester-based co-solvents were incorporated into multi-component electrolytes of the following composition: 1.0 M LiPF6 in ethylene carbonate (EC) + ethyl methyl carbonate (EMC) + X (1:1:8 volume percent) [where X = methyl butyrate (MB), ethyl butyrate EB, methyl propionate (MP), or ethyl valerate (EV)]. These electrolyte formulations result in improved low-temperature performance of lithium-ion cells, with dramatic results at temperatures below 40 C.

  10. Paper-based ultracapacitors with carbon nanotubes-graphene composites

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jian, E-mail:, E-mail:; Cheng, Xiaoqian; Brand, Cameron; Shashurin, Alexey; Keidar, Michael, E-mail:, E-mail: [Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, DC 20052 (United States); Sun, Jianwei; Reeves, Mark [Department of Physics, The George Washington University, Washington, DC 20052 (United States)


    In this paper, a paper-based ultracapacitors were fabricated by the rod-rolling method with the ink of carbon nanomaterials, which were synthesized by arc discharge under various magnetic conditions. Composites of carbon nanostructures, including high-purity single-walled carbon nanotubes (SWCNTs) and graphene flakes were synthesized simultaneously in a magnetically enhanced arc. These two nanostructures have promising electrical properties and synergistic effects in the application of ultracapacitors. Scanning electron microscope, transmission electron microscope, and Raman spectroscopy were employed to characterize the properties of carbon nanostructures and their thin films. The sheet resistance of the SWCNT and composite thin films was also evaluated by four-point probe from room temperature to the cryogenic temperature as low as 90 K. In addition, measurements of cyclic voltammetery and galvanostatic charging/discharging showed the ultracapacitor based on composites possessed a superior specific capacitance of up to 100 F/g, which is around three times higher than the ultracapacitor entirely fabricated with SWCNT.

  11. Subgradient-based neural networks for nonsmooth nonconvex optimization problems. (United States)

    Bian, Wei; Xue, Xiaoping


    This paper presents a subgradient-based neural network to solve a nonsmooth nonconvex optimization problem with a nonsmooth nonconvex objective function, a class of affine equality constraints, and a class of nonsmooth convex inequality constraints. The proposed neural network is modeled with a differential inclusion. Under a suitable assumption on the constraint set and a proper assumption on the objective function, it is proved that for a sufficiently large penalty parameter, there exists a unique global solution to the neural network and the trajectory of the network can reach the feasible region in finite time and stay there thereafter. It is proved that the trajectory of the neural network converges to the set which consists of the equilibrium points of the neural network, and coincides with the set which consists of the critical points of the objective function in the feasible region. A condition is given to ensure the convergence to the equilibrium point set in finite time. Moreover, under suitable assumptions, the coincidence between the solution to the differential inclusion and the "slow solution" of it is also proved. Furthermore, three typical examples are given to present the effectiveness of the theoretic results obtained in this paper and the good performance of the proposed neural network.

  12. Traffic sign recognition based on deep convolutional neural network (United States)

    Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan


    Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.


    Directory of Open Access Journals (Sweden)



    Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

  14. Hydrogen based global renewable energy network

    Energy Technology Data Exchange (ETDEWEB)

    Akai, Makoto [Mechanical Engineering Laboratory, AIST, MITI, Namiki, Tsukuba (Japan)


    In the last quarter of this century, global environmental problem has emerged as a major scientific, political and social issue. Specific Problems include: depletion of ozone layer by chlorofluorocarbons (CFCs), acid rain, destruction of tropical forests and desertification, pollution of the sea and global wanning due to the greenhouse effect by carbon dioxide and others. Among these problems, particular attention of the world has been focused on the global warming because it has direct linkage to energy consumption which our economic development depends on so far. On the other hand, the future program of The Sunshine Project for alternative energy technology R&D, The Moonlight Project for energy conservation technology R&D, and The Global Environmental Technology Program for environmental problem mitigating technology R&D which are Japan`s national projects being promoted by their Agency of Industrial Science and Technology (AIST) in the Ministry of International Trade and Industry have been reexamined in view of recent changes in the situations surrounding new energy technology. In this regard, The New Sunshine Program will be established by integrating these three activities to accelerate R&D in the field of energy and environmental technologies. In the reexamination, additional stress has been laid on the contribution to solving global environmental problem through development of clean renewable energies which constitute a major part of the {open_quotes}New Earth 21{close_quotes}, a comprehensive, long-term and international cooperative program proposed by MITI. The present paper discusses the results of feasibility study on hydrogen energy system leading to the concept of WE-NET following a brief summary on R&D status on solar and wind energy in Japan.

  15. Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education (United States)

    Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav


    Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

  16. Risk Based Maintenance in Electricity Network Organisations

    NARCIS (Netherlands)

    Mehairjan, R.P.Y.


    Presently, maintenance management of assets in infrastructure utilities such as electricity, gas and water are widely undergoing changes towards new working environments. These are mainly driven against the background of stringent regulatory regimes, an ageing asset base, increased customer demands

  17. DMA Reference Base Station Network Data (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data (15,904 records documenting 9,090 worldwide gravity base stations) were gathered by various governmental organizations (and academia) using a variety of...

  18. Comparison of Polymer Networks Synthesized by Conventional Free Radical and RAFT Copolymerization Processes in Supercritical Carbon Dioxide

    Directory of Open Access Journals (Sweden)

    Patricia Pérez-Salinas


    Full Text Available There is a debate in the literature on whether or not polymer networks synthesized by reversible deactivation radical polymerization (RDRP processes, such as reversible addition-fragmentation radical transfer (RAFT copolymerization of vinyl/divinyl monomers, are less heterogeneous than those synthesized by conventional free radical copolymerization (FRP. In this contribution, the syntheses by FRP and RAFT of hydrogels based on 2-hydroxyethylene methacrylate (HEMA and ethylene glycol dimethacrylate (EGDMA in supercritical carbon dioxide (scCO2, using Krytox 157 FSL as the dispersing agent, and the properties of the materials produced, are compared. The materials were characterized by differential scanning calorimetry (DSC, swelling index (SI, infrared spectroscopy (FTIR and scanning electron microscopy (SEM. Studies on ciprofloxacin loading and release rate from hydrogels were also carried out. The combined results show that the hydrogels synthesized by FRP and RAFT are significantly different, with apparently less heterogeneity present in the materials synthesized by RAFT copolymerization. A ratio of experimental (Mcexp to theoretical (Mctheo molecular weight between crosslinks was established as a quantitative tool to assess the degree of heterogeneity of a polymer network.

  19. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks

    Directory of Open Access Journals (Sweden)

    Shibo Luo


    Full Text Available Software-Defined Networking-based Mobile Networks (SDN-MNs are considered the future of 5G mobile network architecture. With the evolving cyber-attack threat, security assessments need to be performed in the network management. Due to the distinctive features of SDN-MNs, such as their dynamic nature and complexity, traditional network security assessment methodologies cannot be applied directly to SDN-MNs, and a novel security assessment methodology is needed. In this paper, an effective security assessment mechanism based on attack graphs and an Analytic Hierarchy Process (AHP is proposed for SDN-MNs. Firstly, this paper discusses the security assessment problem of SDN-MNs and proposes a methodology using attack graphs and AHP. Secondly, to address the diversity and complexity of SDN-MNs, a novel attack graph definition and attack graph generation algorithm are proposed. In order to quantify security levels, the Node Minimal Effort (NME is defined to quantify attack cost and derive system security levels based on NME. Thirdly, to calculate the NME of an attack graph that takes the dynamic factors of SDN-MN into consideration, we use AHP integrated with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS as the methodology. Finally, we offer a case study to validate the proposed methodology. The case study and evaluation show the advantages of the proposed security assessment mechanism.

  20. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks. (United States)

    Luo, Shibo; Dong, Mianxiong; Ota, Kaoru; Wu, Jun; Li, Jianhua


    Software-Defined Networking-based Mobile Networks (SDN-MNs) are considered the future of 5G mobile network architecture. With the evolving cyber-attack threat, security assessments need to be performed in the network management. Due to the distinctive features of SDN-MNs, such as their dynamic nature and complexity, traditional network security assessment methodologies cannot be applied directly to SDN-MNs, and a novel security assessment methodology is needed. In this paper, an effective security assessment mechanism based on attack graphs and an Analytic Hierarchy Process (AHP) is proposed for SDN-MNs. Firstly, this paper discusses the security assessment problem of SDN-MNs and proposes a methodology using attack graphs and AHP. Secondly, to address the diversity and complexity of SDN-MNs, a novel attack graph definition and attack graph generation algorithm are proposed. In order to quantify security levels, the Node Minimal Effort (NME) is defined to quantify attack cost and derive system security levels based on NME. Thirdly, to calculate the NME of an attack graph that takes the dynamic factors of SDN-MN into consideration, we use AHP integrated with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) as the methodology. Finally, we offer a case study to validate the proposed methodology. The case study and evaluation show the advantages of the proposed security assessment mechanism.