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Sample records for network properties including

  1. 26 CFR 1.1013-1 - Property included in inventory.

    Science.gov (United States)

    2010-04-01

    ... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Property included in inventory. 1.1013-1 Section... inventory. The basis of property required to be included in inventory is the last inventory value of such property in the hands of the taxpayer. The requirements with respect to the valuation of an inventory are...

  2. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Y W [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Zhang, L F [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Huang, J P [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China)

    2007-07-20

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property.

  3. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    International Nuclear Information System (INIS)

    Chen, Y W; Zhang, L F; Huang, J P

    2007-01-01

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property

  4. System for testing properties of a network

    Science.gov (United States)

    Rawle, Michael; Bartholomew, David B.; Soares, Marshall A.

    2009-06-16

    A method for identifying properties of a downhole electromagnetic network in a downhole tool sting, including the step of providing an electromagnetic path intermediate a first location and a second location on the electromagnetic network. The method further includes the step of providing a receiver at the second location. The receiver includes a known reference. The analog signal includes a set amplitude, a set range of frequencies, and a set rate of change between the frequencies. The method further includes the steps of sending the analog signal, and passively modifying the signal. The analog signal is sent from the first location through the electromagnetic path, and the signal is modified by the properties of the electromagnetic path. The method further includes the step of receiving a modified signal at the second location and comparing the known reference to the modified signal.

  5. Hydraulic properties of fracture networks

    International Nuclear Information System (INIS)

    Dreuzy, J.R. de

    1999-12-01

    Fractured medium are studied in the general framework of oil and water supply and more recently for the underground storage of high level nuclear wastes. As fractures are generally far more permeable than the embedding medium, flow is highly channeled in a complex network of fractures. The complexity of the network comes from the broad distributions of fracture length and permeability at the fracture scale and appears through the increase of the equivalent permeability at the network scale. The goal of this thesis is to develop models of fracture networks consistent with both local-scale and global-scale observations. Bidimensional models of fracture networks display a wide variety of flow structures ranging from the sole permeable fracture to the equivalent homogeneous medium. The type of the relevant structure depends not only on the density and the length and aperture distributions but also on the observation scale. In several models, a crossover scale separates complex structures highly channeled from more distributed and homogeneous-like flow patterns at larger scales. These models, built on local characteristics and validated by global properties, have been settled in steady state. They have also been compared to natural well test data obtained in Ploemeur (Morbihan) in transient state. The good agreement between models and data reinforces the relevance of the models. Once validated and calibrated, the models are used to estimate the global tendencies of the main flow properties and the risk associated with the relative lack of data on natural fractures media. (author)

  6. Directed networks, allocation properties and hierarchy formation

    NARCIS (Netherlands)

    Slikker, M.; Gilles, R.P.; Norde, H.W.; Tijs, S.H.

    2005-01-01

    We investigate properties for allocation rules on directed communication networks and the formation of such networks under these payoff properties. We study allocation rules satisfying two appealing properties, Component Efficiency (CE) and the Hierarchical Payoff Property (HPP). We show that such

  7. Property transfer assessments should include radon gas testing

    International Nuclear Information System (INIS)

    Nardi, M.A.

    1992-01-01

    There are two emerging influences that will require radon gas testing as part of many property transfers and most environmental assessments. These requirements come from lending regulators and state legislatures and affect single family, multifamily, and commercial properties. Fannie Mae and others have developed environmental investigation guidelines for protection from long term legal liabilities in the purchase of environmentally contaminated real estate. These guidelines include radon gas testing for many properties. Several states have enacted laws that require environmental disclosure forms be prepared to ensure that the parties involved in certain real estate transactions are aware of the environmental liabilities that may come with the transfer of property. Indiana has recently enacted legislation that would require the disclosure of the presence of radon gas on many commercial real estate transactions. With more banks and state governments following this trend, radon gas testing should be performed during all property transfers and environmental assessments to protect the parties involved from any long term legal liabilities

  8. The Vulnerability of Some Networks including Cycles via Domination Parameters

    Directory of Open Access Journals (Sweden)

    Tufan Turaci

    2016-01-01

    Full Text Available Let G=(V(G,E(G be an undirected simple connected graph. A network is usually represented by an undirected simple graph where vertices represent processors and edges represent links between processors. Finding the vulnerability values of communication networks modeled by graphs is important for network designers. The vulnerability value of a communication network shows the resistance of the network after the disruption of some centers or connection lines until a communication breakdown. The domination number and its variations are the most important vulnerability parameters for network vulnerability. Some variations of domination numbers are the 2-domination number, the bondage number, the reinforcement number, the average lower domination number, the average lower 2-domination number, and so forth. In this paper, we study the vulnerability of cycles and related graphs, namely, fans, k-pyramids, and n-gon books, via domination parameters. Then, exact solutions of the domination parameters are obtained for the above-mentioned graphs.

  9. Connecting Network Properties of Rapidly Disseminating Epizoonotics

    Science.gov (United States)

    Rivas, Ariel L.; Fasina, Folorunso O.; Hoogesteyn, Almira L.; Konah, Steven N.; Febles, José L.; Perkins, Douglas J.; Hyman, James M.; Fair, Jeanne M.; Hittner, James B.; Smith, Steven D.

    2012-01-01

    Background To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure. Methods Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) ‘connectivity’, a model that integrated bio-physical concepts (the agent’s transmission cycle, road topology) into indicators designed to measure networks (‘nodes’ or infected sites with short- and long-range links), and 2) ‘contacts’, which focused on infected individuals but did not assess connectivity. Results The connectivity model showed five network properties: 1) spatial aggregation of cases (disease clusters), 2) links among similar ‘nodes’ (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a “20∶80″ pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads. Conclusions Geo-temporal constructs of Network Theory’s nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished

  10. PROPERTIES AND MICROSTRUCTURE OF CEMENT PASTE INCLUDING RECYCLED CONCRETE POWDER

    Directory of Open Access Journals (Sweden)

    Jaroslav Topič

    2017-02-01

    Full Text Available The disposal and further recycling of concrete is being investigated worldwide, because the issue of complete recycling has not yet been fully resolved. A fundamental difficulty faced by researchers is the reuse of the recycled concrete fines which are very small (< 1 mm. Currently, full recycling of such waste fine fractions is highly energy intensive and resulting in production of CO2. Because of this, the only recycling methods that can be considered as sustainable and environmentally friendly are those which involve recycled concrete powder (RCP in its raw form. This article investigates the performance of RCP with the grain size < 0.25 mm as a potential binder replacement, and also as a microfiller in cement-based composites. Here, the RCP properties are assessed, including how mechanical properties and the microstructure are influenced by increasing the amount of the RCP in a cement paste (≤ 25 wt%.

  11. Terrorism cover in France for property damage including nuclear risks

    International Nuclear Information System (INIS)

    Stanislas, A.

    2004-01-01

    The obligation to include terrorism cover in all Property Damage policies issued on the French Market is ruled by an Act of 1986 and introduced under Section R 126-2 of the French Code of Insurance. This section stipulates that Property Damage policies must provide cover for damage resulting from acts of terrorism, with the same deductible and the same limit than that of the other damage covered in the policy. Soon after the dramatic events of September 11, 2001 in the United States and although reinsurers worldwide restricted their offer of capacities, French insurers recognized that they had to maintain this global cover for the benefit of their insurers. After difficult discussions between insurers, reinsurers, brokers, risk managers and representatives of the State, the creation of a new Pool, backed with a State guarantee, was decided in less than three months. Effective January 1, 2002 and called Gestion d'Assurance et de Reassurance des Risques Attentats et Actes de Terrorisme (GAREAT), the Pool offers a multiple layers stop-loss cover for Property Damage only, i.e. excluding TPL policies. Considering that nuclear risks should be treated in the same way as other industrial risks, it was decided that they would be covered by GAREAT as well. In the meantime, by a Decree of December 28, 2001 modifying Section R 126-2, a special provision, aiming at reducing the limit and thus the price of this cover, was introduced in the Code. The purpose of this paper is to expose the present situation applying through GAREAT and, after two years of operation to discuss future developments, including other sources of capacity for the coverage of acts of terrorism in nuclear risks insurance.(author)

  12. Thermoelectric properties of semiconductor nanowire networks

    Science.gov (United States)

    Roslyak, Oleksiy; Piryatinski, Andrei

    2016-03-01

    To examine the thermoelectric (TE) properties of a semiconductor nanowire (NW) network, we propose a theoretical approach mapping the TE network on a two-port network. In contrast to a conventional single-port (i.e., resistor) network model, our model allows for large scale calculations showing convergence of TE figure of merit, ZT, with an increasing number of junctions. Using this model, numerical simulations are performed for the Bi2Te3 branched nanowire (BNW) and Cayley tree NW (CTNW) network. We find that the phonon scattering at the network junctions plays a dominant role in enhancing the network ZT. Specifically, disordered BNW and CTNW demonstrate an order of magnitude higher ZT enhancement compared to their ordered counterparts. Formation of preferential TE pathways in CTNW makes the network effectively behave as its BNW counterpart. We provide formalism for simulating large scale nanowire networks hinged upon experimentally measurable TE parameters of a single T-junction.

  13. Statistical properties of random clique networks

    Science.gov (United States)

    Ding, Yi-Min; Meng, Jun; Fan, Jing-Fang; Ye, Fang-Fu; Chen, Xiao-Song

    2017-10-01

    In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

  14. Universal properties of mythological networks

    Science.gov (United States)

    Mac Carron, Pádraig; Kenna, Ralph

    2012-07-01

    As in statistical physics, the concept of universality plays an important, albeit qualitative, role in the field of comparative mythology. Here we apply statistical mechanical tools to analyse the networks underlying three iconic mythological narratives with a view to identifying common and distinguishing quantitative features. Of the three narratives, an Anglo-Saxon and a Greek text are mostly believed by antiquarians to be partly historically based while the third, an Irish epic, is often considered to be fictional. Here we use network analysis in an attempt to discriminate real from imaginary social networks and place mythological narratives on the spectrum between them. This suggests that the perceived artificiality of the Irish narrative can be traced back to anomalous features associated with six characters. Speculating that these are amalgams of several entities or proxies, renders the plausibility of the Irish text comparable to the others from a network-theoretic point of view.

  15. Weighted Scale-Free Network Properties of Ecological Network

    International Nuclear Information System (INIS)

    Lee, Jae Woo; Maeng, Seong Eun

    2013-01-01

    We investigate the scale-free network properties of the bipartite ecological network, in particular, the plant-pollinator network. In plant-pollinator network, the pollinators visit the plant to get the nectars. In contrast to the other complex network, the plant-pollinator network has not only the trophic relationships among the interacting partners but also the complexities of the coevolutionary effects. The interactions between the plant and pollinators are beneficial relations. The plant-pollinator network is a bipartite and weighted network. The networks have two types of the nodes: plant and pollinator. We consider the visiting frequency of a pollinator to a plant as the weighting value of the link. We defined the strength of a node as the sum of the weighting value of the links. We reported the cumulative distribution function (CDF) of the degree and the strength of the plant-pollinator network. The CDF of the plants followed stretched exponential functions for both degree and strength, but the CDF of the pollinators showed the power law for both degree and strength. The average strength of the links showed the nonlinear dependence on the degree of the networks.

  16. Network optimization including gas lift and network parameters under subsurface uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Schulze-Riegert, R.; Baffoe, J.; Pajonk, O. [SPT Group GmbH, Hamburg (Germany); Badalov, H.; Huseynov, S. [Technische Univ. Clausthal, Clausthal-Zellerfeld (Germany). ITE; Trick, M. [SPT Group, Calgary, AB (Canada)

    2013-08-01

    Optimization of oil and gas field production systems poses a great challenge to field development due to complex and multiple interactions between various operational design parameters and subsurface uncertainties. Conventional analytical methods are capable of finding local optima based on single deterministic models. They are less applicable for efficiently generating alternative design scenarios in a multi-objective context. Practical implementations of robust optimization workflows integrate the evaluation of alternative design scenarios and multiple realizations of subsurface uncertainty descriptions. Production or economic performance indicators such as NPV (Net Present Value) are linked to a risk-weighted objective function definition to guide the optimization processes. This work focuses on an integrated workflow using a reservoir-network simulator coupled to an optimization framework. The work will investigate the impact of design parameters while considering the physics of the reservoir, wells, and surface facilities. Subsurface uncertainties are described by well parameters such as inflow performance. Experimental design methods are used to investigate parameter sensitivities and interactions. Optimization methods are used to find optimal design parameter combinations which improve key performance indicators of the production network system. The proposed workflow will be applied to a representative oil reservoir coupled to a network which is modelled by an integrated reservoir-network simulator. Gas-lift will be included as an explicit measure to improve production. An objective function will be formulated for the net present value of the integrated system including production revenue and facility costs. Facility and gas lift design parameters are tuned to maximize NPV. Well inflow performance uncertainties are introduced with an impact on gas lift performance. Resulting variances on NPV are identified as a risk measure for the optimized system design. A

  17. Droplet networks with incorporated protein diodes show collective properties

    Science.gov (United States)

    Maglia, Giovanni; Heron, Andrew J.; Hwang, William L.; Holden, Matthew A.; Mikhailova, Ellina; Li, Qiuhong; Cheley, Stephen; Bayley, Hagan

    2009-07-01

    Recently, we demonstrated that submicrolitre aqueous droplets submerged in an apolar liquid containing lipid can be tightly connected by means of lipid bilayers to form networks. Droplet interface bilayers have been used for rapid screening of membrane proteins and to form asymmetric bilayers with which to examine the fundamental properties of channels and pores. Networks, meanwhile, have been used to form microscale batteries and to detect light. Here, we develop an engineered protein pore with diode-like properties that can be incorporated into droplet interface bilayers in droplet networks to form devices with electrical properties including those of a current limiter, a half-wave rectifier and a full-wave rectifier. The droplet approach, which uses unsophisticated components (oil, lipid, salt water and a simple pore), can therefore be used to create multidroplet networks with collective properties that cannot be produced by droplet pairs.

  18. Properties of a memory network in psychology

    Science.gov (United States)

    Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.

    2007-12-01

    We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.

  19. Properties of a memory network in psychology

    International Nuclear Information System (INIS)

    Wedemann, Roseli S.; Donangelo, Raul; Carvalho, Luis A. V. de

    2007-01-01

    We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory

  20. Magnetic properties of nickel halide hydrates including deuteration effects

    Energy Technology Data Exchange (ETDEWEB)

    DeFotis, G.C., E-mail: gxdefo@wm.edu [Chemistry Department, College of William & Mary, Williamsburg, VA, 23187 United States (United States); Van Dongen, M.J.; Hampton, A.S.; Komatsu, C.H.; Trowell, K.T.; Havas, K.C.; Davis, C.M.; DeSanto, C.L. [Chemistry Department, College of William & Mary, Williamsburg, VA, 23187 United States (United States); Hays, K.; Wagner, M.J. [Chemistry Department, George Washington University, Washington, DC, 20052 United States (United States)

    2017-01-01

    Magnetic measurements on variously hydrated nickel chlorides and bromides, including deuterated forms, are reported. Results include locations and sizes of susceptibility maxima, T{sub max} and χ{sub max}, ordering temperatures T{sub c}, Curie constants and Weiss theta in the paramagnetic regime, and primary and secondary exchange interactions from analysis of low temperature data. For the latter a 2D Heisenberg model augmented by interlayer exchange in a mean-field approximation is applied. Magnetization data to 16 kG as a function of temperature show curvature and hysteresis characteristics quite system dependent. For four materials high field magnetization data to 70 kG at 2.00 K are also obtained. Comparison is made with theoretical relations for spin-1 models. Trends are apparent, primarily that T{sub max} of each bromide hydrate is less than for the corresponding chloride, and that for a given halide nD{sub 2}O (n=1 or 2) deuterates exhibit lesser T{sub max} than do nH{sub 2}O hydrates. A monoclinic unit cell determined from powder X-ray diffraction data on NiBr{sub 2}·2D{sub 2}O is different from and slightly larger than that of NiBr{sub 2}·2H{sub 2}O. This provides some rationale for the difference in magnetic properties between these. - Highlights: • The magnetism of Ni(II) chloride and bromide dihydrates and monohydrates is studied. • Effects of replacing H{sub 2}O by D{sub 2}O are examined for both hydration states and both halides. • Exchange interactions in bromides are weaker than in corresponding chlorides. • Exchange interactions are weaker in D{sub 2}O than in corresponding H{sub 2}O containing systems. • The unit cell of NiBr{sub 2}·2D{sub 2}O is different from and slightly larger than that of NiBr{sub 2}·2H{sub 2}O.

  1. On topological properties of sierpinski networks

    International Nuclear Information System (INIS)

    Imran, Muhammad; Sabeel-e-Hafi; Gao, Wei; Reza Farahani, Mohammad

    2017-01-01

    Sierpinski graphs constitute an extensively studied class of graphs of fractal nature applicable in topology, mathematics of Tower of Hanoi, computer science, and elsewhere. A large number of properties like physico-chemical properties, thermodynamic properties, chemical activity, biological activity, etc. are determined by the chemical applications of graph theory. These properties can be characterized by certain graph invariants referred to as topological indices. In QRAR/QSPR study these graph invariants has played a vital role. In this paper, we study the molecular topological properties of Sierpinski networks and derive the analytical closed formulas for the atom-bond connectivity (ABC) index, geometric-arithmetic (GA) index, and fourth and fifth version of these topological indices for Sierpinski networks denoted by S(n, k).

  2. Mathematical Properties of Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available Many researchers are attempting to create systems which
    mimic human thought, or understand speech, or beat to the best human chess-player [14]. Understanding intelligence and Creating intelligent artifacts both are the twin goals of Artificial Intelligence (AI.In more recent times, the interest is focused on problems related with Complex Networks [3, 5,6, 19], in particular on questions such as clustering search and identification. We attempt, in this paper, a panoramic vision of such mathematical methods in AI.

  3. Unraveling spurious properties of interaction networks with tailored random networks.

    Directory of Open Access Journals (Sweden)

    Stephan Bialonski

    Full Text Available We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

  4. Generic Properties of Random Gene Regulatory Networks.

    Science.gov (United States)

    Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao

    2013-12-01

    Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

  5. Spectral properties of the Google matrix of the World Wide Web and other directed networks.

    Science.gov (United States)

    Georgeot, Bertrand; Giraud, Olivier; Shepelyansky, Dima L

    2010-05-01

    We study numerically the spectrum and eigenstate properties of the Google matrix of various examples of directed networks such as vocabulary networks of dictionaries and university World Wide Web networks. The spectra have gapless structure in the vicinity of the maximal eigenvalue for Google damping parameter α equal to unity. The vocabulary networks have relatively homogeneous spectral density, while university networks have pronounced spectral structures which change from one university to another, reflecting specific properties of the networks. We also determine specific properties of eigenstates of the Google matrix, including the PageRank. The fidelity of the PageRank is proposed as a characterization of its stability.

  6. Scaling properties of cosmic (super)string networks

    International Nuclear Information System (INIS)

    Martins, C J A P

    2014-01-01

    I use a combination of state-of-the-art numerical simulations and analytic modelling to discuss the scaling properties of cosmic defect networks, including superstrings. Particular attention is given to the role of extra degrees of freedom in the evolution of these networks. Compared to the 'plain vanilla' case of Goto-Nambu strings, three such extensions play important but distinct roles in the network dynamics: the presence of charges/currents on the string worldsheet, the existence of junctions, and the possibility of a hierarchy of string tensions. I also comment on insights gained from studying simpler defect networks, including Goto-Nambu strings themselves, domain walls and semilocal strings

  7. The Model of the Software Running on a Computer Equipment Hardware Included in the Grid network

    Directory of Open Access Journals (Sweden)

    T. A. Mityushkina

    2012-12-01

    Full Text Available A new approach to building a cloud computing environment using Grid networks is proposed in this paper. The authors describe the functional capabilities, algorithm, model of software running on a computer equipment hardware included in the Grid network, that will allow to implement cloud computing environment using Grid technologies.

  8. 43 CFR 30.127 - What happens if property was improperly included in the inventory?

    Science.gov (United States)

    2010-10-01

    ... Interior INDIAN PROBATE HEARINGS PROCEDURES Judicial Authority and Duties § 30.127 What happens if property... proceeding, it is found that property has been improperly included in the inventory of an estate, the...

  9. Design and Optimization of Capacitated Supply Chain Networks Including Quality Measures

    Directory of Open Access Journals (Sweden)

    Krystel K. Castillo-Villar

    2014-01-01

    Full Text Available This paper presents (1 a novel capacitated model for supply chain network design which considers manufacturing, distribution, and quality costs (named SCND-COQ model and (2 five combinatorial optimization methods, based on nonlinear optimization, heuristic, and metaheuristic approaches, which are used to solve realistic instances of practical size. The SCND-COQ model is a mixed-integer nonlinear problem which can be used at a strategic planning level to design a supply chain network that maximizes the total profit subject to meeting an overall quality level of the final product at minimum costs. The SCND-COQ model computes the quality-related costs for the whole supply chain network considering the interdependencies among business entities. The effectiveness of the proposed solution approaches is shown using numerical experiments. These methods allow solving more realistic (capacitated supply chain network design problems including quality-related costs (inspections, rework, opportunity costs, and others within a reasonable computational time.

  10. Spectral properties of the temporal evolution of brain network structure.

    Science.gov (United States)

    Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

    2015-12-01

    The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

  11. Pore network properties of sandstones in a fault damage zone

    Science.gov (United States)

    Bossennec, Claire; Géraud, Yves; Moretti, Isabelle; Mattioni, Luca; Stemmelen, Didier

    2018-05-01

    The understanding of fluid flow in faulted sandstones is based on a wide range of techniques. These depend on the multi-method determination of petrological and structural features, porous network properties and both spatial and temporal variations and interactions of these features. The question of the multi-parameter analysis on fluid flow controlling properties is addressed for an outcrop damage zone in the hanging wall of a normal fault zone on the western border of the Upper Rhine Graben, affecting the Buntsandstein Group (Early Triassic). Diagenetic processes may alter the original pore type and geometry in fractured and faulted sandstones. Therefore, these may control the ultimate porosity and permeability of the damage zone. The classical model of evolution of hydraulic properties with distance from the major fault core is nuanced here. The hydraulic behavior of the rock media is better described by a pluri-scale model including: 1) The grain scale, where the hydraulic properties are controlled by sedimentary features, the distance from the fracture, and the impact of diagenetic processes. These result in the ultimate porous network characteristics observed. 2) A larger scale, where the structural position and characteristics (density, connectivity) of the fracture corridors are strongly correlated with both geo-mechanical and hydraulic properties within the damage zone.

  12. A practical algorithm for optimal operation management of distribution network including fuel cell power plants

    Energy Technology Data Exchange (ETDEWEB)

    Niknam, Taher; Meymand, Hamed Zeinoddini; Nayeripour, Majid [Electrical and Electronic Engineering Department, Shiraz University of Technology, Shiraz (Iran)

    2010-08-15

    Fuel cell power plants (FCPPs) have been taken into a great deal of consideration in recent years. The continuing growth of the power demand together with environmental constraints is increasing interest to use FCPPs in power system. Since FCPPs are usually connected to distribution network, the effect of FCPPs on distribution network is more than other sections of power system. One of the most important issues in distribution networks is optimal operation management (OOM) which can be affected by FCPPs. This paper proposes a new approach for optimal operation management of distribution networks including FCCPs. In the article, we consider the total electrical energy losses, the total electrical energy cost and the total emission as the objective functions which should be minimized. Whereas the optimal operation in distribution networks has a nonlinear mixed integer optimization problem, the optimal solution could be obtained through an evolutionary method. We use a new evolutionary algorithm based on Fuzzy Adaptive Particle Swarm Optimization (FAPSO) to solve the optimal operation problem and compare this method with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO) and Tabu Search (TS) over two distribution test feeders. (author)

  13. 76 FR 19466 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable...

    Science.gov (United States)

    2011-04-07

    ... Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable Staffing, and Third Dimension Waverly, OH; Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network... Group including on-site leased workers from Reserves Network, Jackson, Ohio. The workers produce...

  14. Structural properties and complexity of a new network class: Collatz step graphs.

    Directory of Open Access Journals (Sweden)

    Frank Emmert-Streib

    Full Text Available In this paper, we introduce a biologically inspired model to generate complex networks. In contrast to many other construction procedures for growing networks introduced so far, our method generates networks from one-dimensional symbol sequences that are related to the so called Collatz problem from number theory. The major purpose of the present paper is, first, to derive a symbol sequence from the Collatz problem, we call the step sequence, and investigate its structural properties. Second, we introduce a construction procedure for growing networks that is based on these step sequences. Third, we investigate the structural properties of this new network class including their finite scaling and asymptotic behavior of their complexity, average shortest path lengths and clustering coefficients. Interestingly, in contrast to many other network models including the small-world network from Watts & Strogatz, we find that CS graphs become 'smaller' with an increasing size.

  15. Topological properties of random wireless networks

    Indian Academy of Sciences (India)

    Wireless networks in which the node locations are random are best modelled as random geometric graphs (RGGs). In addition to their extensive application in the modelling of wireless networks, RGGs find many new applications and are being studied in their own right. In this paper we first provide a brief introduction to the ...

  16. Can recurrence networks show small-world property?

    International Nuclear Information System (INIS)

    Jacob, Rinku; Harikrishnan, K.P.; Misra, R.; Ambika, G.

    2016-01-01

    Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value ϵ chosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with ϵ equal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-world structure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor. - Highlights: • Properties of recurrence networks at intermediate-to-large values of recurrence threshold are analyzed from a complex network perspective. • Using a combined plot of characteristic path length and clustering coefficient, it is shown that the recurrence network constructed with recurrence threshold equal to or just above the percolation threshold cannot, in general, display small-world property. • As the recurrence threshold is increased from its usual operational window, the resulting network makes a smooth transition initially to a small-world network for an intermediate range of thresholds and finally to the classical random graph as the threshold becomes comparable to the size of the attractor.

  17. Can recurrence networks show small-world property?

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, Rinku, E-mail: rinku.jacob.vallanat@gmail.com [Department of Physics, The Cochin College, Cochin, 682002 (India); Harikrishnan, K.P., E-mail: kp_hk2002@yahoo.co.in [Department of Physics, The Cochin College, Cochin, 682002 (India); Misra, R., E-mail: rmisra@iucaa.in [Inter University Centre for Astronomy and Astrophysics, Pune, 411007 (India); Ambika, G., E-mail: g.ambika@iiserpune.ac.in [Indian Institute of Science Education and Research, Pune, 411008 (India)

    2016-08-12

    Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value ϵ chosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with ϵ equal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-world structure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor. - Highlights: • Properties of recurrence networks at intermediate-to-large values of recurrence threshold are analyzed from a complex network perspective. • Using a combined plot of characteristic path length and clustering coefficient, it is shown that the recurrence network constructed with recurrence threshold equal to or just above the percolation threshold cannot, in general, display small-world property. • As the recurrence threshold is increased from its usual operational window, the resulting network makes a smooth transition initially to a small-world network for an intermediate range of thresholds and finally to the classical random graph as the threshold becomes comparable to the size of the attractor.

  18. Structural and robustness properties of smart-city transportation networks

    Science.gov (United States)

    Zhang, Zhen-Gang; Ding, Zhuo; Fan, Jing-Fang; Meng, Jun; Ding, Yi-Min; Ye, Fang-Fu; Chen, Xiao-Song

    2015-09-01

    The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. Project supported by the Major Projects of the China National Social Science Fund (Grant No. 11 & ZD154).

  19. Structural and robustness properties of smart-city transportation networks

    International Nuclear Information System (INIS)

    Zhang Zhen-Gang; Ding Zhuo; Fan Jing-Fang; Chen Xiao-Song; Meng Jun; Ye Fang-Fu; Ding Yi-Min

    2015-01-01

    The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. (rapid communication)

  20. Spectral properties of Google matrix of Wikipedia and other networks

    Science.gov (United States)

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

    2013-05-01

    We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method, we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between PageRank and CheiRank vectors distinguishes different organizations of information flow on BBC and Le Monde web sites.

  1. Computational Models and Emergent Properties of Respiratory Neural Networks

    Science.gov (United States)

    Lindsey, Bruce G.; Rybak, Ilya A.; Smith, Jeffrey C.

    2012-01-01

    Computational models of the neural control system for breathing in mammals provide a theoretical and computational framework bringing together experimental data obtained from different animal preparations under various experimental conditions. Many of these models were developed in parallel and iteratively with experimental studies and provided predictions guiding new experiments. This data-driven modeling approach has advanced our understanding of respiratory network architecture and neural mechanisms underlying generation of the respiratory rhythm and pattern, including their functional reorganization under different physiological conditions. Models reviewed here vary in neurobiological details and computational complexity and span multiple spatiotemporal scales of respiratory control mechanisms. Recent models describe interacting populations of respiratory neurons spatially distributed within the Bötzinger and pre-Bötzinger complexes and rostral ventrolateral medulla that contain core circuits of the respiratory central pattern generator (CPG). Network interactions within these circuits along with intrinsic rhythmogenic properties of neurons form a hierarchy of multiple rhythm generation mechanisms. The functional expression of these mechanisms is controlled by input drives from other brainstem components, including the retrotrapezoid nucleus and pons, which regulate the dynamic behavior of the core circuitry. The emerging view is that the brainstem respiratory network has rhythmogenic capabilities at multiple levels of circuit organization. This allows flexible, state-dependent expression of different neural pattern-generation mechanisms under various physiological conditions, enabling a wide repertoire of respiratory behaviors. Some models consider control of the respiratory CPG by pulmonary feedback and network reconfiguration during defensive behaviors such as cough. Future directions in modeling of the respiratory CPG are considered. PMID:23687564

  2. Including Internet insurance as part of a hospital computer network security plan.

    Science.gov (United States)

    Riccardi, Ken

    2002-01-01

    Cyber attacks on a hospital's computer network is a new crime to be reckoned with. Should your hospital consider internet insurance? The author explains this new phenomenon and presents a risk assessment for determining network vulnerabilities.

  3. Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method.

    Science.gov (United States)

    Barkaoui, Abdelwahed; Chamekh, Abdessalem; Merzouki, Tarek; Hambli, Ridha; Mkaddem, Ali

    2014-03-01

    The complexity and heterogeneity of bone tissue require a multiscale modeling to understand its mechanical behavior and its remodeling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network (NN) computation and homogenization equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained NN simulation. Finite element calculation is performed at nanoscopic levels to provide a database to train an in-house NN program; and (iii) in steps 2-10 from fibril to continuum cortical bone tissue, homogenization equations are used to perform the computation at the higher scales. The NN outputs (elastic properties of the microfibril) are used as inputs for the homogenization computation to determine the properties of mineralized collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen, and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modeling. Good agreement was obtained between our predicted results and literature data. Copyright © 2013 John Wiley & Sons, Ltd.

  4. Epidemic spreading in scale-free networks including the effect of individual vigilance

    International Nuclear Information System (INIS)

    Gong Yong-Wang; Song Yu-Rong; Jiang Guo-Ping

    2012-01-01

    In this paper, we study the epidemic spreading in scale-free networks and propose a new susceptible-infected-recovered (SIR) model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is derived. It shows that individual vigilance has no effect on the epidemic threshold. The numerical simulations agree well with the analytical result. Furthermore, we investigate the effect of individual vigilance on the epidemic spreading speed. It is shown that individual vigilance can slow the epidemic spreading speed effectively and delay the arrival of peak epidemic infection. (general)

  5. Fundamental statistical features and self-similar properties of tagged networks

    International Nuclear Information System (INIS)

    Palla, Gergely; Farkas, Illes J; Pollner, Peter; Vicsek, Tamas; Derenyi, Imre

    2008-01-01

    We investigate the fundamental statistical features of tagged (or annotated) networks having a rich variety of attributes associated with their nodes. Tags (attributes, annotations, properties, features, etc) provide essential information about the entity represented by a given node, thus, taking them into account represents a significant step towards a more complete description of the structure of large complex systems. Our main goal here is to uncover the relations between the statistical properties of the node tags and those of the graph topology. In order to better characterize the networks with tagged nodes, we introduce a number of new notions, including tag-assortativity (relating link probability to node similarity), and new quantities, such as node uniqueness (measuring how rarely the tags of a node occur in the network) and tag-assortativity exponent. We apply our approach to three large networks representing very different domains of complex systems. A number of the tag related quantities display analogous behaviour (e.g. the networks we studied are tag-assortative, indicating possible universal aspects of tags versus topology), while some other features, such as the distribution of the node uniqueness, show variability from network to network allowing for pin-pointing large scale specific features of real-world complex networks. We also find that for each network the topology and the tag distribution are scale invariant, and this self-similar property of the networks can be well characterized by the tag-assortativity exponent, which is specific to each system.

  6. Scaling properties of domain wall networks

    International Nuclear Information System (INIS)

    Leite, A. M. M.; Martins, C. J. A. P.

    2011-01-01

    We revisit the cosmological evolution of domain wall networks, taking advantage of recent improvements in computing power. We carry out high-resolution field theory simulations in two, three and four spatial dimensions to study the effects of dimensionality and damping on the evolution of the network. Our results are consistent with the expected scale-invariant evolution of the network, which suggests that previous hints of deviations from this behavior may have been due to the limited dynamical range of those simulations. We also use the results of very large (1024 3 ) simulations in three cosmological epochs to provide a calibration for the velocity-dependent one-scale model for domain walls: we numerically determine the two free model parameters to have the values c w =0.5±0.2 and k w =1.1±0.3.

  7. Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

    Science.gov (United States)

    Pesavento, Michael J; Pinto, David J

    2012-11-01

    Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

  8. The microwave properties of composites including lightweight core–shell ellipsoids

    International Nuclear Information System (INIS)

    Yuan, Liming; Xu, Yonggang; Dai, Fei; Liao, Yi; Zhang, Deyuan

    2016-01-01

    In order to study the microwave properties of suspensions including lightweight core–shell ellipsoids, the calculation formula was obtained by substituting an equivalent ellipsoid for the original core–shell ellipsoid. Simulations for Fe-coated diatomite/paraffin suspensions were performed. Results reveal that the calculated results fitted the measured results very well when the inclusion concentration was no more than 15 vol%, but there was an obvious deviation when the inclusion concentration reached 24 vol%. By comparisons, the formula for less diluted suspensions was more suitable for calculating the electromagnetic parameter of suspensions especially when the ratio was smaller between the electromagnetic parameter of the inclusion and that of the host medium. - Highlights: • The microwave properties of suspensions with core-shell inclusions were studied. • Less diluted suspensions were considered. • Flaky Fe-coated diatomite/paraffin suspensions were studied. • The microwave properties could be simulated successfully.

  9. The microwave properties of composites including lightweight core–shell ellipsoids

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, Liming, E-mail: lming_y@163.com [Science and Technology on Electromagnetic Scattering Laboratory, Shanghai 200438 (China); Xu, Yonggang; Dai, Fei; Liao, Yi [Science and Technology on Electromagnetic Scattering Laboratory, Shanghai 200438 (China); Zhang, Deyuan [School of Mechanical Engineering and Automation, Beihang University, Beijing 100191 (China)

    2016-12-01

    In order to study the microwave properties of suspensions including lightweight core–shell ellipsoids, the calculation formula was obtained by substituting an equivalent ellipsoid for the original core–shell ellipsoid. Simulations for Fe-coated diatomite/paraffin suspensions were performed. Results reveal that the calculated results fitted the measured results very well when the inclusion concentration was no more than 15 vol%, but there was an obvious deviation when the inclusion concentration reached 24 vol%. By comparisons, the formula for less diluted suspensions was more suitable for calculating the electromagnetic parameter of suspensions especially when the ratio was smaller between the electromagnetic parameter of the inclusion and that of the host medium. - Highlights: • The microwave properties of suspensions with core-shell inclusions were studied. • Less diluted suspensions were considered. • Flaky Fe-coated diatomite/paraffin suspensions were studied. • The microwave properties could be simulated successfully.

  10. Scaling properties in time-varying networks with memory

    Science.gov (United States)

    Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

    2015-12-01

    The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

  11. The synaptic properties of cells define the hallmarks of interval timing in a recurrent neural network.

    Science.gov (United States)

    Pérez, Oswaldo; Merchant, Hugo

    2018-04-03

    Extensive research has described two key features of interval timing. The bias property is associated with accuracy and implies that time is overestimated for short intervals and underestimated for long intervals. The scalar property is linked to precision and states that the variability of interval estimates increases as a function of interval duration. The neural mechanisms behind these properties are not well understood. Here we implemented a recurrent neural network that mimics a cortical ensemble and includes cells that show paired-pulse facilitation and slow inhibitory synaptic currents. The network produces interval selective responses and reproduces both bias and scalar properties when a Bayesian decoder reads its activity. Notably, the interval-selectivity, timing accuracy, and precision of the network showed complex changes as a function of the decay time constants of the modeled synaptic properties and the level of background activity of the cells. These findings suggest that physiological values of the time constants for paired-pulse facilitation and GABAb, as well as the internal state of the network, determine the bias and scalar properties of interval timing. Significant Statement Timing is a fundamental element of complex behavior, including music and language. Temporal processing in a wide variety of contexts shows two primary features: time estimates exhibit a shift towards the mean (the bias property) and are more variable for longer intervals (the scalar property). We implemented a recurrent neural network that includes long-lasting synaptic currents, which can not only produce interval selective responses but also follow the bias and scalar properties. Interestingly, only physiological values of the time constants for paired-pulse facilitation and GABAb, as well as intermediate background activity within the network can reproduce the two key features of interval timing. Copyright © 2018 the authors.

  12. Properties of four real world collaboration--competition networks

    Science.gov (United States)

    Fu, Chun-Hua; Xu, Xiu-Lian; He, Da-Ren

    2009-03-01

    Our research group has empirically investigated 9 real world collaboration networks and 25 real world cooperation-competition networks. Among the 34 real world systems, all the 9 real world collaboration networks and 6 real world cooperation-competition networks show the unimodal act-size distribution and the shifted power law distribution of degree and act-degree. We have proposed a collaboration network evolution model for an explanation of the rules [1]. The other 14 real world cooperation-competition networks show that the act-size distributions are not unimodal; instead, they take qualitatively the same shifted power law forms as the degree and act-degree distributions. The properties of four systems (the main land movie film network, Beijing restaurant network, 2004 Olympic network, and Tao-Bao notebook computer sale network) are reported in detail as examples. Via a numerical simulation, we show that the new rule can still be explained by the above-mentioned model. [1] H. Chang, B. B. Su, et al. Phsica A, 2007, 383: 687-702.

  13. Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

    Directory of Open Access Journals (Sweden)

    Ram Prahlad T

    2008-08-01

    Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models

  14. 76 FR 79169 - Power Network New Mexico, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes...

    Science.gov (United States)

    2011-12-21

    ... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ER12-605-000] Power Network New Mexico, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for... Power Network New Mexico, LLC's application for market-based rate authority, with an accompanying rate...

  15. Some Learning Properties of Modular Network SOMs

    Science.gov (United States)

    Takeda, Manabu; Ikeda, Kazushi; Furukawa, Tetsuo

    The Modular Network Self-Organizing Map (mnSOM) is a generalization of the SOM, where each node represents a parametric function such as a multi-layer perceptron or another SOM. Since given datasets are, in general, fewer than nodes, some nodes never win in competition and have to update their parameters from the winners in the neighborhood. This is a process that can be regarded as interpolation. This study derives the interpolation curve between winners in simple cases and discusses the distribution of winners based on the neighborhood function.

  16. Referee Networks and Their Spectral Properties

    Science.gov (United States)

    Slanina, F.; Zhang, Y.-Ch.

    2005-09-01

    The bipartite graph connecting products and reviewers of that product is studied empirically in the case of amazon.com. We find that the network has power-law degree distribution on the side of reviewers, while on the side of products the distribution is better fitted by stretched exponential. The spectrum of normalised adjacency matrix shows power-law tail in the density of states. Establishing the community structures by finding localised eigenstates is not straightforward as the localised and delocalised states are mixed throughout the whole support of the spectrum.

  17. Electrical Properties of an m × n Hammock Network

    Science.gov (United States)

    Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

    2018-05-01

    Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

  18. Properties of healthcare teaming networks as a function of network construction algorithms.

    Directory of Open Access Journals (Sweden)

    Martin S Zand

    Full Text Available Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106-108 individual claims per year, making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast

  19. Dislocation concepts applied to fatigue properties of austenitic stainless steels including time-dependent modes

    Energy Technology Data Exchange (ETDEWEB)

    Tavassoli, A.A.

    1986-10-01

    Dislocation substructures formed in austenitic stainless steel 304L and 316L, fatigued at 673 K, 823 K and 873 K under total imposed strain ranges of 0.7 to 2.25%, and their correlation with mechanical properties have been investigated. In addition substructures formed at lower strain ranges have been examined using foils prepared from parts of the specimens with larger cross-sections. Investigation has also been extended to include the effect of intermittent hold-times up to 1.8 x 10/sup 4/s and sequential creep-fatigue and fatigue-creep. The experimental results obtained are analysed and their implications for current dislocation concepts and mechanical properties are discussed.

  20. Three-dimensional graphene networks: synthesis,properties and applications

    Institute of Scientific and Technical Information of China (English)

    Yanfeng Ma; Yongsheng Chen

    2015-01-01

    Recently, three-dimensional graphene/graphene oxide(GO) networks(3DGNs) in the form of foams,sponges and aerogels have atracted much atention. 3D structures provide graphene materials with high speciic surface areas, large pore volumes, strong mechanical strengths and fast mass and electron transport,owing to the combination of the 3D porous structures and the excellent intrinsic properties of graphene.his review focuses on the latest advances in the preparation, properties and potential applications of 3D micro-/nano-architectures made of graphene/GO-based networks, with emphasis on graphene foams and sponges.

  1. Interactions between the Design and Operation of Shale Gas Networks, Including CO2 Sequestration

    Directory of Open Access Journals (Sweden)

    Sharifzadeh Mahdi

    2017-04-01

    Full Text Available As the demand for energy continues to increase, shale gas, as an unconventional source of methane (CH4, shows great potential for commercialization. However, due to the ultra-low permeability of shale gas reservoirs, special procedures such as horizontal drilling, hydraulic fracturing, periodic well shut-in, and carbon dioxide (CO2 injection may be required in order to boost gas production, maximize economic benefits, and ensure safe and environmentally sound operation. Although intensive research is devoted to this emerging technology, many researchers have studied shale gas design and operational decisions only in isolation. In fact, these decisions are highly interactive and should be considered simultaneously. Therefore, the research question addressed in this study includes interactions between design and operational decisions. In this paper, we first establish a full-physics model for a shale gas reservoir. Next, we conduct a sensitivity analysis of important design and operational decisions such as well length, well arrangement, number of fractures, fracture distance, CO2 injection rate, and shut-in scheduling in order to gain in-depth insights into the complex behavior of shale gas networks. The results suggest that the case with the highest shale gas production may not necessarily be the most profitable design; and that drilling, fracturing, and CO2 injection have great impacts on the economic viability of this technology. In particular, due to the high costs, enhanced gas recovery (EGR using CO2 does not appear to be commercially competitive, unless tax abatements or subsidies are available for CO2 sequestration. It was also found that the interactions between design and operational decisions are significant and that these decisions should be optimized simultaneously.

  2. Structural properties of the Chinese air transportation multilayer network

    International Nuclear Information System (INIS)

    Hong, Chen; Zhang, Jun; Cao, Xian-Bin; Du, Wen-Bo

    2016-01-01

    Highlights: • We investigate the structural properties of the Chinese air transportation multilayer network (ATMN). • We compare two main types of layers corresponding to major and low-cost airlines. • It is found that small-world property and rich-club effect of the Chinese ATMN are mainly caused by major airlines. - Abstract: Recently multilayer networks are attracting great attention because the properties of many real-world systems cannot be well understood without considering their different layers. In this paper, we investigate the structural properties of the Chinese air transportation multilayer network (ATMN) by progressively merging layers together, where each commercial airline (company) defines a layer. The results show that the high clustering coefficient, short characteristic path length and large collection of reachable destinations of the Chinese ATMN can only emerge when several layers are merged together. Moreover, we compare two main types of layers corresponding to major and low-cost airlines. It is found that the small-world property and the rich-club effect of the Chinese ATMN are mainly caused by those layers corresponding to major airlines. Our work will highlight a better understanding of the Chinese air transportation network.

  3. Network properties of robust immunity in plants.

    Directory of Open Access Journals (Sweden)

    Kenichi Tsuda

    2009-12-01

    Full Text Available Two modes of plant immunity against biotrophic pathogens, Effector Triggered Immunity (ETI and Pattern-Triggered Immunity (PTI, are triggered by recognition of pathogen effectors and Microbe-Associated Molecular Patterns (MAMPs, respectively. Although the jasmonic acid (JA/ethylene (ET and salicylic acid (SA signaling sectors are generally antagonistic and important for immunity against necrotrophic and biotrophic pathogens, respectively, their precise roles and interactions in ETI and PTI have not been clear. We constructed an Arabidopsis dde2/ein2/pad4/sid2-quadruple mutant. DDE2, EIN2, and SID2 are essential components of the JA, ET, and SA sectors, respectively. The pad4 mutation affects the SA sector and a poorly characterized sector. Although the ETI triggered by the bacterial effector AvrRpt2 (AvrRpt2-ETI and the PTI triggered by the bacterial MAMP flg22 (flg22-PTI were largely intact in plants with mutations in any one of these genes, they were mostly abolished in the quadruple mutant. For the purposes of this study, AvrRpt2-ETI and flg22-PTI were measured as relative growth of Pseudomonas syringae bacteria within leaves. Immunity to the necrotrophic fungal pathogen Alternaria brassicicola was also severely compromised in the quadruple mutant. Quantitative measurements of the immunity levels in all combinatorial mutants and wild type allowed us to estimate the effects of the wild-type genes and their interactions on the immunity by fitting a mixed general linear model. This signaling allocation analysis showed that, contrary to current ideas, each of the JA, ET, and SA signaling sectors can positively contribute to immunity against both biotrophic and necrotrophic pathogens. The analysis also revealed that while flg22-PTI and AvrRpt2-ETI use a highly overlapping signaling network, the way they use the common network is very different: synergistic relationships among the signaling sectors are evident in PTI, which may amplify the signal

  4. Automatic reconstruction of fault networks from seismicity catalogs including location uncertainty

    International Nuclear Information System (INIS)

    Wang, Y.

    2013-01-01

    Within the framework of plate tectonics, the deformation that arises from the relative movement of two plates occurs across discontinuities in the earth's crust, known as fault zones. Active fault zones are the causal locations of most earthquakes, which suddenly release tectonic stresses within a very short time. In return, fault zones slowly grow by accumulating slip due to such earthquakes by cumulated damage at their tips, and by branching or linking between pre-existing faults of various sizes. Over the last decades, a large amount of knowledge has been acquired concerning the overall phenomenology and mechanics of individual faults and earthquakes: A deep physical and mechanical understanding of the links and interactions between and among them is still missing, however. One of the main issues lies in our failure to always succeed in assigning an earthquake to its causative fault. Using approaches based in pattern-recognition theory, more insight into the relationship between earthquakes and fault structure can be gained by developing an automatic fault network reconstruction approach using high resolution earthquake data sets at largely different scales and by considering individual event uncertainties. This thesis introduces the Anisotropic Clustering of Location Uncertainty Distributions (ACLUD) method to reconstruct active fault networks on the basis of both earthquake locations and their estimated individual uncertainties. This method consists in fitting a given set of hypocenters with an increasing amount of finite planes until the residuals of the fit compare with location uncertainties. After a massive search through the large solution space of possible reconstructed fault networks, six different validation procedures are applied in order to select the corresponding best fault network. Two of the validation steps (cross-validation and Bayesian Information Criterion (BIC)) process the fit residuals, while the four others look for solutions that

  5. Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

    Science.gov (United States)

    Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

    2017-12-01

    Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows

  6. Photometric Properties of Network and Faculae Derived from HMI Data Compensated for Scattered Light

    Energy Technology Data Exchange (ETDEWEB)

    Criscuoli, Serena; Whitney, Taylor [National Solar Observatory, 3665 Discovery Drive, Boulder, CO 80303 (United States); Norton, Aimee [Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA, 94305 (United States)

    2017-10-01

    We report on the photometric properties of faculae and network, as observed in full-disk, scattered-light-corrected images from the Helioseismic Magnetic Imager. We use a Lucy–Richardson deconvolution routine that corrects an image in less than one second. Faculae are distinguished from network through proximity to active regions. This is the first report that full-disk observations, including center-to-limb variations, reproduce the photometric properties of faculae and network observed previously only in sub-arcsecond-resolution; small field-of-view studies, i.e. that network, as defined by distance from active regions, exhibit higher photometric contrasts. Specifically, for magnetic flux values larger than approximately 300 G, the network is brighter than faculae and the contrast differences increase toward the limb, where the network contrast is about twice the facular one. For lower magnetic flux values, network appear darker than faculae. Contrary to reports from previous full-disk observations, we also found that network exhibits a higher center-to-limb variation. Our results are in agreement with reports from simulations that indicate magnetic flux alone is a poor proxy of the photometric properties of magnetic features. We estimate that the contribution of faculae and network to Total Solar Irradiance variability of the current Cycle 24 is overestimated by at least 11%, due to the photometric properties of network and faculae not being recognized as different. This estimate is specific to the method employed in this study to reconstruct irradiance variations, so caution should be paid when extending it to other techniques.

  7. Photometric Properties of Network and Faculae Derived from HMI Data Compensated for Scattered Light

    International Nuclear Information System (INIS)

    Criscuoli, Serena; Whitney, Taylor; Norton, Aimee

    2017-01-01

    We report on the photometric properties of faculae and network, as observed in full-disk, scattered-light-corrected images from the Helioseismic Magnetic Imager. We use a Lucy–Richardson deconvolution routine that corrects an image in less than one second. Faculae are distinguished from network through proximity to active regions. This is the first report that full-disk observations, including center-to-limb variations, reproduce the photometric properties of faculae and network observed previously only in sub-arcsecond-resolution; small field-of-view studies, i.e. that network, as defined by distance from active regions, exhibit higher photometric contrasts. Specifically, for magnetic flux values larger than approximately 300 G, the network is brighter than faculae and the contrast differences increase toward the limb, where the network contrast is about twice the facular one. For lower magnetic flux values, network appear darker than faculae. Contrary to reports from previous full-disk observations, we also found that network exhibits a higher center-to-limb variation. Our results are in agreement with reports from simulations that indicate magnetic flux alone is a poor proxy of the photometric properties of magnetic features. We estimate that the contribution of faculae and network to Total Solar Irradiance variability of the current Cycle 24 is overestimated by at least 11%, due to the photometric properties of network and faculae not being recognized as different. This estimate is specific to the method employed in this study to reconstruct irradiance variations, so caution should be paid when extending it to other techniques.

  8. Reliability–based economic model predictive control for generalised flow–based networks including actuators’ health–aware capabilities

    Directory of Open Access Journals (Sweden)

    Grosso Juan M.

    2016-09-01

    Full Text Available This paper proposes a reliability-based economic model predictive control (MPC strategy for the management of generalised flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamical allocation of safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators’ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the case study considered.

  9. Dynamic properties of epidemic spreading on finite size complex networks

    Science.gov (United States)

    Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

    2005-11-01

    The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

  10. Psychometric properties of the personal wellbeing index in Brazilian and Chilean adolescents including spirituality and religion

    Directory of Open Access Journals (Sweden)

    Jorge Castellá Sarriera

    2014-12-01

    Full Text Available This study compared the 7-item Personal Wellbeing Index (PWI with two other versions which include the domains "Spirituality" and "Religion", separately, in a sample of Brazilian (n = 1.047 and Chilean (n = 1.053 adolescents. A comparison of psychometric properties between the PWI versions was carried out through multigroup confirmatory factor analysis showing adequate adjustments (CFI > .95, RMSEA < .08, whereas the item spirituality presented better performance. For the analysis of the differential contribution of each domain to the notion of global satisfaction, a regression on the item Overall Life Satisfaction (OLS was applied using structural equations. It is recommended the inclusion of the item spirituality in the original scale, considering the importance of such domain in both cultures.

  11. Automatic reconstruction of fault networks from seismicity catalogs including location uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y.

    2013-07-01

    Within the framework of plate tectonics, the deformation that arises from the relative movement of two plates occurs across discontinuities in the earth's crust, known as fault zones. Active fault zones are the causal locations of most earthquakes, which suddenly release tectonic stresses within a very short time. In return, fault zones slowly grow by accumulating slip due to such earthquakes by cumulated damage at their tips, and by branching or linking between pre-existing faults of various sizes. Over the last decades, a large amount of knowledge has been acquired concerning the overall phenomenology and mechanics of individual faults and earthquakes: A deep physical and mechanical understanding of the links and interactions between and among them is still missing, however. One of the main issues lies in our failure to always succeed in assigning an earthquake to its causative fault. Using approaches based in pattern-recognition theory, more insight into the relationship between earthquakes and fault structure can be gained by developing an automatic fault network reconstruction approach using high resolution earthquake data sets at largely different scales and by considering individual event uncertainties. This thesis introduces the Anisotropic Clustering of Location Uncertainty Distributions (ACLUD) method to reconstruct active fault networks on the basis of both earthquake locations and their estimated individual uncertainties. This method consists in fitting a given set of hypocenters with an increasing amount of finite planes until the residuals of the fit compare with location uncertainties. After a massive search through the large solution space of possible reconstructed fault networks, six different validation procedures are applied in order to select the corresponding best fault network. Two of the validation steps (cross-validation and Bayesian Information Criterion (BIC)) process the fit residuals, while the four others look for solutions that

  12. A Novel Water Supply Network Sectorization Methodology Based on a Complete Economic Analysis, Including Uncertainties

    Directory of Open Access Journals (Sweden)

    Enrique Campbell

    2016-04-01

    Full Text Available The core idea behind sectorization of Water Supply Networks (WSNs is to establish areas partially isolated from the rest of the network to improve operational control. Besides the benefits associated with sectorization, some drawbacks must be taken into consideration by water operators: the economic investment associated with both boundary valves and flowmeters and the reduction of both pressure and system resilience. The target of sectorization is to properly balance these negative and positive aspects. Sectorization methodologies addressing the economic aspects mainly consider costs of valves and flowmeters and of energy, and the benefits in terms of water saving linked to pressure reduction. However, sectorization entails other benefits, such as the reduction of domestic consumption, the reduction of burst frequency and the enhanced capacity to detect and intervene over future leakage events. We implement a development proposed by the International Water Association (IWA to estimate the aforementioned benefits. Such a development is integrated in a novel sectorization methodology based on a social network community detection algorithm, combined with a genetic algorithm optimization method and Monte Carlo simulation. The methodology is implemented over a fraction of the WSN of Managua city, capital of Nicaragua, generating a net benefit of 25,572 $/year.

  13. Effect of the social influence on topological properties of user-object bipartite networks

    Science.gov (United States)

    Liu, Jian-Guo; Hu, Zhaolong; Guo, Qiang

    2013-11-01

    Social influence plays an important role in analyzing online users' collective behaviors [Salganik et al., Science 311, 854 (2006)]. However, the effect of the social influence from the viewpoint of theoretical model is missing. In this paper, by taking into account the social influence and users' preferences, we develop a theoretical model to analyze the topological properties of user-object bipartite networks, including the degree distribution, average nearest neighbor degree and the bipartite clustering coefficient, as well as topological properties of the original user-object networks and their unipartite projections. According to the users' preferences and the global ranking effect, we analyze the theoretical results for two benchmark data sets, Amazon and Bookcrossing, which are approximately consistent with the empirical results. This work suggests that this model is feasible to analyze topological properties of bipartite networks in terms of the social influence and the users' preferences.

  14. Mechanical properties of polymer-infiltrated-ceramic-network materials.

    Science.gov (United States)

    Coldea, Andrea; Swain, Michael V; Thiel, Norbert

    2013-04-01

    To determine and identify correlations between flexural strength, strain at failure, elastic modulus and hardness versus ceramic network densities of a range of novel polymer-infiltrated-ceramic-network (PICN) materials. Four ceramic network densities ranging from 59% to 72% of theoretical density, resin infiltrated PICN as well as pure polymer and dense ceramic cross-sections were subjected to Vickers Indentations (HV 5) for hardness evaluation. The flexural strength and elastic modulus were measured using three-point-bending. The fracture response of PICNs was determined for cracks induced by Vickers-indentation. Optical and scanning electron microscopy (SEM) was employed to observe the indented areas. Depending on the density of the porous ceramic the flexural strength of PICNs ranged from 131 to 160MPa, the hardness values ranged between 1.05 and 2.10GPa and the elastic modulus between 16.4 and 28.1GPa. SEM observations of the indentation induced cracks indicate that the polymer network causes greater crack deflection than the dense ceramic material. The results were compared with simple analytical expressions for property variation of two phase composite materials. This study points out the correlation between ceramic network density, elastic modulus and hardness of PICNs. These materials are considered to more closely imitate natural tooth properties compared with existing dental restorative materials. Copyright © 2013 Academy of Dental Materials. All rights reserved.

  15. Multi-equilibrium property of metabolic networks: SSI module

    Directory of Open Access Journals (Sweden)

    Chen Luonan

    2011-06-01

    Full Text Available Abstract Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

  16. Scattering Analysis of a Compact Dipole Array with Series and Parallel Feed Network including Mutual Coupling Effect

    Directory of Open Access Journals (Sweden)

    H. L. Sneha

    2013-01-01

    Full Text Available The current focus in defense arena is towards the stealth technology with an emphasis to control the radar cross-section (RCS. The scattering from the antennas mounted over the platform is of prime importance especially for a low-observable aerospace vehicle. This paper presents the analysis of the scattering cross section of a uniformly spaced linear dipole array. Two types of feed networks, that is, series and parallel feed networks, are considered. The total RCS of phased array with either kind of feed network is obtained by following the signal as it enters through the aperture and travels through the feed network. The RCS estimation of array is done including the mutual coupling effect between the dipole elements in three configurations, that is, side-by-side, collinear, and parallel-in-echelon. The results presented can be useful while designing a phased array with optimum performance towards low observability.

  17. Evolution properties of the community members for dynamic networks

    Science.gov (United States)

    Yang, Kai; Guo, Qiang; Li, Sheng-Nan; Han, Jing-Ti; Liu, Jian-Guo

    2017-03-01

    The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s ≤ 10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.

  18. Specialists meeting on properties of primary circuit structural materials including environmental effects

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1977-07-01

    The Specialists Meeting on Properties of Primary Circuit Structural Materials of LMFBRs covered the following topics: overview of materials program in different countries; mechanical properties of materials in air; fracture mechanics studies - component related activities; impact of environmental influences on mechanical properties; relationship of material properties and design methods. The purpose of the meeting was to provide a forum for exchange of information on structural materials behaviour in primary circuit of fast breeder reactors. Special emphasis was placed on environmental effects such as influence of sodium and irradiation on mechanical properties of reactor materials.

  19. Specialists meeting on properties of primary circuit structural materials including environmental effects

    International Nuclear Information System (INIS)

    1977-01-01

    The Specialists Meeting on Properties of Primary Circuit Structural Materials of LMFBRs covered the following topics: overview of materials program in different countries; mechanical properties of materials in air; fracture mechanics studies - component related activities; impact of environmental influences on mechanical properties; relationship of material properties and design methods. The purpose of the meeting was to provide a forum for exchange of information on structural materials behaviour in primary circuit of fast breeder reactors. Special emphasis was placed on environmental effects such as influence of sodium and irradiation on mechanical properties of reactor materials

  20. Measurement network design including traveltime determinations to minimize model prediction uncertainty

    NARCIS (Netherlands)

    Janssen, G.M.C.M.; Valstar, J.R.; Zee, van der S.E.A.T.M.

    2008-01-01

    Traveltime determinations have found increasing application in the characterization of groundwater systems. No algorithms are available, however, to optimally design sampling strategies including this information type. We propose a first-order methodology to include groundwater age or tracer arrival

  1. Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

    Directory of Open Access Journals (Sweden)

    Alexandru D. Iordan

    2018-01-01

    Full Text Available Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA and 20 older adults (OA were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of

  2. Topological properties of complex networks in protein structures

    Science.gov (United States)

    Kim, Kyungsik; Jung, Jae-Won; Min, Seungsik

    2014-03-01

    We study topological properties of networks in structural classification of proteins. We model the native-state protein structure as a network made of its constituent amino-acids and their interactions. We treat four structural classes of proteins composed predominantly of α helices and β sheets and consider several proteins from each of these classes whose sizes range from amino acids of the Protein Data Bank. Particularly, we simulate and analyze the network metrics such as the mean degree, the probability distribution of degree, the clustering coefficient, the characteristic path length, the local efficiency, and the cost. This work was supported by the KMAR and DP under Grant WISE project (153-3100-3133-302-350).

  3. Methods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists

    Directory of Open Access Journals (Sweden)

    Brenton J Prettejohn

    2011-03-01

    Full Text Available Many simulations of networks in computational neuroscience assume completely homogenous random networks of the Erd"{o}s-R'{e}nyi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the `scale-free' and `small-world' properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks.

  4. Development of pacemaker properties and rhythmogenic mechanisms in the mouse embryonic respiratory network

    Science.gov (United States)

    Chevalier, Marc; Toporikova, Natalia; Simmers, John; Thoby-Brisson, Muriel

    2016-01-01

    Breathing is a vital rhythmic behavior generated by hindbrain neuronal circuitry, including the preBötzinger complex network (preBötC) that controls inspiration. The emergence of preBötC network activity during prenatal development has been described, but little is known regarding inspiratory neurons expressing pacemaker properties at embryonic stages. Here, we combined calcium imaging and electrophysiological recordings in mouse embryo brainstem slices together with computational modeling to reveal the existence of heterogeneous pacemaker oscillatory properties relying on distinct combinations of burst-generating INaP and ICAN conductances. The respective proportion of the different inspiratory pacemaker subtypes changes during prenatal development. Concomitantly, network rhythmogenesis switches from a purely INaP/ICAN-dependent mechanism at E16.5 to a combined pacemaker/network-driven process at E18.5. Our results provide the first description of pacemaker bursting properties in embryonic preBötC neurons and indicate that network rhythmogenesis undergoes important changes during prenatal development through alterations in both circuit properties and the biophysical characteristics of pacemaker neurons. DOI: http://dx.doi.org/10.7554/eLife.16125.001 PMID:27434668

  5. Sparse and shrunken estimates of MRI networks in the brain and their influence on network properties

    DEFF Research Database (Denmark)

    Romero-Garcia, Rafael; Clemmensen, Line Katrine Harder

    2014-01-01

    approaches showed more stable results with a relative low variance at the expense of a little bias. Interestingly, topological properties as local and global efficiency estimated in networks constructed from traditional non-regularized correlations also showed higher variability when compared to those from...... regularized networks. Our findings suggest that a population-based connectivity study can achieve a more robust description of cortical topology through regularization of the correlation estimates. Four regularization methods were examined: Two with shrinkage (Ridge and Schäfer’s shrinkage), one with sparsity...... (Lasso) and one with both shrinkage and sparsity (Elastic net). Furthermore, the different regularizations resulted in different correlation estimates as well as network properties. The shrunken estimates resulted in lower variance of the estimates than the sparse estimates....

  6. Security Property Validation of the Sensor Network Encryption Protocol (SNEP

    Directory of Open Access Journals (Sweden)

    Salekul Islam

    2015-07-01

    Full Text Available Since wireless sensor networks (WSNs have been designed to be deployed in an unsecured, public environment, secured communication is really vital for their wide-spread use. Among all of the communication protocols developed for WSN, the Security Protocols for Sensor Networks (SPINS is exceptional, as it has been designed with security as a goal. SPINS is composed of two building blocks: Secure Network Encryption Protocol (SNEP and the “micro” version of the Timed Efficient Streaming Loss-tolerant Authentication (TESLA, named μTESLA. From the inception of SPINS, a number of efforts have been made to validate its security properties. In this paper, we have validated the security properties of SNEP by using an automated security protocol validation tool, named AVISPA. Using the protocol specification language, HLPSL, we model two combined scenarios—node to node key agreement and counter exchange protocols—followed by data transmission. Next, we validate the security properties of these combined protocols, using different AVISPA back-ends. AVISPA reports the models we have developed free from attacks. However, by analyzing the key distribution sub-protocol, we find one threat of a potential DoS attack that we have demonstrated by modeling in AVISPA. Finally, we propose a modification, and AVISPA reports this modified version free from the potential DoS attack.

  7. 76 FR 2145 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Jackson, OH...

    Science.gov (United States)

    2011-01-12

    ...,287B; TA-W-71,287C] Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Jackson, OH; Masco Builder Cabinet Group, Waverly, OH; Masco Builder Cabinet Group, Seal Township, OH; Masco Builder Cabinet Group, Seaman, OH; Amended Certification Regarding Eligibility To Apply for Worker...

  8. Influence of Bulk PDMS Network Properties on Water Wettability

    Science.gov (United States)

    Melillo, Matthew; Walker, Edwin; Klein, Zoe; Efimenko, Kirill; Genzer, Jan

    Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine antifouling coatings to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - medical devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, and end-group chemical functionality on the mechanical and surface properties of end-linked PDMS networks. Wettability was investigated through the sessile drop technique, wherein a DI water droplet was placed on the bulk network surface and droplet volume, shape, surface area, and contact angle were monitored as a function of time. Various silicone substrates ranging from incredibly soft and flexible materials (E' 50 kPa) to highly rigid networks (E' 5 MPa) were tested. The dynamic behavior of the droplet on the surfaces demonstrated equilibration times between the droplet and surface on the order of 5 minutes. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have provided new evidence for the strong influence that substrate modulus and molecular network structure have on the wettability of PDMS elastomers. These findings will aid in the design and implementation of efficient, accurate, and safe PDMS-based medical devices and microfluidic materials that involve aqueous media.

  9. Neural networks (NN applied to the commercial properties valuation

    Directory of Open Access Journals (Sweden)

    J. M. Núñez Tabales

    2017-03-01

    Full Text Available Several agents, such as buyers and sellers, or local or tax authorities need to estimate the value of properties. There are different approaches to obtain the market price of a dwelling. Many papers have been produced in the academic literature for such purposes, but, these are, almost always, oriented to estimate hedonic prices of residential properties, such as houses or apartments. Here these methodologies are used in the field of estimate market price of commercial premises, using AI techniques. A case study is developed in Cordova —city in the South of Spain—. Neural Networks are an attractive alternative to the traditional hedonic modelling approaches, as they are better adapted to non-linearities of causal relationships and they also produce smaller valuation errors. It is also possible, from the NN model, to obtain implicit prices associated to the main attributes that can explain the variability of the market price of commercial properties.

  10. Impact of visual repetition rate on intrinsic properties of low frequency fluctuations in the visual network.

    Directory of Open Access Journals (Sweden)

    Yi-Chia Li

    Full Text Available BACKGROUND: Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz fluctuations (LFFs during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1 interactions between visual stimuli and resting-state; (2 impact of repetition rate of visual stimuli. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses, fALFF (fractional Amplitude of Low Frequency Fluctuation, and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated. CONCLUSIONS/SIGNIFICANCE: To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration and disordered behaviors (early blind, but also exogenous sensory stimuli (visual stimuli with various repetition rates. It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains.

  11. Statistical properties of the personal social network in the Facebook

    Science.gov (United States)

    Guo, Q.; Shao, F.; Hu, Z. L.; Liu, J. G.

    2013-10-01

    The statistical properties of the user interaction behaviors in a city have great significance for developing the network marketing strategy, promoting personalized service and so on. In this paper, we investigate the interaction property of the users from New Orleans network in the Facebook, and find that one's out-degree and in-degree are approximately the same. In addition, when the number of a user friends is less than 65, the number of their posts would linearly grow with the slope 4.2, but when one user's friends are more than 65, their posts would grow with the slope 2.1. Further, the average link weight is relatively flat when the out-degree ranges from 28 to 65, and before or after the section it is on the rise or in decline, respectively, from which we can conclude that one could not maintain stable and meaningful relationships with more than 65 people in a single city. We present a null model to reshuffle the network to guarantee that the empirical results are not obtained by accident. The result obtained after reshuffling suggests that there exists a limit that restricts people's social activities.

  12. Analyzing self-similar and fractal properties of the C. elegans neural network.

    Directory of Open Access Journals (Sweden)

    Tyler M Reese

    Full Text Available The brain is one of the most studied and highly complex systems in the biological world. While much research has concentrated on studying the brain directly, our focus is the structure of the brain itself: at its core an interconnected network of nodes (neurons. A better understanding of the structural connectivity of the brain should elucidate some of its functional properties. In this paper we analyze the connectome of the nematode Caenorhabditis elegans. Consisting of only 302 neurons, it is one of the better-understood neural networks. Using a Laplacian Matrix of the 279-neuron "giant component" of the network, we use an eigenvalue counting function to look for fractal-like self similarity. This matrix representation is also used to plot visualizations of the neural network in eigenfunction coordinates. Small-world properties of the system are examined, including average path length and clustering coefficient. We test for localization of eigenfunctions, using graph energy and spacial variance on these functions. To better understand results, all calculations are also performed on random networks, branching trees, and known fractals, as well as fractals which have been "rewired" to have small-world properties. We propose algorithms for generating Laplacian matrices of each of these graphs.

  13. Complex networks as an emerging property of hierarchical preferential attachment

    Science.gov (United States)

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

    2015-12-01

    Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

  14. Standard recommended practice for examination of fuel element cladding including the determination of the mechanical properties

    International Nuclear Information System (INIS)

    Anon.

    1975-01-01

    Guidelines are provided for the post-irradiation examination of fuel cladding and to achieve better correlation and interpretation of the data in the field of radiation effects. The recommended practice is applicable to metal cladding of all types of fuel elements. The tests cited are suitable for determining mechanical properties of the fuel elements cladding. Various ASTM standards and test methods are cited

  15. Polyurethane acrylate networks including cellulose nanocrystals: a comparison between UV and EB- curing

    Science.gov (United States)

    Furtak-Wrona, K.; Kozik-Ostrówka, P.; Jadwiszczak, K.; Maigret, J. E.; Aguié-Béghin, V.; Coqueret, X.

    2018-01-01

    A water-based polyurethane (PUR) acrylate water emulsion was selected as a radiation curable matrix for preparing nanocomposites including cellulose nanocrystals (CNC) prepared by controlled hydrolysis of Ramie fibers. Cross-linking polymerization of samples prepared in the form of films or of 1 mm-thick bars was either initiated by exposure to the 395 nm light of a high intensity LED lamp or by treatment with low energy electron beam (EB). The conversion level of acrylate functions in samples submitted to increasing radiation doses was monitored by Fourier Transform Infrared Spectroscopy (FTIR). Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA) were used to characterize changes in the glass transition temperature of the PUR-CNC nanocomposites as a function of acrylate conversion and of CNC content. Micromechanical testing indicates the positive effect of 1 wt% CNC on Young's modulus and on the tensile strength at break (σ) of cured nanocomposites. The presence of CNC in the PUR acrylate matrix was shown to double the σ value of the nanocomposite cured to an acrylate conversion level of 85% by treatment with a 25 kGy dose under EB, whereas no increase of σ was observed in UV-cured samples exhibiting the same acrylate conversion level. The occurrence of grafting reactions inducing covalent linkages between the polysaccharide nanofiller and the PUR acrylate matrix during the EB treatment is advanced as an explanation to account for the improvement observed in samples cured under ionizing radiation.

  16. Polyurethane acrylate networks including cellulose nanocrystals: a comparison between UV and EB- curing

    International Nuclear Information System (INIS)

    Furtak-Wrona, K.; Kozik-Ostrówka, P.; Jadwiszczak, K.; Maigret, J.E.; Aguié-Béghin, V.; Coqueret, X.

    2018-01-01

    A water-based polyurethane (PUR) acrylate water emulsion was selected as a radiation curable matrix for preparing nanocomposites including cellulose nanocrystals (CNC) prepared by controlled hydrolysis of Ramie fibers. Cross-linking polymerization of samples prepared in the form of films or of 1 mm-thick bars was either initiated by exposure to the 395 nm light of a high intensity LED lamp or by treatment with low energy electron beam (EB). The conversion level of acrylate functions in samples submitted to increasing radiation doses was monitored by Fourier Transform Infrared Spectroscopy (FTIR). Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA) were used to characterize changes in the glass transition temperature of the PUR-CNC nanocomposites as a function of acrylate conversion and of CNC content. Micromechanical testing indicates the positive effect of 1 wt% CNC on Young's modulus and on the tensile strength at break (σ) of cured nanocomposites. The presence of CNC in the PUR acrylate matrix was shown to double the σ value of the nanocomposite cured to an acrylate conversion level of 85% by treatment with a 25 kGy dose under EB, whereas no increase of σ was observed in UV-cured samples exhibiting the same acrylate conversion level. The occurrence of grafting reactions inducing covalent linkages between the polysaccharide nanofiller and the PUR acrylate matrix during the EB treatment is advanced as an explanation to account for the improvement observed in samples cured under ionizing radiation. - Highlights: • Nanocomposites were prepared from o/w PUR acrylate emulsion and CNC suspension. • Nanocomposite and reference materials were cured to the same conversion by UV or EB. • Introducing 1 wt% CNC in EB-cured composites doubles the tensile strength. • UV-cured nanocomposites did not show significant improvement in tensile strength.

  17. Regime-dependent topological properties of biofuels networks

    Czech Academy of Sciences Publication Activity Database

    Krištoufek, Ladislav; Janda, K.; Zilberman, D.

    2013-01-01

    Roč. 86, č. 2 (2013), 40-1-40-12 ISSN 1434-6028 R&D Projects: GA ČR GA402/09/0965 Grant - others:GA UK(CZ) 118310; GA ČR(CZ) GAP402/11/0948 Program:GA Institutional support: RVO:67985556 Keywords : topology * biofuels * correlations Subject RIV: AH - Economics Impact factor: 1.463, year: 2013 http://library.utia.cas.cz/separaty/2013/E/kristoufek-regime-dependent topological properties of biofuels networks.pdf

  18. Evaluation of the vibration attenuation properties of an air-inflated cushion with two different heavy machinery seats in multi-axis vibration environments including jolts.

    Science.gov (United States)

    Ji, Xiaoxu; Eger, Tammy R; Dickey, James P

    2017-03-01

    Seats and cushions can attenuate whole-body vibration (WBV) exposures and minimize health risks for heavy machine operators. We successfully developed neural network (NN) algorithms to identify the vibration attenuation properties for four different seating conditions (seat/cushion combinations), and implemented each of the NN models to predict the equivalent daily exposure A(8) values for various vehicles in the forestry and mining environments. We also evaluated the performance of the new prototype No-Jolt™ air-inflated cushion and the original cushion of each seat with jolt exposures. We observed that the air cushion significantly improved the vibration attenuation properties of the seat that initially had good performance, but not for the seat that had relatively poor vibration attenuation properties. In addition, operator's anthropometrics and sex influenced the performance of the air-inflated cushion when the vibration environment included jolt exposures. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Electrical properties of transparent CNT and ITO coatings on PET substrate including nano-structural aspects

    Science.gov (United States)

    Park, Joung-Man; Wang, Zuo-Jia; Kwon, Dong-Jun; Gu, Ga-Young; Lawrence DeVries, K.

    2013-01-01

    Ultraviolet (UV)-visible spectra and surface resistance measurement were used to investigate optical transmittance and conductive properties of carbon nanotube (CNT) and indium tin oxide (ITO) coated polyethylene terephthalate (PET) substrates. Conductive CNT and ITO coatings were successfully fabricated on PET by a spray-coating method. Thin coatings of both materials exhibited good conductivity and transparency. Changes in electrical and optical properties of the coatings were studied as a function of the coating suspension concentration. Interfacial durability of the coatings on PET substrates was also investigated under fatigue and bending loads. CNT coated substrates, with high aspect ratios, exhibited no detectable change in surface resistance up to 2000 cyclic loadings, whereas the ITO coated substrates exhibited a substantial increase in surface resistance at 1000 loading cycles. This change in resistance is attributed to a reduction in the number and effectiveness of the electrical contact points due to the inherent brittle nature of ITO.

  20. Energy star compliant voice over internet protocol (VoIP) telecommunications network including energy star compliant VoIP devices

    Science.gov (United States)

    Kouchri, Farrokh Mohammadzadeh

    2012-11-06

    A Voice over Internet Protocol (VoIP) communications system, a method of managing a communications network in such a system and a program product therefore. The system/network includes an ENERGY STAR (E-star) aware softswitch and E-star compliant communications devices at system endpoints. The E-star aware softswitch allows E-star compliant communications devices to enter and remain in power saving mode. The E-star aware softswitch spools messages and forwards only selected messages (e.g., calls) to the devices in power saving mode. When the E-star compliant communications devices exit power saving mode, the E-star aware softswitch forwards spooled messages.

  1. Hydraulic Model for Drinking Water Networks, Including Household Connections; Modelo hidraulico para redes de agua potable con tomas domiciliarias

    Energy Technology Data Exchange (ETDEWEB)

    Guerrero Angulo, Jose Oscar [Universidad Autonoma de Sinaloa (Mexico); Arreguin Cortes, Felipe [Instituto Mexicano de Tecnologia del Agua, Jiutepec, Morelos (Mexico)

    2002-03-01

    This paper presents a hydraulic simulation model for drinking water networks, including elements that are currently not considered household connections, spatially variable flowrate distribution pipelines, and tee secondary network. This model is determined by solving the equations needed for a conventional model following an indirect procedure for the solution of large equations systems. Household connection performance is considered as dependent of water pressure and the way in which users operate the taps of such intakes. This approach allows a better a acquaintance with the drinking water supply networks performance as well as solving problems that demand a more precise hydraulic simulation, such as water quality variations, leaks in networks, and the influence of home water tanks as regulating devices. [Spanish] Se presenta un modelo de simulacion hidraulica para redes de agua potable en el cual se incluyen elementos que no se toman en cuenta actualmente, como las tomas domiciliarias, los tubos de distribucion con gastos espacialmente variado y la red secundaria, resolviendo el numero de ecuaciones que seria necesario plantear en un modelo convencional mediante un procedimiento indirecto para la solucion de grandes sistemas de ecuaciones. En las tomas domiciliarias se considera que su funcionamiento depende de las presiones y la forma en que los usuarios operan las llaves de las mismas. Este planteamiento permite conocer mejor el funcionamiento de las redes de abastecimiento de agua potable y solucionar problemas que requieren de una simulacion hidraulica mas precisa, como el comportamiento de la calidad del agua, las fugas en las redes y la influencia reguladora de los tinacos de las casas.

  2. Mean Green operators of deformable fiber networks embedded in a compliant matrix and property estimates

    Science.gov (United States)

    Franciosi, Patrick; Spagnuolo, Mario; Salman, Oguz Umut

    2018-04-01

    Composites comprising included phases in a continuous matrix constitute a huge class of meta-materials, whose effective properties, whether they be mechanical, physical or coupled, can be selectively optimized by using appropriate phase arrangements and architectures. An important subclass is represented by "network-reinforced matrices," say those materials in which one or more of the embedded phases are co-continuous with the matrix in one or more directions. In this article, we present a method to study effective properties of simple such structures from which more complex ones can be accessible. Effective properties are shown, in the framework of linear elasticity, estimable by using the global mean Green operator for the entire embedded fiber network which is by definition through sample spanning. This network operator is obtained from one of infinite planar alignments of infinite fibers, which the network can be seen as an interpenetrated set of, with the fiber interactions being fully accounted for in the alignments. The mean operator of such alignments is given in exact closed form for isotropic elastic-like or dielectric-like matrices. We first exemplify how these operators relevantly provide, from classic homogenization frameworks, effective properties in the case of 1D fiber bundles embedded in an isotropic elastic-like medium. It is also shown that using infinite patterns with fully interacting elements over their whole influence range at any element concentration suppresses the dilute approximation limit of these frameworks. We finally present a construction method for a global operator of fiber networks described as interpenetrated such bundles.

  3. Structure-Property Relationships and the Mixed Network Former Effect in Boroaluminosilicate Glasses

    DEFF Research Database (Denmark)

    Zheng, Qiuju; Potuzak, Marcel; Mauro, John C.

    compositions by substituting Al2O3 for SiO2. We also investigate the various roles of sodium in the glasses including charge compensation of tetrahedral aluminum and boron atoms and formation of non-bridging oxygen. We find that mechanical properties (density, elastic moduli, and hardness), glass transition......Boroaluminosilicate glasses are important materials for various applications, e.g., liquid crystal display substrates, glass fibers for reinforcement, and thermal shock-resistant glass containers. The complicated structural speciation in these glasses leads to a mixed network former effect yielding...... nonlinear variation in many macroscopic properties. It is therefore crucial to investigate and understand structure-property correlations in boroaluminosilicate glasses. Here we study the structure-property relationships of a range of sodium boroaluminosilicate glasses from peralkaline to peraluminous...

  4. Numerical calculation of electromagnetic properties including chirality parameters for uniaxial bianisotropic media

    International Nuclear Information System (INIS)

    Amirkhizi, Alireza V; Nemat-Nasser, Sia

    2008-01-01

    Through the use of conductive straight wires or coils the electromagnetic properties of a composite material can be modified. The asymmetric geometry of the coils creates an overall chiral response. The polarization vectors rotate as an electromagnetic wave travels through such a medium. To calculate the chirality of a medium prior to its manufacturing, we developed a method to extract all four electromagnetic material parameter tensors for a general uniaxial bianisotropic composite based on the numerical simulation of the electromagnetic fields. Our method uses appropriate line and surface field averages in a single unit cell of the periodic structure of the composite material. These overall field quantities have physical meaning only when the microscopic variation of the electromagnetic fields in the scale of the unit cell is not important, that is when the wavelength of interest is significantly larger than the maximum linear dimension of the unit cell. The overall constitutive relations of the periodic structure can then be obtained from the relations among the average quantities

  5. Predictive Modeling of Mechanical Properties of Welded Joints Based on Dynamic Fuzzy RBF Neural Network

    Directory of Open Access Journals (Sweden)

    ZHANG Yongzhi

    2016-10-01

    Full Text Available A dynamic fuzzy RBF neural network model was built to predict the mechanical properties of welded joints, and the purpose of the model was to overcome the shortcomings of static neural networks including structural identification, dynamic sample training and learning algorithm. The structure and parameters of the model are no longer head of default, dynamic adaptive adjustment in the training, suitable for dynamic sample data for learning, learning algorithm introduces hierarchical learning and fuzzy rule pruning strategy, to accelerate the training speed of model and make the model more compact. Simulation of the model was carried out by using three kinds of thickness and different process TC4 titanium alloy TIG welding test data. The results show that the model has higher prediction accuracy, which is suitable for predicting the mechanical properties of welded joints, and has opened up a new way for the on-line control of the welding process.

  6. Tribological properties and morphology of bimodal elastomeric nitrile butadiene rubber networks

    International Nuclear Information System (INIS)

    Guo, Yin; Wang, Jiaxu; Li, Kang; Ding, Xingwu

    2013-01-01

    Highlights: • Bimodal elastomeric NBR as a new material was developed. • The structure of bimodal elastomeric NBR networks was determined. • The relationship between structure and mechanical properties was investigated. • The tribological properties and mechanisms of bimodal NBR were analyzed. • The benefits of bimodal NBR in the field of tribology were discussed. - Abstract: Bimodal nitrile butadiene rubber (NBR) was examined in this study. The molecular structure was determined by dynamic mechanical analysis and transmission electron microscopy. The relationship between the structure and the mechanical properties related to elastomeric tribological properties was investigated. The properties and the mechanisms of friction and wear of bimodal elastomeric NBR networks were also analyzed. The lubricating characteristics of bimodal NBR networks were revealed based on the mechanisms of friction and wear. Results show that bimodal NBR networks are similar to bimodal polydimethylsiloxane networks. The form and density of the network structure can be controlled from elastomeric networks to thermosetting resin networks. The mechanical properties of bimodal NBR networks, such as elasticity, elongation at break, fatigue characteristic, tensile strength, elastic modulus, and thermal stability can be precisely controlled following the variation in network structure. The friction, wear, and lubrication of bimodal NBR networks can be clearly described according to the principles of tribology. Common elastomers cannot simultaneously reduce friction and wear because of the different mechanisms of friction and wear; however, bimodal elastomer networks can efficiently address this problem

  7. Enzyme oxidation of plant galactomannans yielding biomaterials with novel properties and applications, including as delivery systems.

    Science.gov (United States)

    Galante, Yves M; Merlini, Luca; Silvetti, Tiziana; Campia, Paola; Rossi, Bianca; Viani, Fiorenza; Brasca, Milena

    2018-06-01

    New biomaterials from renewable sources and the development of "functionalized biopolymers" are fields of growing industrial interest. Plant polysaccharides represent a valid alternative to traditional synthetic polymers, which are obtained from monomers of fossil, non-renewable origin. Several polysaccharides, either in their natural or chemically/biochemically modified forms, are currently employed in the biomedical, food and feed, and industrial fields, including packaging. Sustainable biochemical reactions, such as enzyme modifications of polysaccharides, open further possibilities for new product and process innovation. In the present review, we summarize the recent progress on enzyme oxidation of galactomannans (GM) from few leguminous plants (performed either with galactose oxidase or laccase) and we focus on the versatile and easily accessible laccase/TEMPO oxidative reaction. The latter causes a steep viscosity increase of GM water solutions and a transition of the gels from a viscous to an elastic form, due to formation of emiacetalic bonds and thus of internal cross-linking of the polymers. Following lyophilization of these hydrogels, stable aerogels can be obtained, which were shown to have good potential as delivery systems (DS) of actives. The active molecules tested and herewith described are polymyxin B, an antibiotic; nisin, an antimicrobial peptide; the enzymes lysozyme, protease and lipase; the mixture of the industrial microbiocides 5-chloro-2-methyl-4-isothiazolin-3-one (CIT) and 2-methyl-4-isothiazolin-3-one (MIT). The advantages of such aerogel systems and the possibilities they open for future developments, including as DS, are described.

  8. Identifying the Critical Links in Road Transportation Networks: Centrality-based approach utilizing structural properties

    Energy Technology Data Exchange (ETDEWEB)

    Chinthavali, Supriya [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-04-01

    Surface transportation road networks share structural properties similar to other complex networks (e.g., social networks, information networks, biological networks, and so on). This research investigates the structural properties of road networks for any possible correlation with the traffic characteristics such as link flows those determined independently. Additionally, we define a criticality index for the links of the road network that identifies the relative importance in the network. We tested our hypotheses with two sample road networks. Results show that, correlation exists between the link flows and centrality measures of a link of the road (dual graph approach is followed) and the criticality index is found to be effective for one test network to identify the vulnerable nodes.

  9. The assessment of cyberstalking: an expanded examination including social networking, attachment, jealousy, and anger in relation to violence and abuse.

    Science.gov (United States)

    Strawhun, Jenna; Adams, Natasha; Huss, Matthew T

    2013-01-01

    Because the first antistalking statute was enacted in California in 1990, stalking research has been expanded immensely, yet been largely confined to exploring traditional pursuit tactics. This study instead examined the prevalence and correlates of cyberstalking behaviors while examining the phenomenon in a more inclusive manner than previous studies focusing on cyberstalking by including social networking avenues. In addition to a measure assessing cyberstalking-related behaviors, questionnaires assessing pathological aspects of personality, including attachment style, interpersonal jealousy, interpersonal violence, and anger were also provided to participants. Results indicate that, given preliminary evidence, cyberstalking-related behaviors are related to past measures of traditional stalking and cyberstalking, although prior attachment, jealousy, and violence issues within relationships are significant predictors of cyberstalking-related behaviors. In addition, unexpected gender differences emerged. For example, women admitted greater frequencies of cyberstalking perpetration than males, signaling that further research on frequency and motivation for cyberstalking among the sexes is necessary.

  10. [Research on compatibility of prescriptions including Ginseng Radix et Rhizoma and Trogopterus Dung based on complex network analysis].

    Science.gov (United States)

    Li, Meng-Wen; Fan, Xin-Sheng; Zhang, Ling-Shan; Wang, Cong-Jun

    2017-09-01

    The applications of prescriptions including Ginseng Radix et Rhizoma and Trogopterus Dung in contemporary literatures from 1949 to 2016 are compiled and the data mining techniques containing scale-free complex network method are utilized to explore its practical characteristics, with comparison between modern and ancient ones. The results indicate that malignant neoplasms, coronary heart disease which present Qi deficiency and blood stasis type are the main diseases treated by prescriptions including Ginseng Radix et Rhizoma and Trogopterus Dung according to the reports during 1949 to 2016. The complex network connection shows that Glycyrrhizae Radixet Rhizoma, Angelicae Sinensis Radix, Astragali Radix, Typhae Pollen, Salviae Miltiorrhizae Radix et Rhizoma are the primary drugs related to Ginseng Radix et Rhizoma and Trogopterus Dung. The next are Paeoniae Radix Alba, Atractylodis Macrocephalae Rhizoma, Persicae Semen, Foria, et al. Carthami Flos, Notoginseng Radix et Rhizoma, Cyperi Rhizoma, Bupleuri Radix are the peripheral ones. Also, Ginseng Radix et Rhizoma-Glycyrrhizae Radixet Rhizoma, Trogopterus Dung-Glycyrrhizae Radixet Rhizoma, Ginseng Radix et Rhizoma-Angelicae Sinensis Radix, Trogopterus Dung-Angelicae Sinensis Radix, Ginseng Radix et Rhizoma-Astragali Radix, Trogopterus Dung-Astragali Radix are the main paired drugs. The paired drugs including Ginseng Radix et Rhizoma-Trogopterus Dung-Glycyrrhizae Radixet Rhizoma, Ginseng Radix et Rhizoma-Trogopterus Dung-Angelicae Sinensis Radix, Ginseng Radix et Rhizoma-Trogopterus Dung-Astragali Radix, Ginseng Radix et Rhizoma-Trogopterus Dung-Typhae Pollen have a higher support degree. The main compatible drugs are different in ancient and modern prescriptions including Ginseng Radix et Rhizoma and Trogopterus Dung. Notoginseng Radix et Rhizoma, Typhae Pollen, Salviae Miltiorrhizae Radix et Rhizoma, Astragali Radix are utilized frequently in modern prescriptions while less used in ancient ones. It is also shown

  11. PDMS Network Structure-Property Relationships: Influence of Molecular Architecture on Mechanical and Wetting Properties

    Science.gov (United States)

    Melillo, Matthew Joseph

    Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine-antifouling coatings to medical devices and absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into and leach out of PDMS networks is of critical importance for the design and use in another application - microfluidic devices. The growing use of PDMS in microfluidic devices raises the concern that some researchers may use this material without fully understanding all of its advantages, drawbacks, and intricacies. The primary goal of this Ph.D. dissertation is to elucidate PDMS network molecular structure to macroscopic property relationships and to demonstrate how molecular architecture can alter dynamic mechanical and wetting characteristics. We prepare PDMS materials by using vinyl/ tetrakis(dimethylsiloxy)silane (TDSS) and silanol/ tetraethylorthosilicate (TEOS) combinations of PDMS end-groups and crosslinkers as two model systems. Under constant curing conditions, we systematically study the effects of polymer molecular weight, loading of crosslinker, and end-group chemical functionality on the extent of gelation and the dynamic mechanical and water wetting properties of end-linked PDMS networks. The extent of the gelation reaction is determined using the Soxhlet extraction to quantify the amount of material that did and did not participate in the crosslinking reactions, termed the gel and sol fractions, respectively. We use the Miller-Macosko model in conjunction with the gel fraction and precise chemical composition (i.e., stoichiometric ratio and molecular weight) to determine the fractions of elastic and pendant material, the molecular weight between chemical crosslinks, and the average effective functionality of the crosslinker molecule. Based on dynamic mechanical testing, we find that the maximum storage moduli are achieved at optimal stoichiometric conditions in the vinyl

  12. Milk Technological Properties as Affected by Including Artichoke By-Products Silages in the Diet of Dairy Goats

    Directory of Open Access Journals (Sweden)

    Raquel Muelas

    2017-12-01

    Full Text Available Traditional farming practices include the use of local agricultural by-products in the diet of ruminants. Artichoke harvesting and transformation yield high amounts of by-products that, if properly used, may reduce farming costs and the environmental impact of farming. The present study tests the inclusion of silages from artichoke by-products (plant and outer bracts in the diet of dairy goats (0%, 12.5% and 25% inclusion on the technological and sensory properties of milk during a five-month study. Milk composition, color, stability, coagulation and fermentation properties remained unaffected by diet changes. Panelists were not able to differentiate among yogurts obtained from those milks by discriminant triangular sensory tests. Silages of artichoke by-products can be included in isoproteic and isoenergetic diets for dairy goats, up to a 25% (feed dry matter, without negatively affecting milk technological and sensory properties whereas reducing feeding costs.

  13. Large-scale structure of a network of co-occurring MeSH terms: statistical analysis of macroscopic properties.

    Directory of Open Access Journals (Sweden)

    Andrej Kastrin

    Full Text Available Concept associations can be represented by a network that consists of a set of nodes representing concepts and a set of edges representing their relationships. Complex networks exhibit some common topological features including small diameter, high degree of clustering, power-law degree distribution, and modularity. We investigated the topological properties of a network constructed from co-occurrences between MeSH descriptors in the MEDLINE database. We conducted the analysis on two networks, one constructed from all MeSH descriptors and another using only major descriptors. Network reduction was performed using the Pearson's chi-square test for independence. To characterize topological properties of the network we adopted some specific measures, including diameter, average path length, clustering coefficient, and degree distribution. For the full MeSH network the average path length was 1.95 with a diameter of three edges and clustering coefficient of 0.26. The Kolmogorov-Smirnov test rejects the power law as a plausible model for degree distribution. For the major MeSH network the average path length was 2.63 edges with a diameter of seven edges and clustering coefficient of 0.15. The Kolmogorov-Smirnov test failed to reject the power law as a plausible model. The power-law exponent was 5.07. In both networks it was evident that nodes with a lower degree exhibit higher clustering than those with a higher degree. After simulated attack, where we removed 10% of nodes with the highest degrees, the giant component of each of the two networks contains about 90% of all nodes. Because of small average path length and high degree of clustering the MeSH network is small-world. A power-law distribution is not a plausible model for the degree distribution. The network is highly modular, highly resistant to targeted and random attack and with minimal dissortativity.

  14. Statistical properties and attack tolerance of growing networks with algebraic preferential attachment

    International Nuclear Information System (INIS)

    Liu Zonghua; Lai Yingcheng; Ye Nong

    2002-01-01

    We consider growing networks with algebraic preferential attachment and address two questions: (1) what is the effect of temporal fluctuations in the number of new links acquired by the network? and (2) what is the network tolerance against random failures and intentional attacks? We find that the fluctuations generally have little effect on the network properties, although they lead to a plateau behavior for small degrees in the connectivity distribution. Formulas are derived for the evolution and distribution of the network connectivity, which are tested by numerical simulations. Numerical study of the effect of failures and attacks suggests that networks constructed under algebraic preferential attachment are more robust than scale-free networks

  15. The effect of the neural activity on topological properties of growing neural networks.

    Science.gov (United States)

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  16. Structural Properties of the Brazilian Air Transportation Network

    Directory of Open Access Journals (Sweden)

    GUILHERME S. COUTO

    2015-09-01

    Full Text Available The air transportation network in a country has a great impact on the local, national and global economy. In this paper, we analyze the air transportation network in Brazil with complex network features to better understand its characteristics. In our analysis, we built networks composed either by national or by international flights. We also consider the network when both types of flights are put together. Interesting conclusions emerge from our analysis. For instance, Viracopos Airport (Campinas City is the most central and connected airport on the national flights network. Any operational problem in this airport separates the Brazilian national network into six distinct subnetworks. Moreover, the Brazilian air transportation network exhibits small world characteristics and national connections network follows a power law distribution. Therefore, our analysis sheds light on the current Brazilian air transportation infrastructure, bringing a novel understanding that may help face the recent fast growth in the usage of the Brazilian transport network.

  17. Structural Properties of the Brazilian Air Transportation Network.

    Science.gov (United States)

    Couto, Guilherme S; da Silva, Ana Paula Couto; Ruiz, Linnyer B; Benevenuto, Fabrício

    2015-09-01

    The air transportation network in a country has a great impact on the local, national and global economy. In this paper, we analyze the air transportation network in Brazil with complex network features to better understand its characteristics. In our analysis, we built networks composed either by national or by international flights. We also consider the network when both types of flights are put together. Interesting conclusions emerge from our analysis. For instance, Viracopos Airport (Campinas City) is the most central and connected airport on the national flights network. Any operational problem in this airport separates the Brazilian national network into six distinct subnetworks. Moreover, the Brazilian air transportation network exhibits small world characteristics and national connections network follows a power law distribution. Therefore, our analysis sheds light on the current Brazilian air transportation infrastructure, bringing a novel understanding that may help face the recent fast growth in the usage of the Brazilian transport network.

  18. Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

    Science.gov (United States)

    Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

    2013-06-01

    Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

  19. Syntactic computations in the language network: Characterising dynamic network properties using representational similarity analysis

    Directory of Open Access Journals (Sweden)

    Lorraine Komisarjevsky Tyler

    2013-05-01

    Full Text Available The core human capacity of syntactic analysis involves a left hemisphere network involving left inferior frontal gyrus (LIFG and posterior middle temporal gyrus (LMTG and the anatomical connections between them. Here we use MEG to determine the spatio-temporal properties of syntactic computations in this network. Listeners heard spoken sentences containing a local syntactic ambiguity (e.g. …landing planes…, at the offset of which they heard a disambiguating verb and decided whether it was an acceptable/unacceptable continuation of the sentence. We charted the time-course of processing and resolving syntactic ambiguity by measuring MEG responses from the onset of each word in the ambiguous phrase and the disambiguating word. We used representational similarity analysis (RSA to characterize syntactic information represented in the LIFG and LpMTG over time and to investigate their relationship to each other. Testing a variety of lexico-syntactic and ambiguity models against the MEG data, our results suggest early lexico-syntactic responses in the LpMTG and later effects of ambiguity in the LIFG, pointing to a clear differentiation in the functional roles of these two regions. Our results suggest the LpMTG represents and transmits lexical information to the LIFG, which responds to and resolves the ambiguity.

  20. Confinement properties of 2D porous molecular networks on metal surfaces

    International Nuclear Information System (INIS)

    Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

    2016-01-01

    Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article

  1. Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank

    OpenAIRE

    Zhao, Liang; Liao, Siyu; Wang, Yanzhi; Li, Zhe; Tang, Jian; Pan, Victor; Yuan, Bo

    2017-01-01

    Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks. Empirical results have shown that neural networks with weight matrices of LDR matrices, referred as LDR neural networks, can achieve significant reduction in space and computational complexity while retaining high accuracy. We formally study LDR matrices in deep learning. First, we prove the universal approximation property of LDR neural networks with a ...

  2. Species-free species distribution models describe macroecological properties of protected area networks.

    Science.gov (United States)

    Robinson, Jason L; Fordyce, James A

    2017-01-01

    narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

  3. Modeling and simulating the adaptive electrical properties of stochastic polymeric 3D networks

    International Nuclear Information System (INIS)

    Sigala, R; Smerieri, A; Camorani, P; Schüz, A; Erokhin, V

    2013-01-01

    Memristors are passive two-terminal circuit elements that combine resistance and memory. Although in theory memristors are a very promising approach to fabricate hardware with adaptive properties, there are only very few implementations able to show their basic properties. We recently developed stochastic polymeric matrices with a functionality that evidences the formation of self-assembled three-dimensional (3D) networks of memristors. We demonstrated that those networks show the typical hysteretic behavior observed in the ‘one input-one output’ memristive configuration. Interestingly, using different protocols to electrically stimulate the networks, we also observed that their adaptive properties are similar to those present in the nervous system. Here, we model and simulate the electrical properties of these self-assembled polymeric networks of memristors, the topology of which is defined stochastically. First, we show that the model recreates the hysteretic behavior observed in the real experiments. Second, we demonstrate that the networks modeled indeed have a 3D instead of a planar functionality. Finally, we show that the adaptive properties of the networks depend on their connectivity pattern. Our model was able to replicate fundamental qualitative behavior of the real organic 3D memristor networks; yet, through the simulations, we also explored other interesting properties, such as the relation between connectivity patterns and adaptive properties. Our model and simulations represent an interesting tool to understand the very complex behavior of self-assembled memristor networks, which can finally help to predict and formulate hypotheses for future experiments. (paper)

  4. VSNL1 Co-expression networks in aging include calcium signaling, synaptic plasticity, and Alzheimer’s disease pathways

    Directory of Open Access Journals (Sweden)

    C W Lin

    2015-03-01

    Full Text Available The Visinin-like 1 (VSNL1 gene encodes Visinin-like protein 1, a peripheral biomarker for Alzheimer disease (AD. Little is known, however, about normal VSNL1 expression in brain and the biologic networks in which it participates. Frontal cortex gray matter from 209 subjects without neurodegenerative or psychiatric illness, ranging in age from 16–91, were processed on Affymetrix GeneChip 1.1 ST and Human SNP Array 6.0. VSNL1 expression was unaffected by age and sex, and not significantly associated with SNPs in cis or trans. VSNL1 was significantly co-expressed with genes in pathways for Calcium Signaling, AD, Long Term Potentiation, Long Term Depression, and Trafficking of AMPA Receptors. The association with AD was driven, in part, by correlation with amyloid precursor protein (APP expression. These findings provide an unbiased link between VSNL1 and molecular mechanisms of AD, including pathways implicated in synaptic pathology in AD. Whether APP may drive increased VSNL1 expression, VSNL1 drives increased APP expression, or both are downstream of common pathogenic regulators will need to be evaluated in model systems.

  5. PTA-1 computer program for treating pressure transients in hydraulic networks including the effect of pipe plasticity

    International Nuclear Information System (INIS)

    Youngdahl, C.K.; Kot, C.A.

    1977-01-01

    Pressure pulses in the intermediate sodium system of a liquid-metal-cooled fast breeder reactor, such as may originate from a sodium/water reaction in a steam generator, are propagated through the complex sodium piping network to system components such as the pump and intermediate heat exchanger. To assess the effects of such pulses on continued reliable operation of these components and to contribute to system designs which result in the mitigation of these effects, Pressure Transient Analysis (PTA) computer codes are being developed for accurately computing the transmission of pressure pulses through a complicated fluid transport system, consisting of piping, fittings and junctions, and components. PTA-1 provides an extension of the well-accepted and verified fluid hammer formulation for computing hydraulic transients in elastic or rigid piping systems to include plastic deformation effects. The accuracy of the modeling of pipe plasticity effects on transient propagation has been validated using results from two sets of Stanford Research Institute experiments. Validation of PTA-1 using the latter set of experiments is described briefly. The comparisons of PTA-1 computations with experiments show that (1) elastic-plastic deformation of LMFBR-type piping can have a significant qualitative and quantitative effect on pressure pulse propagation, even in simple systems; (2) classical fluid-hammer theory gives erroneous results when applied to situations where piping deforms plastically; and (3) the computational model incorporated in PTA-1 for predicting plastic deformation and its effect on transient propagation is accurate

  6. Graph analysis of structural brain networks in Alzheimer's disease: beyond small world properties.

    Science.gov (United States)

    John, Majnu; Ikuta, Toshikazu; Ferbinteanu, Janina

    2017-03-01

    Changes in brain connectivity in patients with early Alzheimer's disease (AD) have been investigated using graph analysis. However, these studies were based on small data sets, explored a limited range of network parameters, and did not focus on more restricted sub-networks, where neurodegenerative processes may introduce more prominent alterations. In this study, we constructed structural brain networks out of 87 regions using data from 135 healthy elders and 100 early AD patients selected from the Open Access Series of Imaging Studies (OASIS) database. We evaluated the graph properties of these networks by investigating metrics of network efficiency, small world properties, segregation, product measures of complexity, and entropy. Because degenerative processes take place at different rates in different brain areas, analysis restricted to sub-networks may reveal changes otherwise undetected. Therefore, we first analyzed the graph properties of a network encompassing all brain areas considered together, and then repeated the analysis after dividing the brain areas into two sub-networks constructed by applying a clustering algorithm. At the level of large scale network, the analysis did not reveal differences between AD patients and controls. In contrast, the same analysis performed on the two sub-networks revealed that small worldness diminished with AD only in the sub-network containing the areas of medial temporal lobe known to be heaviest and earliest affected. The second sub-network, which did not present significant AD-induced modifications of 'classical' small world parameters, nonetheless showed a trend towards an increase in small world propensity, a novel metric that unbiasedly quantifies small world structure. Beyond small world properties, complexity and entropy measures indicated that the intricacy of connection patterns and structural diversity decreased in both sub-networks. These results show that neurodegenerative processes impact volumetric

  7. Integration Strategy Is a Key Step in Network-Based Analysis and Dramatically Affects Network Topological Properties and Inferring Outcomes

    Science.gov (United States)

    Jin, Nana; Wu, Deng; Gong, Yonghui; Bi, Xiaoman; Jiang, Hong; Li, Kongning; Wang, Qianghu

    2014-01-01

    An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches. PMID:25243127

  8. Investigation of the properties of fully reacted unstoichiometric polydimethylsiloxane networks and their extracted network fractions

    DEFF Research Database (Denmark)

    Frankær, Sarah Maria Grundahl; Jensen, Mette Krog; Bejenariu, Anca Gabriela

    2012-01-01

    We investigated the linear dynamic response of a series of fully reacted unstoichiometric polydimethylsiloxane (PDMS) networks and of the two corresponding network fractions namely the sol and the washed network. The sol and the washed network were separated by a simple extraction process. This way...

  9. LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

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

    Directory of Open Access Journals (Sweden)

    G. Suresh

    2015-02-01

    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.

  11. R2 & NE: NAVTEQ 2011 Q3 Highway Network for the United States, including Puerto Rico and the US Virgin Islands in SDC Format

    Data.gov (United States)

    U.S. Environmental Protection Agency — The HIGHWAYS layer contains the Highway network, using NAVTEQ Functional Class=1,2,3 which includes major routes between minor cities or towns, and through city...

  12. Tailoring the mechanical properties by molecular integration of flexible and stiff polymer networks.

    Science.gov (United States)

    Wan, Haixiao; Shen, Jianxiang; Gao, Naishen; Liu, Jun; Gao, Yangyang; Zhang, Liqun

    2018-03-28

    Designing a multiple-network structure at the molecular level to tailor the mechanical properties of polymeric materials is of great scientific and technological importance. Through the coarse-grained molecular dynamics simulation, we successfully construct an interpenetrating polymer network (IPN) composed of a flexible polymer network and a stiff polymer network. First, we find that there is an optimal chain stiffness for a single network (SN) to achieve the best stress-strain behavior. Then we turn to study the mechanical behaviors of IPNs. The result shows that the stress-strain behaviors of the IPNs appreciably exceed the sum of that of the corresponding single flexible and stiff network, which highlights the advantage of the IPN structure. By systematically varying the stiffness of the stiff polymer network of the IPNs, optimal stiffness also exists to achieve the best performance. We attribute this to a much larger contribution of the non-bonded interaction energy. Last, the effect of the component concentration ratio is probed. With the increase of the concentration of the flexible network, the stress-strain behavior of the IPNs is gradually enhanced, while an optimized concentration (around 60% molar ration) of the stiff network occurs, which could result from the dominant role of the enthalpy rather than the entropy. In general, our work is expected to provide some guidelines to better tailor the mechanical properties of the IPNs made of a flexible network and a stiff network, by manipulating the stiffness of the stiff polymer network and the component concentration ratio.

  13. Interpenetrated polymer networks based on commercial silicone elastomers and ionic networks with high dielectric permittivity and self-healing properties

    DEFF Research Database (Denmark)

    Ogliani, Elisa; Yu, Liyun; Skov, Anne Ladegaard

    the applicability. One method used to avoid this limitation is to increase the dielectric permittivity of the material in order to improve the actuation response at a given field. Recently, interpenetrating polymer networks (IPNs) based on covalently cross-linked commercial silicone elastomers and ionic networks...... from amino- and carboxylic acid- functional silicones have been designed[2] (Figure 1). This novel system provides both the mechanical stability and the high breakdown strength given by the silicone part of the IPNs and the high permittivity and the softening effect of the ionic network. Thus......,1 Hz), and the commercial elastomers RT625 and LR3043/30 provide thebest viscoelastic properties to the systems, since they maintain low viscous losses upon addition of ionic network. The values ofthe breakdown strength in all cases remain higher than that of the reference pure PDMS network (ranging...

  14. Association of structural global brain network properties with intelligence in normal aging.

    Directory of Open Access Journals (Sweden)

    Florian U Fischer

    Full Text Available Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60-85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience.

  15. Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

    Science.gov (United States)

    Fischer, Florian U.; Wolf, Dominik; Scheurich, Armin; Fellgiebel, Andreas

    2014-01-01

    Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60–85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience. PMID:24465994

  16. Probing the structural and dynamical properties of liquid water with models including non-local electron correlation

    International Nuclear Information System (INIS)

    Del Ben, Mauro; Hutter, Jürg; VandeVondele, Joost

    2015-01-01

    Water is a ubiquitous liquid that displays a wide range of anomalous properties and has a delicate structure that challenges experiment and simulation alike. The various intermolecular interactions that play an important role, such as repulsion, polarization, hydrogen bonding, and van der Waals interactions, are often difficult to reproduce faithfully in atomistic models. Here, electronic structure theories including all these interactions at equal footing, which requires the inclusion of non-local electron correlation, are used to describe structure and dynamics of bulk liquid water. Isobaric-isothermal (NpT) ensemble simulations based on the Random Phase Approximation (RPA) yield excellent density (0.994 g/ml) and fair radial distribution functions, while various other density functional approximations produce scattered results (0.8-1.2 g/ml). Molecular dynamics simulation in the microcanonical (NVE) ensemble based on Møller-Plesset perturbation theory (MP2) yields dynamical properties in the condensed phase, namely, the infrared spectrum and diffusion constant. At the MP2 and RPA levels of theory, ice is correctly predicted to float on water, resolving one of the anomalies as resulting from a delicate balance between van der Waals and hydrogen bonding interactions. For several properties, obtaining quantitative agreement with experiment requires correction for nuclear quantum effects (NQEs), highlighting their importance, for structure, dynamics, and electronic properties. A computed NQE shift of 0.6 eV for the band gap and absorption spectrum illustrates the latter. Giving access to both structure and dynamics of condensed phase systems, non-local electron correlation will increasingly be used to study systems where weak interactions are of paramount importance

  17. Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

    Directory of Open Access Journals (Sweden)

    Dallakyan Sargis

    2008-08-01

    Full Text Available Abstract Background Gram-negative bacteria use periplasmic-binding proteins (bPBP to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo and closed (ligated conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding. Results We use a distance constraint model (DCM to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network. Conclusion Non-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect

  18. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    Directory of Open Access Journals (Sweden)

    Go Myong-Hyun

    2011-07-01

    Full Text Available Abstract Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability. Please see related article BMC Medicine, 2011, 9:87

  19. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    Science.gov (United States)

    Blower, Sally; Go, Myong-Hyun

    2011-07-19

    Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.

  20. Heuristic algorithm for determination of local properties of scale-free networks

    CERN Document Server

    Mitrovic, M

    2006-01-01

    Complex networks are everywhere. Many phenomena in nature can be modeled as networks: - brain structures - protein-protein interaction networks - social interactions - the Internet and WWW. They can be represented in terms of nodes and edges connecting them. Important characteristics: - these networks are not random; they have a structured architecture. Structure of different networks are similar: - all have power law degree distribution (scale-free property) - despite large size there is usually relatively short path between any two nodes (small world property). Global characteristics: - degree distribution, clustering coefficient and the diameter. Local structure: - frequency of subgraphs of given type (subgraph of order k is a part of the network consisting of k nodes and edges between them). There are different types of subgraphs of the same order.

  1. Using network properties to evaluate targeted immunization algorithms

    Directory of Open Access Journals (Sweden)

    Bita Shams

    2014-09-01

    Full Text Available Immunization of complex network with minimal or limited budget is a challenging issue for research community. In spite of much literature in network immunization, no comprehensive research has been conducted for evaluation and comparison of immunization algorithms. In this paper, we propose an evaluation framework for immunization algorithms regarding available amount of vaccination resources, goal of immunization program, and time complexity. The evaluation framework is designed based on network topological metrics which is extensible to all epidemic spreading model. Exploiting evaluation framework on well-known targeted immunization algorithms shows that in general, immunization based on PageRank centrality outperforms other targeting strategies in various types of networks, whereas, closeness and eigenvector centrality exhibit the worst case performance.

  2. Network Properties of the Ensemble of RNA Structures

    Science.gov (United States)

    Clote, Peter; Bayegan, Amir

    2015-01-01

    We describe the first dynamic programming algorithm that computes the expected degree for the network, or graph G = (V, E) of all secondary structures of a given RNA sequence a = a 1, …, a n. Here, the nodes V correspond to all secondary structures of a, while an edge exists between nodes s, t if the secondary structure t can be obtained from s by adding, removing or shifting a base pair. Since secondary structure kinetics programs implement the Gillespie algorithm, which simulates a random walk on the network of secondary structures, the expected network degree may provide a better understanding of kinetics of RNA folding when allowing defect diffusion, helix zippering, and related conformation transformations. We determine the correlation between expected network degree, contact order, conformational entropy, and expected number of native contacts for a benchmarking dataset of RNAs. Source code is available at http://bioinformatics.bc.edu/clotelab/RNAexpNumNbors. PMID:26488894

  3. Memory functions reveal structural properties of gene regulatory networks

    Science.gov (United States)

    Perez-Carrasco, Ruben

    2018-01-01

    Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

  4. Diamond network: template-free fabrication and properties.

    Science.gov (United States)

    Zhuang, Hao; Yang, Nianjun; Fu, Haiyuan; Zhang, Lei; Wang, Chun; Huang, Nan; Jiang, Xin

    2015-03-11

    A porous diamond network with three-dimensionally interconnected pores is of technical importance but difficult to be produced. In this contribution, we demonstrate a simple, controllable, and "template-free" approach to fabricate diamond networks. It combines the deposition of diamond/β-SiC nanocomposite film with a wet-chemical selective etching of the β-SiC phase. The porosity of these networks was tuned from 15 to 68%, determined by the ratio of the β-SiC phase in the composite films. The electrochemical working potential and the reactivity of redox probes on the diamond networks are similar to those of a flat nanocrystalline diamond film, while their surface areas are hundreds of times larger than that of a flat diamond film (e.g., 490-fold enhancement for a 3 μm thick diamond network). The marriage of the unprecedented physical/chemical features of diamond with inherent advantages of the porous structure makes the diamond network a potential candidate for various applications such as water treatment, energy conversion (batteries or fuel cells), and storage (capacitors), as well as electrochemical and biochemical sensing.

  5. Prediction of thermophysical and transport properties of ternary organic non-electrolyte systems including water by polynomials

    Directory of Open Access Journals (Sweden)

    Đorđević Bojan D.

    2013-01-01

    Full Text Available The description and prediction of the thermophysical and transport properties of ternary organic non-electrolyte systems including water by the polynomial equations are reviewed. Empirical equations of Radojković et al. (also known as Redlich-Kister, Kohler, Jacob-Fitzner, Colinet, Tsao-Smith, Toop, Scatchard et al. and Rastogi et al. are compared with experimental data of available papers appeared in well know international journals (Fluid Phase Equilibria, Journal of Chemical and Engineering Data, Journal of Chemical Thermodynamics, Journal of Solution Chemistry, Journal of the Serbian Chemical Society, The Canadian Journal of Chemical Engineering, Journal of Molecular Liquids, Thermochimica Acta, etc.. The applicability of empirical models to estimate excess molar volumes, VE, excess viscosities, ηE, excess free energies of activation of a viscous flow,

  6. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    OpenAIRE

    Blower, Sally; Go, Myong-Hyun

    2011-01-01

    Abstract Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagu...

  7. Modeling and dynamical topology properties of VANET based on complex networks theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hong; Li, Jie, E-mail: prof.li@foxmail.com [School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, 430074 (China)

    2015-01-15

    Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a

  8. Effects of network resolution on topological properties of human neocortex

    DEFF Research Database (Denmark)

    Romero-Garcia, Rafael; Atienza, Mercedes; Clemmensen, Line Katrine Harder

    2012-01-01

    Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small-world or......Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small...

  9. Elastic properties and short-range structural order in mixed network former glasses.

    Science.gov (United States)

    Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John

    2017-06-21

    Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.

  10. Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

    Science.gov (United States)

    Merrison-Hort, Robert; Soffe, Stephen R; Borisyuk, Roman

    2018-01-01

    Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model). PMID:29589828

  11. Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects

    Science.gov (United States)

    Castellano, Claudio; Pastor-Satorras, Romualdo

    2017-10-01

    The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.

  12. Stationary and nonstationary properties of evolving networks with preferential linkage

    International Nuclear Information System (INIS)

    Jezewski, W.

    2002-01-01

    Networks evolving by preferential attachment of both external and internal links are investigated. The rate of adding an external link is assumed to depend linearly on the degree of a preexisting node to which a new node is connected. The process of creating an internal link, between a pair of existing vertices, is assumed to be controlled entirely by the vertex that has more links than the other vertex in the pair, and the rate of creation of such a link is assumed to be, in general, nonlinear in the degree of the more strongly connected vertex. It is shown that degree distributions of networks evolving only by creating internal links display for large degrees a nonstationary power-law decay with a time-dependent scaling exponent. Nonstationary power-law behaviors are numerically shown to persist even when the number of nodes is not fixed and both external and internal connections are introduced, provided that the rate of preferential attachment of internal connections is nonlinear. It is argued that nonstationary effects are not unlikely in real networks, although these effects may not be apparent, especially in networks with a slowly varying mean degree

  13. Prediction of Multiphase Flow Properties from Network Models ...

    African Journals Online (AJOL)

    A uniform pore size structure resulted in more favorable two-phase relative permeability distribution, with the relative permeability depending greatly on the phase saturations. Capillary pressure, on the other hand, was found to increase with image resolution. Keywords: Network Model, Computer Tomography, Relative ...

  14. Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

    Science.gov (United States)

    Sadeh, Sadra; Rotter, Stefan

    2015-01-01

    The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not

  15. Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

    Directory of Open Access Journals (Sweden)

    Sadra Sadeh

    2015-01-01

    Full Text Available The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are

  16. Criticality is an emergent property of genetic networks that exhibit evolvability.

    Directory of Open Access Journals (Sweden)

    Christian Torres-Sosa

    Full Text Available Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype while allowing for switching between multiple phenotypes (network states as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations. We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i preserve all the already acquired phenotypes (dynamical attractor states and (ii generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation while conserving the existing phenotypes (conservation suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape.

  17. A comparative analysis of the statistical properties of large mobile phone calling networks.

    Science.gov (United States)

    Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2014-05-30

    Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

  18. Investigation of global and local network properties of music perception with culturally different styles of music.

    Science.gov (United States)

    Li, Yan; Rui, Xue; Li, Shuyu; Pu, Fang

    2014-11-01

    Graph theoretical analysis has recently become a popular research tool in neuroscience, however, there have been very few studies on brain responses to music perception, especially when culturally different styles of music are involved. Electroencephalograms were recorded from ten subjects listening to Chinese traditional music, light music and western classical music. For event-related potentials, phase coherence was calculated in the alpha band and then constructed into correlation matrices. Clustering coefficients and characteristic path lengths were evaluated for global properties, while clustering coefficients and efficiency were assessed for local network properties. Perception of light music and western classical music manifested small-world network properties, especially with a relatively low proportion of weights of correlation matrices. For local analysis, efficiency was more discernible than clustering coefficient. Nevertheless, there was no significant discrimination between Chinese traditional and western classical music perception. Perception of different styles of music introduces different network properties, both globally and locally. Research into both global and local network properties has been carried out in other areas; however, this is a preliminary investigation aimed at suggesting a possible new approach to brain network properties in music perception. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. The 'emergent scaling' phenomenon and the dielectric properties of random resistor-capacitor networks

    CERN Document Server

    Bouamrane, R

    2003-01-01

    An efficient algorithm, based on the Frank-Lobb reduction scheme, for calculating the equivalent dielectric properties of very large random resistor-capacitor (R-C) networks has been developed. It has been used to investigate the network size and composition dependence of dielectric properties and their statistical variability. The dielectric properties of 256 samples of random networks containing: 512, 2048, 8192 and 32 768 components distributed randomly in the ratios 60% R-40% C, 50% R-50% C and 40% R-60% C have been computed. It has been found that these properties exhibit the anomalous power law dependences on frequency known as the 'universal dielectric response' (UDR). Attention is drawn to the contrast between frequency ranges across which percolation determines dielectric response, where considerable variability is found amongst the samples, and those across which power laws define response where very little variability is found between samples. It is concluded that the power law UDRs are emergent pr...

  20. Structure-Property Relationships in Polycyanurate / Graphene Networks

    Science.gov (United States)

    2015-12-12

    Briefing Charts 3. DATES COVERED (From - To) 17 Nov 2015 – 12 Dec 2015 4. TITLE AND SUBTITLE Structure-Property Relationships in Polycyanurate...ANSI Std. 239.18 1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Structure-Property Relationships in...the attractive processing characteristics of LECy are retained in graphene oxide / LECy mixtures. Impurities, such as aryl phenols and transition metals

  1. Chemical structure, network topology, and porosity effects on the mechanical properties of Zeolitic Imidazolate Frameworks

    OpenAIRE

    Tan, J. C.; Bennett, T. D.; Cheetham, A. K.

    2010-01-01

    The mechanical properties of seven zeolitic imidazolate frameworks (ZIFs) based on five unique network topologies have been systematically characterized by single-crystal nanoindentation studies. We demonstrate that the elastic properties of ZIF crystal structures are strongly correlated to the framework density and the underlying porosity. For the systems considered here, the elastic modulus was found to range from 3 to 10 GPa, whereas the hardness property lies between 300 MPa and 1.1 GPa. ...

  2. Laboratory Studies of the Reactive Chemistry and Changing CCN Properties of Secondary Organic Aerosol, Including Model Development

    Energy Technology Data Exchange (ETDEWEB)

    Scot Martin

    2013-01-31

    The chemical evolution of secondary-organic-aerosol (SOA) particles and how this evolution alters their cloud-nucleating properties were studied. Simplified forms of full Koehler theory were targeted, specifically forms that contain only those aspects essential to describing the laboratory observations, because of the requirement to minimize computational burden for use in integrated climate and chemistry models. The associated data analysis and interpretation have therefore focused on model development in the framework of modified kappa-Koehler theory. Kappa is a single parameter describing effective hygroscopicity, grouping together several separate physicochemical parameters (e.g., molar volume, surface tension, and van't Hoff factor) that otherwise must be tracked and evaluated in an iterative full-Koehler equation in a large-scale model. A major finding of the project was that secondary organic materials produced by the oxidation of a range of biogenic volatile organic compounds for diverse conditions have kappa values bracketed in the range of 0.10 +/- 0.05. In these same experiments, somewhat incongruently there was significant chemical variation in the secondary organic material, especially oxidation state, as was indicated by changes in the particle mass spectra. Taken together, these findings then support the use of kappa as a simplified yet accurate general parameter to represent the CCN activation of secondary organic material in large-scale atmospheric and climate models, thereby greatly reducing the computational burden while simultaneously including the most recent mechanistic findings of laboratory studies.

  3. Solar photospheric network properties and their cycle variation

    Energy Technology Data Exchange (ETDEWEB)

    Thibault, K.; Charbonneau, P.; Béland, M., E-mail: kim@astro.umontreal.ca-a, E-mail: paulchar@astro.umontreal.ca-b, E-mail: michel.beland@calculquebec.ca-c [Département de Physique et Calcul Québec, Université de Montréal, 2900 Édouard-Montpetit, Montréal, QC H3T 1J4 (Canada)

    2014-11-20

    We present a numerical simulation of the formation and evolution of the solar photospheric magnetic network over a full solar cycle. The model exhibits realistic behavior as it produces large, unipolar concentrations of flux in the polar caps, a power-law flux distribution with index –1.69, a flux replacement timescale of 19.3 hr, and supergranule diameters of 20 Mm. The polar behavior is especially telling of model accuracy, as it results from lower-latitude activity, and accumulates the residues of any potential modeling inaccuracy and oversimplification. In this case, the main oversimplification is the absence of a polar sink for the flux, causing an amount of polar cap unsigned flux larger than expected by almost one order of magnitude. Nonetheless, our simulated polar caps carry the proper signed flux and dipole moment, and also show a spatial distribution of flux in good qualitative agreement with recent high-latitude magnetographic observations by Hinode. After the last cycle emergence, the simulation is extended until the network has recovered its quiet Sun initial condition. This permits an estimate of the network relaxation time toward the baseline state characterizing extended periods of suppressed activity, such as the Maunder Grand Minimum. Our simulation results indicate a network relaxation time of 2.9 yr, setting 2011 October as the soonest the time after which the last solar activity minimum could have qualified as a Maunder-type Minimum. This suggests that photospheric magnetism did not reach its baseline state during the recent extended minimum between cycles 23 and 24.

  4. Engineering the Mechanical Properties of Polymer Networks with Precise Doping of Primary Defects.

    Science.gov (United States)

    Chan, Doreen; Ding, Yichuan; Dauskardt, Reinhold H; Appel, Eric A

    2017-12-06

    Polymer networks are extensively utilized across numerous applications ranging from commodity superabsorbent polymers and coatings to high-performance microelectronics and biomaterials. For many applications, desirable properties are known; however, achieving them has been challenging. Additionally, the accurate prediction of elastic modulus has been a long-standing difficulty owing to the presence of loops. By tuning the prepolymer formulation through precise doping of monomers, specific primary network defects can be programmed into an elastomeric scaffold, without alteration of their resulting chemistry. The addition of these monomers that respond mechanically as primary defects is used both to understand their impact on the resulting mechanical properties of the materials and as a method to engineer the mechanical properties. Indeed, these materials exhibit identical bulk and surface chemistry, yet vastly different mechanical properties. Further, we have adapted the real elastic network theory (RENT) to the case of primary defects in the absence of loops, thus providing new insights into the mechanism for material strength and failure in polymer networks arising from primary network defects, and to accurately predict the elastic modulus of the polymer system. The versatility of the approach we describe and the fundamental knowledge gained from this study can lead to new advancements in the development of novel materials with precisely defined and predictable chemical, physical, and mechanical properties.

  5. Modeling mechanical properties of cast aluminum alloy using artificial neural network

    International Nuclear Information System (INIS)

    Jokhio, M.H.; Panhwar, M.I.

    2009-01-01

    Modeling is widely used to investigate the mechanical properties of engineering materials due to increasing demand of low cost and high strength to weight ratio for many engineering applications. The aluminum casting alloys are cost competitive material and possess the desired properties. The mechanical properties largely depend upon composition of alloys and their processing method. Alloy design involves controlling mechanical properties via optimization of the composition and processing parameters. For optimization the possible root is empirical modeling and its more refined version is the analysis of the wide range of data using ANN (Artificial Neural Networks) modeling. The modeling of mechanical properties of the aluminum alloys are the main objective of present work. For this purpose, some data were collected and experimentally prepared using conventional casting method. A MLP (Multilayer Perceptron) network was developed, which is trained by using the error back propagation algorithm. (author)

  6. Electromechanical properties of carbon nanotube networks under compression

    Czech Academy of Sciences Publication Activity Database

    Slobodian, P.; Říha, Pavel; Olejník, R.; Sáha, P.

    2011-01-01

    Roč. 22, č. 12 (2011), s. 124006 ISSN 0957-0233 R&D Projects: GA AV ČR IAA200600803 Grant - others:Interní grantová agentura UTB(CZ) IGA/12/FT/10/D; OP VaVpI(XE) CZ.1.05/2.1.00/03.0111 Institutional research plan: CEZ:AV0Z20600510 Keywords : carbon nanotube network * compression * electrical conductivity * stress sensor Subject RIV: JB - Sensor s, Measurment, Regulation Impact factor: 1.494, year: 2011

  7. Dielectric and conductivity properties of composite polyaniline/polyurethane network

    Science.gov (United States)

    Liang, C.; Gest, J.; Leroy, G.; Carru, J.-C.

    2013-09-01

    In this work, we present the dielectric characterization of polyaniline/polyurethane composite. The samples consisting of 0.5%, 1%, and 5% of polyaniline were deposited on glass fiber, and the measurements were performed in a frequency range of 20 Hz to 20 GHz. The results showed a dielectric relaxation strongly dependent on the concentration of polyaniline. This phenomenon is explained by a theoretical model. In this model, we assume that the alternative conductivity of the polymer network systems is due to conducting clusters whose lengths followed a Gaussian distribution. Depending on their size and the frequency of the excitation signal, the clusters showed a resistive or capacitive effect.

  8. Fractal properties of percolation clusters in Euclidian neural networks

    International Nuclear Information System (INIS)

    Franovic, Igor; Miljkovic, Vladimir

    2009-01-01

    The process of spike packet propagation is observed in two-dimensional recurrent networks, consisting of locally coupled neuron pools. Local population dynamics is characterized by three key parameters - probability for pool connectedness, synaptic strength and neuron refractoriness. The formation of dynamic attractors in our model, synfire chains, exhibits critical behavior, corresponding to percolation phase transition, with probability for non-zero synaptic strength values representing the critical parameter. Applying the finite-size scaling method, we infer a family of critical lines for various synaptic strengths and refractoriness values, and determine the Hausdorff-Besicovitch fractal dimension of the percolation clusters.

  9. More randomized and resilient in the topological properties of functional brain networks in patients with major depressive disorder.

    Science.gov (United States)

    Li, Huaizhou; Zhou, Haiyan; Yang, Yang; Wang, Haiyuan; Zhong, Ning

    2017-10-01

    Previous studies have reported the enhanced randomization of functional brain networks in patients with major depressive disorder (MDD). However, little is known about the changes of key nodal attributes for randomization, the resilience of network, and the clinical significance of the alterations. In this study, we collected the resting-state functional MRI data from 19 MDD patients and 19 healthy control (HC) individuals. Graph theory analysis showed that decreases were found in the small-worldness, clustering coefficient, local efficiency, and characteristic path length (i.e., increase of global efficiency) in the network of MDD group compared with HC group, which was consistent with previous findings and suggested the development toward randomization in the brain network in MDD. In addition, the greater resilience under the targeted attacks was also found in the network of patients with MDD. Furthermore, the abnormal nodal properties were found, including clustering coefficients and nodal efficiencies in the left orbital superior frontal gyrus, bilateral insula, left amygdala, right supramarginal gyrus, left putamen, left posterior cingulate cortex, left angular gyrus. Meanwhile, the correlation analysis showed that most of these abnormal areas were associated with the clinical status. The observed increased randomization and resilience in MDD might be related to the abnormal hub nodes in the brain networks, which were attacked by the disease pathology. Our findings provide new evidence to indicate that the weakening of specialized regions and the enhancement of whole brain integrity could be the potential endophenotype of the depressive pathology. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Physical Properties of 3D Interconnected Graphite Networks - Aerographite

    Science.gov (United States)

    2015-10-30

    resistance could be observed. The dielectric properties are studied using AC impedance spectroscopy. A low capacitance can be measured that refers to...current frequency ..................................................... 17 Figure 3.11: Parallel circuit of resistance and capacitor (left) and...release; distribution is unlimited. Figure 3.11: Parallel circuit of resistance and capacitor (left) and Nyquist plot of reactance against re- sistance

  11. Node-node correlations and transport properties in scale-free networks

    Science.gov (United States)

    Obregon, Bibiana; Guzman, Lev

    2011-03-01

    We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

  12. Computing and the electrical transport properties of coupled quantum networks

    Science.gov (United States)

    Cain, Casey Andrew

    In this dissertation a number of investigations were conducted on ballistic quantum networks in the mesoscopic range. In this regime, the wave nature of electron transport under the influence of transverse magnetic fields leads to interesting applications for digital logic and computing circuits. The work specifically looks at characterizing a few main areas that would be of interest to experimentalists who are working in nanostructure devices, and is organized as a series of papers. The first paper analyzes scaling relations and normal mode charge distributions for such circuits in both isolated and open (terminals attached) form. The second paper compares the flux-qubit nature of quantum networks to the well-established spintronics theory. The results found exactly contradict the conventional school of thought for what is required for quantum computation. The third paper investigates the requirements and limitations of extending the Thevenin theorem in classic electric circuits to ballistic quantum transport. The fourth paper outlines the optimal functionally complete set of quantum circuits that can completely satisfy all sixteen Boolean logic operations for two variables.

  13. Spinal cellular and network properties modulate pain perception

    Directory of Open Access Journals (Sweden)

    Darbon Pascal

    2016-01-01

    Previously, it has been shown that high levels of plasma glucocorticoids give rise to analgesia. However to our knowledge nothing has been reported regarding a direct non genomic modulation of neuronal spinal activity by peripheral CORT. In the present study, we used combined in vivo and in vitro electrophysiology approaches, associated with the measure of nociceptive mechanical sensitivity and plasma corticosterone level measurement to assess the impact of circulating CORT on rat nociception. We showed that CORT plasma level elevation produced analgesia via the reduction of nociceptive fiber mediated spinal responses. CORT is spinally reduced in the neuroactive metabolite THDOC that specifically enhances lamina II GABAergic synaptic transmission. The main consequence is a reduction of lamina II network excitability reflecting a selective decrease in processing of nociceptive inputs. The depressed neuronal activity at the spinal level then in turn leads to a weaker nociceptive message transmission to supraspinal structures and hence to an alleviation of pain.

  14. Size-dependent mechanical properties of 2D random nanofibre networks

    International Nuclear Information System (INIS)

    Lu, Zixing; Zhu, Man; Liu, Qiang

    2014-01-01

    The mechanical properties of nanofibre networks (NFNs) are size dependent with respect to different fibre diameters. In this paper, a continuum model is developed to reveal the size-dependent mechanical properties of 2D random NFNs. Since such size-dependent behaviours are attributed to different micromechanical mechanisms, the surface effects and the strain gradient (SG) effects are, respectively, introduced into the mechanical analysis of NFNs. Meanwhile, a modified fibre network model is proposed, in which the axial, bending and shearing deformations are incorporated. The closed-form expressions of effective modulus and Poisson's ratio are obtained for NFNs. Different from the results predicted by conventional fibre network model, the present model predicts the size-dependent mechanical properties of NFNs. It is found that both surface effects and SG effects have significant influences on the effective mechanical properties. Moreover, the present results show that the shearing deformation of fibre segment is also crucial to precisely evaluate the effective mechanical properties of NFNs. This work mainly aims to provide an insight into the micromechanical mechanisms of NFNs. Besides, this work is also expected to provide a more accurate theoretical model for 2D fibre networks. (paper)

  15. Proposta de um quadro de referência para integrar o consumidor nos conceitos de redes [Proposed Reference Table to Include the Consumer in Network Concepts

    Directory of Open Access Journals (Sweden)

    Ernesto Michelangelo Giglio

    2011-06-01

    Full Text Available O artigo apresenta uma proposta e defesa da inclusão do ator consumidor nos raciocínios e pesquisas sobre redes, a partir da teoria das redes sociais. A proposta decorre da análise e reflexão sobre 82 artigos de redes selecionados, cujos objetivos incluíam o consumidor. Esta análise mostrou que o consumidor está ausente como ator, tanto teoricamente, quanto nas sugestões gerenciais. Seu papel na rede é secundário e são raros os estudos sobre a gestão de sua participação. Entre as causas dessa ausência, destacam-se a dominância de modelos sócio técnicos de redes na bibliografia e o uso de teorias da psicologia do indivíduo, quando se aborda o consumidor, o que se entende como inadequado num raciocínio de redes a partir das redes sociais. Nas conclusões, propõe-se um conjunto de princípios que inclui o consumidor como ator da rede, ampliando o campo de reflexões e de pesquisas da área. --- Proposed Reference Table to Include the Consumer in Network Concepts --- Abstract --- The article presents a model that includes the consumer in the principles and research on networks, using the concepts of social networks. The model arises from the analysis and reflections of 82 articles about networks, whose objectives included the consumer. It showed that he/she is absent as an actor in both theoretically and management proposals. His/her role in the network is secondary and there are few studies into the management of his/her participation. Among the causes of this absence we identify the dominance of socio-technical models in the bibliography and the use of theories of individual psychology, which are inadequate in a reasoning of social networks. Finally we propose a set of principles that includes the consumer as an actor in a network, widening the reflections and research in this area.

  16. Prediction of thermophysical properties of mixed refrigerants using artificial neural network

    International Nuclear Information System (INIS)

    Sencan, Arzu; Koese, Ismail Ilke; Selbas, Resat

    2011-01-01

    The determination of thermophysical properties of the refrigerants is very important for thermodynamic analysis of vapor compression refrigeration systems. In this paper, an artificial neural network (ANN) is proposed to determine properties as heat conduction coefficient, dynamic viscosity, kinematic viscosity, thermal diffusivity, density, specific heat capacity of refrigerants. Five alternative refrigerants are considered: R413A, R417A, R422A, R422D and R423A. The training and validation were performed with good accuracy. The thermophysical properties of the refrigerants are formulated using artificial neural network (ANN) methodology. Liquid and vapor thermophysical properties of refrigerants with new formulation obtained from ANN can be easily estimated. The method proposed offers more flexibility and therefore thermodynamic analysis of vapor compression refrigeration systems is fairly simplified.

  17. Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

    Science.gov (United States)

    Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

    2012-06-01

    This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

  18. The transcriptional regulatory network in the drought response and its crosstalk in abiotic stress responses including drought, cold and heat

    Directory of Open Access Journals (Sweden)

    Kazuo eNakashima

    2014-05-01

    Full Text Available Drought negatively impacts plant growth and the productivity of crops around the world. Understanding the molecular mechanisms in the drought response is important for improvement of drought tolerance using molecular techniques. In plants, abscisic acid (ABA is accumulated under osmotic stress conditions caused by drought, and has a key role in stress responses and tolerance. Comprehensive molecular analyses have shown that ABA regulates the expression of many genes under osmotic stress conditions, and the ABA-responsive element (ABRE is the major cis-element for ABA-responsive gene expression. Transcription factors (TFs are master regulators of gene expression. ABRE-binding protein (AREB and ABRE-binding factor (ABF TFs control gene expression in an ABA-dependent manner. SNF1-related protein kinases 2, group A 2C-type protein phosphatases, and ABA receptors were shown to control the ABA signaling pathway. ABA-independent signaling pathways such as dehydration-responsive element-binding protein (DREB TFs and NAC TFs are also involved in stress responses including drought, heat and cold. Recent studies have suggested that there are interactions between the major ABA signaling pathway and other signaling factors in stress responses. The important roles of these transcription factors in crosstalk among abiotic stress responses will be discussed. Control of ABA or stress signaling factor expression can improve tolerance to environmental stresses. Recent studies using crops have shown that stress-specific overexpression of TFs improves drought tolerance and grain yield compared with controls in the field.

  19. The transcriptional regulatory network in the drought response and its crosstalk in abiotic stress responses including drought, cold, and heat.

    Science.gov (United States)

    Nakashima, Kazuo; Yamaguchi-Shinozaki, Kazuko; Shinozaki, Kazuo

    2014-01-01

    Drought negatively impacts plant growth and the productivity of crops around the world. Understanding the molecular mechanisms in the drought response is important for improvement of drought tolerance using molecular techniques. In plants, abscisic acid (ABA) is accumulated under osmotic stress conditions caused by drought, and has a key role in stress responses and tolerance. Comprehensive molecular analyses have shown that ABA regulates the expression of many genes under osmotic stress conditions, and the ABA-responsive element (ABRE) is the major cis-element for ABA-responsive gene expression. Transcription factors (TFs) are master regulators of gene expression. ABRE-binding protein and ABRE-binding factor TFs control gene expression in an ABA-dependent manner. SNF1-related protein kinases 2, group A 2C-type protein phosphatases, and ABA receptors were shown to control the ABA signaling pathway. ABA-independent signaling pathways such as dehydration-responsive element-binding protein TFs and NAC TFs are also involved in stress responses including drought, heat, and cold. Recent studies have suggested that there are interactions between the major ABA signaling pathway and other signaling factors in stress responses. The important roles of these TFs in crosstalk among abiotic stress responses will be discussed. Control of ABA or stress signaling factor expression can improve tolerance to environmental stresses. Recent studies using crops have shown that stress-specific overexpression of TFs improves drought tolerance and grain yield compared with controls in the field.

  20. Fractal properties and small-scale structure of cosmic string networks

    International Nuclear Information System (INIS)

    Martins, C.J.A.P.; Shellard, E.P.S.

    2006-01-01

    We present results from a detailed numerical study of the small-scale and loop production properties of cosmic string networks, based on the largest and highest resolution string simulations to date. We investigate the nontrivial fractal properties of cosmic strings, in particular, the fractal dimension and renormalized string mass per unit length, and we also study velocity correlations. We demonstrate important differences between string networks in flat (Minkowski) spacetime and the two very similar expanding cases. For high resolution matter era network simulations, we provide strong evidence that small-scale structure has converged to 'scaling' on all dynamical length scales, without the need for other radiative damping mechanisms. We also discuss preliminary evidence that the dominant loop production size is also approaching scaling

  1. NARX neural network Prediction of SYMH and ASYH indices for geomagnetic storms of solar cycle 24 including recent St. Patrick's day, 2015 storm

    Science.gov (United States)

    Bhaskar, A. T.; Vichare, G.

    2017-12-01

    Here, an attempt is made to develop a prediction model for SYMH and ASYH geomagnetic indices using Artificial Neural Network (ANN). SYMH and ASYH indices represent longitudinal symmetric and asymmetric component of the ring current. The ring current state depends on its past conditions therefore, it is necessary to consider its history for prediction. To account this effect Nonlinear Autoregressive Network with eXogenous inputs (NARX) is implemented. This network considers input history of 30 minutes and output feedback of 120 minutes. Solar wind parameters mainly velocity, density and interplanetary magnetic field are used as inputs. SYMH and ASYH indices during geomagnetic storms of 1998-2013, having minimum SYMH training two independent networks. We present the prediction of SYMH and ASYH indices during 9 geomagnetic storms of solar cycle 24 including the recent largest storm occurred on St. Patrick's day, 2015. The present prediction model reproduces the entire time profile of SYMH and ASYH indices along with small variations of 10-30 minutes to good extent within noise level, indicating significant contribution of interplanetary sources and past state of the magnetosphere. However, during the main phase of major storms, residuals (observed-modeled) are found to be large, suggesting influence of internal factors such as magnetospheric processes.

  2. Interconnected networks

    CERN Document Server

    2016-01-01

    This volume provides an introduction to and overview of the emerging field of interconnected networks which include multi layer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave – understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant – for example regarding diffusion, robustness and competition – the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

  3. Fabrication and properties of carbon network reinforced composite fuel

    International Nuclear Information System (INIS)

    Umer, Malik Adeel; Mistarihi, Qusai Mahmoud; Kim, Joon Hui; Hong, Soon Hyung; Ryu, Ho Jin

    2014-01-01

    Zirconium dioxide composites reinforced with 3D glassy carbon foam was fabricated using Spark Plasma Sintering (SPS) with a heating rate of 100degC/min and a uniaxial pressure of 50 MPa at 1500degC, 1600degC, and 1700degC, respectively. The effect of carbon foam on the thermal properties of the ZrO 2 composites was investigated. In addition, the effect of the sintering temperature on the densification of the composites was also investigated and the optimized sintering temperature was identified. The microstructures of 3D carbon foam reinforced ZrO 2 composites showed that the 3D shape of carbon foam was retained after the sintering process, and the ZrO 2 was homogeneously distributed within the 3D carbon foam. At the interfaces between the 3D carbon foam and ZrO 2 , neither a chemical reaction nor a new phase formation was detected by Scanning Electron Microscopy (SEM) and X-ray Diffractometry (XRD). The thermal diffusivity of carbon foam reinforced ZrO 2 composites measured at 1100degC was increased by 47% and reached to 0.66 mm 2 s -1 and the thermal conductivity was increased by 50% and reached to 2.428 W/m-K. (author)

  4. Short-term memory capacity in networks via the restricted isometry property.

    Science.gov (United States)

    Charles, Adam S; Yap, Han Lun; Rozell, Christopher J

    2014-06-01

    Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.

  5. Variations in Carabidae assemblages across the farmland habitats in relation to selected environmental variables including soil properties

    Directory of Open Access Journals (Sweden)

    Beáta Baranová

    2018-03-01

    Full Text Available The variations in ground beetles (Coleoptera: Carabidae assemblages across the three types of farmland habitats, arable land, meadows and woody vegetation were studied in relation to vegetation cover structure, intensity of agrotechnical interventions and selected soil properties. Material was pitfall trapped in 2010 and 2011 on twelve sites of the agricultural landscape in the Prešov town and its near vicinity, Eastern Slovakia. A total of 14,763 ground beetle individuals were entrapped. Material collection resulted into 92 Carabidae species, with the following six species dominating: Poecilus cupreus, Pterostichus melanarius, Pseudoophonus rufipes, Brachinus crepitans, Anchomenus dorsalis and Poecilus versicolor. Studied habitats differed significantly in the number of entrapped individuals, activity abundance as well as representation of the carabids according to their habitat preferences and ability to fly. However, no significant distinction was observed in the diversity, evenness neither dominance. The most significant environmental variables affecting Carabidae assemblages species variability were soil moisture and herb layer 0-20 cm. Another best variables selected by the forward selection were intensity of agrotechnical interventions, humus content and shrub vegetation. The other from selected soil properties seem to have just secondary meaning for the adult carabids. Environmental variables have the strongest effect on the habitat specialists, whereas ground beetles without special requirements to the habitat quality seem to be affected by the studied environmental variables just little.

  6. The investigation of gamma and neutron shielding properties of concrete including basalt fibre for nuclear energy applications

    International Nuclear Information System (INIS)

    Nulk, H.; Ipbuker, C.; Gulik, V.; Tkaczyk, A.; Biland, A.

    2015-01-01

    In this study, we would like to draw attention to the prospect of basalt fibre as the main component for concrete reinforcement of NPP. This work describes the computational study of gamma attenuation parameters, the effective atomic number Z(eff) and the effective electron density N e (eff), of relatively light-weight concrete with chopped basalt fibre used as reinforcement in different mixture rates. We can draw the following conclusions. Basalt fibre is a relatively cheap material that can be used as reinforcement instead of metallic fibers. Basalt fibre has a similar specific gravity to that of concrete elements. Basalt fibre has high chemical and abrasion resistance. Basalt fibre has almost 10 times the tensile strength of steel re-bars. Gamma-ray attenuation coefficients increase with addition of basalt fibre into concrete in every case. The effective atomic number of the concrete increases with the addition of basalt fibre. The results show that basalt fibre reinforced concrete have improved shielding properties against gamma rays in comparison with regular concrete. This result is based on a regular concrete with only basalt fiber reinforcement. We estimate that with addition of standard aggregates for radiation shielding concrete, such as barite, magnetite or hematite, the shielding properties will increase exponentially

  7. Psychometric properties including reliability, validity and responsiveness of the Majeed pelvic score in patients with chronic sacroiliac joint pain.

    Science.gov (United States)

    Bajada, Stefan; Mohanty, Khitish

    2016-06-01

    The Majeed scoring system is a disease-specific outcome measure that was originally designed to assess pelvic injuries. The aim of this study was to determine the psychometric properties of the Majeed scoring system for chronic sacroiliac joint pain. Internal consistency, content validity, criterion validity, construct validity and responsiveness to change was assessed prospectively for the Majeed scoring system in a cohort of 60 patients diagnosed with sacroiliac joint pain. This diagnosis was confirmed with CT-guided sacroiliac joint anaesthetic block. The overall Majeed score showed acceptable internal consistency (Cronbach alpha = 0.63). Similarly, it showed acceptable floor (0 %) and ceiling (0 %) effects. On the other hand, the domains of pain, work, sitting and sexual intercourse had high (>30 %) floor effects. Significant correlation with the physical component of the Short Form-36 (p = 0.005) and Oswestry disability index (p ≤ 0.001) was found indicating acceptable criterion validity. The overall Majeed score showed acceptable construct validity with all five developed hypotheses showing significance (p ≤ 0.05). The overall Majeed score showed acceptable responsiveness to change with a large (≥0.80) effect size and standardized response mean. Overall the Majeed scoring system demonstrated acceptable psychometric properties for outcome assessment in chronic sacroiliac joint pain. Thus, its use in this condition is adequate. However, some domains demonstrated suboptimal performance indicating that improvement might be achieved with the development of an outcome measure specific for sacroiliac joint dysfunction and degeneration.

  8. ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Garrett B.; Siegel, Charles M.; Vishnu, Abhinav; Hodas, Nathan O.

    2017-12-08

    With access to large datasets, deep neural networks through representation learning have been able to identify patterns from raw data, achieving human-level accuracy in image and speech recognition tasks. However, in chemistry, availability of large standardized and labelled datasets is scarce, and with a multitude of chemical properties of interest, chemical data is inherently small and fragmented. In this work, we explore transfer learning techniques in conjunction with the existing Chemception CNN model, to create a transferable and generalizable deep neural network for small-molecule property prediction. Our latest model, ChemNet learns in a semi-supervised manner from inexpensive labels computed from the ChEMBL database. When fine-tuned to the Tox21, HIV and FreeSolv dataset, which are 3 separate chemical tasks that ChemNet was not originally trained on, we demonstrate that ChemNet exceeds the performance of existing Chemception models, contemporary MLP models that trains on molecular fingerprints, and it matches the performance of the ConvGraph algorithm, the current state-of-the-art. Furthermore, as ChemNet has been pre-trained on a large diverse chemical database, it can be used as a universal “plug-and-play” deep neural network, which accelerates the deployment of deep neural networks for the prediction of novel small-molecule chemical properties.

  9. Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

    Science.gov (United States)

    Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

  10. Best Signal Quality in Cellular Networks: Asymptotic Properties and Applications to Mobility Management in Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Baccelli François

    2010-01-01

    Full Text Available The quickly increasing data traffic and the user demand for a full coverage of mobile services anywhere and anytime are leading mobile networking into a future of small cell networks. However, due to the high-density and randomness of small cell networks, there are several technical challenges. In this paper, we investigate two critical issues: best signal quality and mobility management. Under the assumptions that base stations are uniformly distributed in a ring-shaped region and that shadowings are lognormal, independent, and identically distributed, we prove that when the number of sites in the ring tends to infinity, then (i the maximum signal strength received at the center of the ring tends in distribution to a Gumbel distribution when properly renormalized, and (ii it is asymptotically independent of the interference. Using these properties, we derive the distribution of the best signal quality. Furthermore, an optimized random cell scanning scheme is proposed, based on the evaluation of the optimal number of sites to be scanned for maximizing the user data throughput.

  11. Social network properties and self-rated health in later life: comparisons from the Korean social life, health, and aging project and the national social life, health and aging project.

    Science.gov (United States)

    Youm, Yoosik; Laumann, Edward O; Ferraro, Kenneth F; Waite, Linda J; Kim, Hyeon Chang; Park, Yeong-Ran; Chu, Sang Hui; Joo, Won-Tak; Lee, Jin A

    2014-09-14

    This paper has two objectives. Firstly, it provides an overview of the social network module, data collection procedures, and measurement of ego-centric and complete-network properties in the Korean Social Life, Health, and Aging Project (KSHAP). Secondly, it directly compares the KSHAP structure and results to the ego-centric network structure and results of the National Social Life, Health, and Aging Project (NSHAP), which conducted in-home interviews with 3,005 persons 57 to 85 years of age in the United States. The structure of the complete social network of 814 KSHAP respondents living in Township K was measured and examined at two levels of networks. Ego-centric network properties include network size, composition, volume of contact with network members, density, and bridging potential. Complete-network properties are degree centrality, closeness centrality, betweenness centrality, and brokerage role. We found that KSHAP respondents with a smaller number of social network members were more likely to be older and tended to have poorer self-rated health. Compared to the NSHAP, the KSHAP respondents maintained a smaller network size with a greater network density among their members and lower bridging potential. Further analysis of the complete network properties of KSHAP respondents revealed that more brokerage roles inside the same neighborhood (Ri) were significantly associated with better self-rated health. Socially isolated respondents identified by network components had the worst self-rated health. The findings demonstrate the importance of social network analysis for the study of older adults' health status in Korea. The study also highlights the importance of complete-network data and its ability to reveal mechanisms beyond ego-centric network data.

  12. Spectroscopic and electric properties of the LiCs molecule: a coupled cluster study including higher excitations

    Science.gov (United States)

    Sørensen, L. K.; Fleig, T.; Olsen, J.

    2009-08-01

    Aimed at obtaining complete and highly accurate potential energy surfaces for molecules containing heavy elements, we present a new general-order coupled cluster method which can be applied in the framework of the spin-free Dirac formalism. As an initial application we present a systematic study of electron correlation and relativistic effects on the spectroscopic and electric properties of the LiCs molecule in its electronic ground state. In particular, we closely investigate the importance of excitations higher than coupled cluster doubles, spin-free and spin-dependent relativistic effects and the correlation of outer-core electrons on the equilibrium bond length, the harmonic vibrational frequency, the dissociation energy, the dipole moment and the static electric dipole polarizability. We demonstrate that our new implementation allows for highly accurate calculations not only in the bonding region but also along the complete potential curve. The quality of our results is demonstrated by a vibrational analysis where an almost complete set of vibrational levels has been calculated accurately.

  13. Spectroscopic and electric properties of the LiCs molecule: a coupled cluster study including higher excitations

    International Nuclear Information System (INIS)

    Soerensen, L K; Fleig, T; Olsen, J

    2009-01-01

    Aimed at obtaining complete and highly accurate potential energy surfaces for molecules containing heavy elements, we present a new general-order coupled cluster method which can be applied in the framework of the spin-free Dirac formalism. As an initial application we present a systematic study of electron correlation and relativistic effects on the spectroscopic and electric properties of the LiCs molecule in its electronic ground state. In particular, we closely investigate the importance of excitations higher than coupled cluster doubles, spin-free and spin-dependent relativistic effects and the correlation of outer-core electrons on the equilibrium bond length, the harmonic vibrational frequency, the dissociation energy, the dipole moment and the static electric dipole polarizability. We demonstrate that our new implementation allows for highly accurate calculations not only in the bonding region but also along the complete potential curve. The quality of our results is demonstrated by a vibrational analysis where an almost complete set of vibrational levels has been calculated accurately.

  14. Mechanical and chemical properties of polyvinyl alcohol modified cement mortar with silica fume used as matrix including radioactive waste

    International Nuclear Information System (INIS)

    Dakroury, A. M.

    2007-01-01

    This paper discussed the mechanical and chemical properties of polyvinyl alcohol - modified cement mortar with silica fume to assess the safety for disposal of radioactive waste. The modified cement mortars containing polyvinyl alcohol (PVA) in the presence of 10 % silica fume (SF) .The chemical reaction between polymer and cement - hydrated product were investigated by the Infrared Spectral Technology, Differential Thermal Analysis and X-ray diffraction. The leaching of 137Cs from a waste composite into a surrounding fluid has been studied .The results shown that PVA increases the strength and decreases the porosity. The increase in strength duo to the interaction of PVA with cement , may be forming some new compound that fill the pores or improve the bond between the cement . The pozzolanic reaction of the SF increases the calcium silicate hydrates in the hardening matrix composites. There is distinct change in the refinement of the pore structure in cement composites giving fewer capillary pores and more of the finer gel pores

  15. Spectroscopic and electric dipole properties of Sr+Ar and SrAr systems including high excited states

    Science.gov (United States)

    Hamdi, Rafika; Abdessalem, Kawther; Dardouri, Riadh; Al-Ghamdi, Attieh A.; Oujia, Brahim; Gadéa, Florent Xavier

    2018-01-01

    The spectroscopic properties of the fundamental and several excited states of Sr+Ar and SrAr, Van der Waals systems are investigated by employing an ab initio method in a pseudo-potential approach. The potential energy curves and the spectroscopic parameters are displayed for the 1-10 2Σ+, 1-6 2Π and 1-3 2Δ electronic states of the Sr+Ar molecule and for the 1-6 1Σ+, 1-4 3Σ+, 1-3 1,3Π and 1-3 1,3Δ states of the neutral molecule SrAr. In addition, from these curves, the vibrational levels and their energy spacing are deduced for Σ+, Π and Δ symmetries. The spectra of the permanent and transition dipole moments are studied for the 1,3Σ+ states of SrAr, which are considered to be two-electron systems and 2Σ+ states of the single electron Sr+Ar ion. The spectroscopic parameters obtained for each molecular system are compared with previous theoretical and experimental works. A significant correlation revealed the accuracy of our results.

  16. Network access charges, vertical integration, and property rights structure - experiences from the German electricity markets

    International Nuclear Information System (INIS)

    Growitsch, C.; Wein, T.

    2005-01-01

    After the deregulation of the German electricity markets in 1998, the German government opted for a regulatory regime called negotiated third party access, which would be subject to ex-post control by the federal cartel office. Network access charges for new competitors are based on contractual arrangements between energy producers and industrial consumers. As the electricity networks are incontestable natural monopolies, the local and regional network operators are able to set (monopolistic) charges at their own discretion, restricted only by the possible interference of the federal cartel office (Bundeskartellamt). In this paper we analyze if there is evidence for varying charging behaviour depending on the supplier's economic independence (structure of property rights) or its level of vertical integration. For this purpose, we hypothesise that incorporated and vertically integrated suppliers set different charges than independent utility companies. Multivariate estimations show a relation between network access charges and the network operator's economic independence as well as level of vertical integration: on the low voltage level for an estimated annual consumption of 1700 kW/h, vertically integrated firms set-in accordance with our hypothesis-significantly lower access charges than vertically separated suppliers, whereas incorporated network operators charge significantly higher charges compared to independent suppliers. These results could not have been confirmed for other consumptions or voltage levels. (author)

  17. Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.

    Directory of Open Access Journals (Sweden)

    Ryan C Williamson

    2016-12-01

    Full Text Available Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction-shared dimensionality and percent shared variance-with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.

  18. Mixed random walks with a trap in scale-free networks including nearest-neighbor and next-nearest-neighbor jumps

    Science.gov (United States)

    Zhang, Zhongzhi; Dong, Yuze; Sheng, Yibin

    2015-10-01

    Random walks including non-nearest-neighbor jumps appear in many real situations such as the diffusion of adatoms and have found numerous applications including PageRank search algorithm; however, related theoretical results are much less for this dynamical process. In this paper, we present a study of mixed random walks in a family of fractal scale-free networks, where both nearest-neighbor and next-nearest-neighbor jumps are included. We focus on trapping problem in the network family, which is a particular case of random walks with a perfect trap fixed at the central high-degree node. We derive analytical expressions for the average trapping time (ATT), a quantitative indicator measuring the efficiency of the trapping process, by using two different methods, the results of which are consistent with each other. Furthermore, we analytically determine all the eigenvalues and their multiplicities for the fundamental matrix characterizing the dynamical process. Our results show that although next-nearest-neighbor jumps have no effect on the leading scaling of the trapping efficiency, they can strongly affect the prefactor of ATT, providing insight into better understanding of random-walk process in complex systems.

  19. Preparation and its drug release property of radiation-polymerized poly(methyl methacrylate) capsule including potassium chloride

    International Nuclear Information System (INIS)

    Yoshida, Masaru; Kumakura, Minoru; Kaetsu, Isao

    1979-01-01

    Porous flat circular capsules including KCl as a drug were prepared by radiation-induced polymerization of methyl methacrylate at room temperature in the presence of polyethylene glycol No. 600. The porous structure can be controlled by the methyl methacrylate-polyethylene glycol No. 600 composition. The amount of drug released was linearly related to the square root of time. The magnitude of drug release increased roughly in proportional to the water content of capsule, which can be related to porosity in the capsule. (author)

  20. Fermented soybean meal exhibits probiotic properties when included in Japanese quail diet in replacement of soybean meal.

    Science.gov (United States)

    Jazi, V; Ashayerizadeh, A; Toghyani, M; Shabani, A; Tellez, G; Toghyani, M

    2018-03-15

    This study was conducted to investigate and compare the effect of dietary probiotic mixture (PM) and organic acid (OA) mixture with fermented soybean meal (FSBM) on performance, crop, and ceca microbiota, small intestine morphology, and serum lipid profile in Japanese quails. A total of 800 day-old Japanese quails was randomly allotted to 5 treatments with 8 replicate pens of 20 birds each, for 35 days. The experimental diets consisted of a control corn-soybean meal diet and 4 test diets: 1) control diet + 0.1% PM; 2) control diet + 0.2% OA mixture; 3) control diet + the combination of both PM and OA; and 4) an additives-free diet in which the soybean meal in the control diet was replaced with FSBM. The results indicated that in starter and the entire rearing periods, FSBM, PM, and PM+OA diets had significantly lower FCR compared to control or OA diets (P < 0.05). Birds in the FSBM group gained higher weight than control and OA birds (P < 0.05; 1 to 35 d). At d 21 and 35, birds fed the control diet showed significantly lower numbers of lactic acid bacteria in the crop, while coliforms were higher in the cecal content compared to the other diets (P < 0.05). At d 21, the villus height and villus height to crypt depth ratio in the duodenum and jejunum of birds fed PM, PM+OA, and FSBM diets were greater than in other treatments (P < 0.05). The serum concentrations of cholesterol and low-density lipoprotein cholesterol of birds fed PM, PM+OA, and FSBM diets were significantly lower than birds in control and AO groups (P < 0.05). The results obtained herein suggest that FSBM exhibits probiotic properties and, when used in substitution of SBM in Japanese quail diet, can improve growth performance, balance of desirable gastrointestinal microbiota in crop and ceca, small intestinal morphology, and serum lipid profile-likewise, a probiotic supplement.

  1. Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

    Science.gov (United States)

    Xie, Tian; Grossman, Jeffrey C.

    2018-04-01

    The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

  2. Meso-decorated self-healing gels: network structure and properties

    Science.gov (United States)

    Gong, Jin; Sawamura, Kensuke; Igarashi, Susumu; Furukawa, Hidemitsu

    2013-04-01

    Gels are a new material having three-dimensional network structures of macromolecules. They possess excellent properties as swellability, high permeability and biocompatibility, and have been applied in various fields of daily life, food, medicine, architecture, and chemistry. In this study, we tried to prepare new multi-functional and high-strength gels by using Meso-Decoration (Meso-Deco), one new method of structure design at intermediate mesoscale. High-performance rigid-rod aromatic polymorphic crystals, and the functional groups of thermoreversible Diels-Alder reaction were introduced into soft gels as crosslinkable pendent chains. The functionalization and strengthening of gels can be realized by meso-decorating the gels' structure using high-performance polymorphic crystals and thermoreversible pendent chains. New gels with good mechanical properties, novel optical properties and thermal properties are expected to be developed.

  3. The effects of topology on the structural, dynamic and mechanical properties of network-forming materials

    International Nuclear Information System (INIS)

    Wilson, Mark

    2012-01-01

    The effects of network topology on the static structural, mechanical and dynamic properties of MX 2 network-forming liquids (with tetrahedral short-range order) are discussed. The network topology is controlled via a single model parameter (the anion polarizability) which effectively constrains the inter-tetrahedral linkages in a physically transparent manner. Critically, it is found to control the balance between the stability of corner- and edge-sharing tetrahedra. A potential rigidity transformation is investigated. The vibrational density of states is investigated, using an instantaneous normal model analysis, as a function of both anion polarizability and temperature. A low frequency peak is seen to appear and is shown to be correlated with the fraction of cations which are linked through solely edge-sharing structural motifs. A modified effective mean atom coordination number is proposed which allows the appearance of the low frequency feature to be understood in terms of a mean field rigidity percolation threshold. (paper)

  4. Intrinsic properties of channel network structure and the hierarchical classification approach for stream-limits delineation

    Energy Technology Data Exchange (ETDEWEB)

    Afana, A.; Barrio, G. del

    2009-07-01

    Delineation of drainage networks is an essential task in hydrological and geomorphologic analysis. Manual channel definition depends on topographic contrast and is highly subjective, leading to important errors at high resolutions. different automatic methods have proposed the use of a constant threshold of up sole contributing are to define channel initiation. Actually, these are the most commonly used for the automatic-channel network extraction from Digital Models (DEMs). However, these methods fall to detect and appropriate threshold when the basin is made up to heterogeneous sub-zones, as they only work either lumped or locally. In this study, the critical threshold area for channel delineation has been defined through the analysis of dominant geometric and topologic properties of stream network formation. (Author) 5 refs.

  5. Graph theoretical analysis reveals disrupted topological properties of whole brain functional networks in temporal lobe epilepsy.

    Science.gov (United States)

    Wang, Junjing; Qiu, Shijun; Xu, Yong; Liu, Zhenyin; Wen, Xue; Hu, Xiangshu; Zhang, Ruibin; Li, Meng; Wang, Wensheng; Huang, Ruiwang

    2014-09-01

    Temporal lobe epilepsy (TLE) is one of the most common forms of drug-resistant epilepsy. Previous studies have indicated that the TLE-related impairments existed in extensive local functional networks. However, little is known about the alterations in the topological properties of whole brain functional networks. In this study, we acquired resting-state BOLD-fMRI (rsfMRI) data from 26 TLE patients and 25 healthy controls, constructed their whole brain functional networks, compared the differences in topological parameters between the TLE patients and the controls, and analyzed the correlation between the altered topological properties and the epilepsy duration. The TLE patients showed significant increases in clustering coefficient and characteristic path length, but significant decrease in global efficiency compared to the controls. We also found altered nodal parameters in several regions in the TLE patients, such as the bilateral angular gyri, left middle temporal gyrus, right hippocampus, triangular part of left inferior frontal gyrus, left inferior parietal but supramarginal and angular gyri, and left parahippocampus gyrus. Further correlation analysis showed that the local efficiency of the TLE patients correlated positively with the epilepsy duration. Our results indicated the disrupted topological properties of whole brain functional networks in TLE patients. Our findings indicated the TLE-related impairments in the whole brain functional networks, which may help us to understand the clinical symptoms of TLE patients and offer a clue for the diagnosis and treatment of the TLE patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  6. Semi-degradable poly(β-amino ester) networks with temporally controlled enhancement of mechanical properties.

    Science.gov (United States)

    Safranski, David L; Weiss, Daiana; Clark, J Brian; Taylor, W Robert; Gall, Ken

    2014-08-01

    Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss of mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  7. Application of CAPEC Lipid Property Databases in the Synthesis and Design of Biorefinery Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Cunico, Larissa; Gani, Rafiqul

    Petroleum is currently the primary raw material for the production of fuels and chemicals. Consequently, our society is highly dependent on fossil non-renewable resources. However, renewable raw materials are recently receiving increasing interest for the production of chemicals and fuels, so a n...... of biorefinery networks. The objective of this work is to show the application of databases of physical and thermodynamic properties of lipid components to the synthesis and design of biorefinery networks.......]. The wide variety and complex nature of components in biorefineries poses a challenge with respect to the synthesis and design of these types of processes. Whereas physical and thermodynamic property data or models for petroleum-based processes are widely available, most data and models for biobased...

  8. Effect of the metal work function on the electrical properties of carbon nanotube network transistors

    International Nuclear Information System (INIS)

    Kim, Un Jeong; Ko, Dae Young; Kil, Joon Pyo; Lee, Jung Wha; Park, Wan Jun

    2012-01-01

    A nearly perfect semiconducting single-walled carbon nanotube random network thin film transistor array was fabricated, and its reproducible transport properties were investigated. The effects of the metal work function for both the source and the drain on the electrical properties of the transistors were systematically investigated. Three different metal electrodes, Al, Ti, and Pd, were employed. As the metal work function increased, p-type behavior became dominant, and the field effect hole mobility dramatically increased. Also, the Schottky barrier of the Ti-nanotube contact was invariant to the molecular adsorption of species in air.

  9. Methodology for electrical studies in industrial networks including the study of electric arc; Metodologia para los estudios electricos en redes industriales incluyendo el estudio de arco electrico

    Energy Technology Data Exchange (ETDEWEB)

    Rasgado Casique, Jose Pepe; Silva Farias, Jose Luis [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)]. E-mail: jrasgado@iie.org.mx; jlsilva@iie.org.mx

    2010-11-15

    This article presents a methodology for conducting electrical studies in industrial networks. The methodology included the study of arc flash as a very important area of current basic electrical studies, such as power flow, short circuit and coordination. The aim of this study is to determine the Personal Protective Equipment (PPE) and flash protection boundary for personnel working with or near energized equipment, based on the IEEE Std 1584-2004 and NFPA-70E- 2004. Also included are criteria and recommendations to reduce incident energy level (cal/cm{sup 2}). At work we used a distribution network for industrial type test. The studies were carried out using a commercial program for the analysis of electrical networks. [Spanish] En este articulo se presenta una metodologia para llevar a cabo los estudios electricos en redes industriales. En la metodologia se incluye al estudio de arco electrico como un area muy importante de los estudios electricos basicos actuales, como: flujos de potencia, cortocircuito y coordinacion de protecciones. El objetivo de dicho estudio es determinar el Equipo de Proteccion Personal (EPP) apropiado y los limites de proteccion para el personal que opera con o cerca de equipo energizado, con base en las normas IEEE Std. 1584-2004 y la NFPA-70E-2004. Ademas, se incluyen criterios y recomendaciones para disminuir el nivel de energia incidente (cal/cm{sup 2}). En el trabajo se utilizo una red de distribucion tipo industrial de prueba. Los estudios se llevaron a cabo utilizando un programa comercial para el analisis de redes electricas.

  10. Empirical investigation of topological and weighted properties of a bus transport network from China

    Science.gov (United States)

    Shu-Min, Feng; Bao-Yu, Hu; Cen, Nie; Xiang-Hao, Shen; Yu-Sheng, Ci

    2016-03-01

    Many bus transport networks (BTNs) have evolved into directed networks. A new representation model for BTNs is proposed, called directed-space P. The bus transport network of Harbin (BTN-H) is described as a directed and weighted complex network by the proposed representation model and by giving each node weights. The topological and weighted properties are revealed in detail. In-degree and out-degree distributions, in-weight and out-weight distributions are presented as an exponential law, respectively. There is a strong relation between in-weight and in-degree (also between out-weight and out-degree), which can be fitted by a power function. Degree-degree and weight-weight correlations are investigated to reveal that BTN-H has a disassortative behavior as the nodes have relatively high degree (or weight). The disparity distributions of out-degree and in-degree follow an approximate power-law. Besides, the node degree shows a near linear increase with the number of routes that connect to the corresponding station. These properties revealed in this paper can help public transport planners to analyze the status quo of the BTN in nature. Project supported by the National High Technology Research and Development Program of China (Grant No. 2014AA110304).

  11. Thermochemical Stability and Friction Properties of Soft Organosilica Networks for Solid Lubrication

    Directory of Open Access Journals (Sweden)

    Pablo Gonzalez Rodriguez

    2018-01-01

    Full Text Available In view of their possible application as high temperature solid lubricants, the tribological and thermochemical properties of several organosilica networks were investigated over a range of temperatures between 25 and 580 °C. Organosilica networks, obtained from monomers with terminal and bridging organic groups, were synthesized by a sol-gel process. The influence of carbon content, crosslink density, rotational freedom of incorporated hydrocarbon groups, and network connectivity on the high temperature friction properties of the polymer was studied for condensed materials from silicon alkoxide precursors with terminating organic groups, i.e., methyltrimethoxysilane, propyltrimethoxysilane, diisopropyldimethoxysilane, cyclohexyltrimethoxysilane, phenyltrimethoxysilane and 4-biphenylyltriethoxysilane networks, as well as precursors with organic bridging groups between Si centers, i.e., 1,4-bis(triethoxysilylbenzene and 4,4′-bis(triethoxysilyl-1,1′-biphenyl. Pin-on-disc measurements were performed using all selected solid lubricants. It was found that materials obtained from phenyltrimethoxysilane and cyclohexyltrimethoxysilane precursors showed softening above 120 °C and performed best in terms of friction reduction, reaching friction coefficients as low as 0.01. This value is lower than that of graphite films (0.050 ± 0.005, a common bench mark for solid lubricants.

  12. Application of backpropagation neural networks to evaluate residual properties of thermally damaged concrete

    International Nuclear Information System (INIS)

    Vasconcelos, W.L.; Shigaki, Y.; Tolentino, E.

    2009-01-01

    In this work it was analyzed the residual performance of Portland cement concretes, when cold after heat-treated up to 600 deg C. Granite-gneiss was used in the three concrete mix proportions as the coarse aggregate, and river sand with finesses modulus of 2.7 as the fine aggregate. Ultrasonic pulse tests were performed on all the specimens and ultrasonic dynamic modulus were obtained. An artificial neural network of the backpropagation type was trained to evaluate and apply models in predicting residual properties of Portland cement concretes. The input layer for both models consists of an external layer input vector of the temperature. The hidden layer has two processing units with hyperbolic tangent sigmoid transfer functions (tansig for short), and the output layer contains one processing unit that represents the network's output (ultrasonic pulse velocity or modulus of elasticity) for each input vector. The training phase of the network converged for reasonable results after 5.000 epochs approximately, resulting in mean squared errors less than 0.02 for the normalized data. The neural network developed for modeling residual properties of Portland cement concretes was shown to be efficient in both the training phase and the test. From the results reasonable predictions could be made for the ultrasonic pulse velocity or dynamic modulus of elasticity by using temperature. (author)

  13. Microstructure and Mechanical Properties of Heterogeneous Ceramic-Polymer Composite Using Interpenetrating Network

    OpenAIRE

    Kim, Eun-Hee; Jung, Yeon-Gil; Jo, Chang-Yong

    2012-01-01

    Prepolymer, which can be polymerized by a photo, has been infiltrated into a porous ceramic to improve the addition effect of polymer into the ceramic, as a function of the functionality of prepolymer. It induces the increase in the mechanical properties of the ceramic. The porous alumina (Al2O3) and the polyurethane acrylate (PUA) with a network structure by photo-polymerization were used as the matrix and infiltration materials, respectively. The porous Al2O3 matrix without t...

  14. The dependence of the optoelectrical properties of silver nanowire networks on nanowire length and diameter

    International Nuclear Information System (INIS)

    Sorel, Sophie; Lyons, Philip E; De, Sukanta; Coleman, Jonathan N; Dickerson, Janet C

    2012-01-01

    We have characterized the optoelectrical properties of networks of silver nanowires as a function of nanowire dimension by measuring transmittance (T) and sheet resistance (R s ) for a large number of networks of different thicknesses fabricated from wires of different diameters (D) and lengths (L). We have analysed these data using both bulk-like and percolative models. We find the network DC conductivity to scale linearly with wire length while the optical conductivity is approximately invariant with nanowire length. The ratio of DC to optical conductivity, often taken as a figure of merit for transparent conductors, scales approximately as L/D. Interestingly, the percolative exponent, n, scales empirically as D 2 , while the percolative figure of merit, Π, displays large values at low D. As high T and low R s are associated with low n and high Π, these data are consistent with improved optoelectrical performance for networks of low-D wires. We predict that networks of wires with D = 25 nm could give sheet resistance as low as 25 Ω/□ for T = 90%. (paper)

  15. Research on the Topological Properties of Air Quality Index Based on a Complex Network

    Directory of Open Access Journals (Sweden)

    Yongli Zhang

    2018-04-01

    Full Text Available To analyze the dynamic characteristics of air quality for enforcing effective measures to prevent and evade air pollution harm, air quality index (AQI time series data was selected and transformed into a symbol sequence consisting of characters (H, M, L through the coarse graining process; then each 6-symbols series was treated as one vertex by time sequence to construct the AQI directed-weighted network; finally the centrality, clusterability, and ranking of the AQI network were analyzed. The results indicated that vertex strength and cumulative strength distribution, vertex strength and strength rank presented power law distributions, and the AQI network is a scale-free network. Only 17 vertices possessed a higher weighted clustering coefficient; meanwhile weighted clustering coefficient and vertex strength didn’t show a strong correlation. The AQI network did not have an obvious central tendency towards intermediaries in general, but 20.55% of vertices accounted for nearly 1/2 of the intermediaries, and the varieties still existed. The mean distance of 68.4932% of vertices was 6.120–9.973, the AQI network did not have obvious small-world phenomena, the conversion of AQI patterns presented the characteristics of periodicity and regularity, and 20.2055% of vertices had high proximity prestige. The vertices fell into six islands, the AQI pattern indicating heavy or serious air pollution lasting six days always lingered for a long time. The number of triads 2-012 was the largest, and the AQI network followed the transitivity model. The study has instructional significance in understanding time change regulation of air quality in Beijing, opening a new way for time series prediction research. Additionally, the factors causing the change of topological properties should be analyzed in the future research.

  16. Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

    Science.gov (United States)

    Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

    2010-11-01

    The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

  17. The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes.

    Science.gov (United States)

    Veroniki, Areti Angeliki; Straus, Sharon E; Fyraridis, Alexandros; Tricco, Andrea C

    2016-08-01

    To present a novel and simple graphical approach to improve the presentation of the treatment ranking in a network meta-analysis (NMA) including multiple outcomes. NMA simultaneously compares many relevant interventions for a clinical condition from a network of trials, and allows ranking of the effectiveness and/or safety of each intervention. There are numerous ways to present the NMA results, which can challenge their interpretation by research users. The rank-heat plot is a novel graph that can be used to quickly recognize which interventions are most likely the best or worst interventions with respect to their effectiveness and/or safety for a single or multiple outcome(s) and may increase interpretability. Using empirical NMAs, we show that the need for a concise and informative presentation of results is imperative, particularly as the number of competing treatments and outcomes in an NMA increases. The rank-heat plot is an efficient way to present the results of ranking statistics, particularly when a large amount of data is available, and it is targeted to users from various backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Applying network theory to animal movements to identify properties of landscape space use.

    Science.gov (United States)

    Bastille-Rousseau, Guillaume; Douglas-Hamilton, Iain; Blake, Stephen; Northrup, Joseph M; Wittemyer, George

    2018-04-01

    Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a

  19. Knowledge-based artificial neural network model to predict the properties of alpha+ beta titanium alloys

    Energy Technology Data Exchange (ETDEWEB)

    Banu, P. S. Noori; Rani, S. Devaki [Dept. of Metallurgical Engineering, Jawaharlal Nehru Technological University, HyderabadI (India)

    2016-08-15

    In view of emerging applications of alpha+beta titanium alloys in aerospace and defense, we have aimed to develop a Back propagation neural network (BPNN) model capable of predicting the properties of these alloys as functions of alloy composition and/or thermomechanical processing parameters. The optimized BPNN model architecture was based on the sigmoid transfer function and has one hidden layer with ten nodes. The BPNN model showed excellent predictability of five properties: Tensile strength (r: 0.96), yield strength (r: 0.93), beta transus (r: 0.96), specific heat capacity (r: 1.00) and density (r: 0.99). The developed BPNN model was in agreement with the experimental data in demonstrating the individual effects of alloying elements in modulating the above properties. This model can serve as the platform for the design and development of new alpha+beta titanium alloys in order to attain desired strength, density and specific heat capacity.

  20. Microstructure and Mechanical Properties of Heterogeneous Ceramic-Polymer Composite Using Interpenetrating Network

    International Nuclear Information System (INIS)

    Eun-Hee, K.; Yeon-Gil, J.; Chang-Yong, J.

    2012-01-01

    Prepolymer, which can be polymerized by a photo, has been infiltrated into a porous ceramic to improve the addition effect of polymer into the ceramic, as a function of the functionality of prepolymer. It induces the increase in the mechanical properties of the ceramic. The porous alumina (Al 2 O 3 ) and the polyurethane acrylate (PUA) with a network structure by photo-polymerization were used as the matrix and infiltration materials, respectively. The porous Al 2 O 3 matrix without the polymer shows lower values in fracture strength than the composites, since the stress is transmitted more quickly via propagation of cracks from intrinsic defects in the porous matrix. However, in the case of composites, the distribution of stress between hetero phases results in the improved mechanical properties. In addition, the mechanical properties of composites, such as elastic modulus and fracture strength, are enhanced with increasing the functionality of prepolymer attributed to the crosslinking density of polymer.

  1. Conductivity and properties of polysiloxane-polyether cluster-LiTFSI networks as hybrid polymer electrolytes

    Science.gov (United States)

    Boaretto, Nicola; Joost, Christine; Seyfried, Mona; Vezzù, Keti; Di Noto, Vito

    2016-09-01

    This report describes the synthesis and the properties of a series of polymer electrolytes, composed of a hybrid inorganic-organic matrix doped with LiTFSI. The matrix is based on ring-like oligo-siloxane clusters, bearing pendant, partially cross-linked, polyether chains. The dependency of the thermo-mechanic and of the transport properties on several structural parameters, such as polyether chains' length, cross-linkers' concentration, and salt concentration is studied. Altogether, the materials show good thermo-mechanical and electrochemical stabilities, with conductivities reaching, at best, 8·10-5 S cm-1 at 30 °C. In conclusion, the cell performances of one representative sample are shown. The scope of this report is to analyze the correlations between structure and properties in networked and hybrid polymer electrolytes. This could help the design of optimized polymer electrolytes for application in lithium metal batteries.

  2. Characterization of Genotoxic Response to 15 Multiwalled Carbon Nanotubes with Variable Physicochemical Properties Including Surface Functionalizations in the FE1-Muta(TM) Mouse Lung Epithelial Cell Line

    DEFF Research Database (Denmark)

    Jackson, Petra; Kling, Kirsten; Jensen, Keld Alstrup

    2015-01-01

    Carbon nanotubes vary greatly in physicochemical properties. We compared cytotoxic and genotoxic response to 15 multiwalled carbon nanotubes (MWCNT) with varying physicochemical properties to identify drivers of toxic responses. The studied MWCNT included OECD Working Party on Manufactured...... Nanomaterials (WPMN) (NM-401, NM-402, and NM-403), materials (NRCWE-026 and MWCNT-XNRI-7), and three sets of surface-modified MWCNT grouped by physical characteristics (thin, thick, and short I-III, respectively). Each Groups I-III included pristine, hydroxylated and carboxylated MWCNT. Group III also included...... an amino-functionalized MWCNT. The level of surface functionalization of the MWCNT was low. The level and type of elemental impurities of the MWCNT varied by...

  3. Neural Networks Relating Alloy Composition, Microstructure, and Tensile Properties of α/ β-Processed TIMETAL 6-4

    Science.gov (United States)

    Collins, Peter C.; Koduri, Santhosh; Welk, Brian; Tiley, Jaimie; Fraser, Hamish L.

    2013-03-01

    Bayesian neural networks have been developed, which relate composition, microstructure, and tensile properties of the alloy TIMETAL 6-4 (nominal composition: Ti-6Al-4V (wt pct) after thermomechanical processing (TMP) in the two-phase ( α + β)-phase field. The developed networks are able to make interpolative predictions of properties within the ranges of composition and microstructural features that are in the population of the database used for training and testing of the networks. In addition, the neural networks have been used to conduct virtual experiments which permit the functional dependencies of properties on composition and microstructural features to be determined. In this way, it is shown that in the microstructural condition resulting from TMP in the two-phase ( α + β) phase field, the most significant contribution to strength is from solid solution strengthening, with microstructural features apparently influencing the balance of a number of properties.

  4. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network

    Directory of Open Access Journals (Sweden)

    Zhibin Yu

    2017-01-01

    Full Text Available Underwater inherent optical properties (IOPs are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

  5. Equilibrium switching and mathematical properties of nonlinear interaction networks with concurrent antagonism and self-stimulation

    International Nuclear Information System (INIS)

    Rabajante, Jomar Fajardo; Talaue, Cherryl Ortega

    2015-01-01

    Graphical abstract: Display Omitted -- Highlights: •Properties of n-dimensional decision model of competitive interaction networks. •Graphical technique for component-wise and steady state stability analysis. •Search for parameter conditions that control equilibrium switching. •Illustrations of multi-stable systems and repressilators. -- Abstract: Concurrent decision-making model (CDM) of interaction networks with more than two antagonistic components represents various biological systems, such as gene interaction, species competition and mental cognition. The CDM model assumes sigmoid kinetics where every component stimulates itself but concurrently represses the others. Here we prove generic mathematical properties (e.g., location and stability of steady states) of n-dimensional CDM with either symmetric or asymmetric reciprocal antagonism between components. Significant modifications in parameter values serve as biological regulators for inducing steady state switching by driving a temporal state to escape an undesirable equilibrium. Increasing the maximal growth rate and decreasing the decay rate can expand the basin of attraction of a steady state that contains the desired dominant component. Perpetually adding an external stimulus could shut down multi-stability of the system which increases the robustness of the system against stochastic noise. We further show that asymmetric interaction forming a repressilator-type network generates oscillatory behavior

  6. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

    Science.gov (United States)

    Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

    2017-01-01

    Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

  7. Probing the topological properties of complex networks modeling short written texts.

    Directory of Open Access Journals (Sweden)

    Diego R Amancio

    Full Text Available In recent years, graph theory has been widely employed to probe several language properties. More specifically, the so-called word adjacency model has been proven useful for tackling several practical problems, especially those relying on textual stylistic analysis. The most common approach to treat texts as networks has simply considered either large pieces of texts or entire books. This approach has certainly worked well-many informative discoveries have been made this way-but it raises an uncomfortable question: could there be important topological patterns in small pieces of texts? To address this problem, the topological properties of subtexts sampled from entire books was probed. Statistical analyses performed on a dataset comprising 50 novels revealed that most of the traditional topological measurements are stable for short subtexts. When the performance of the authorship recognition task was analyzed, it was found that a proper sampling yields a discriminability similar to the one found with full texts. Surprisingly, the support vector machine classification based on the characterization of short texts outperformed the one performed with entire books. These findings suggest that a local topological analysis of large documents might improve its global characterization. Most importantly, it was verified, as a proof of principle, that short texts can be analyzed with the methods and concepts of complex networks. As a consequence, the techniques described here can be extended in a straightforward fashion to analyze texts as time-varying complex networks.

  8. A social network's changing statistical properties and the quality of human innovation

    Energy Technology Data Exchange (ETDEWEB)

    Uzzi, Brian [Kellogg School of Management, Northwestern University, Evanston, IL (United States)], E-mail: uzzi@northwestern.edu

    2008-06-06

    We examined the entire network of creative artists that made Broadway musicals, in the post-War period, a collaboration network of international acclaim and influence, with an eye to investigating how the network's structural features condition the relationship between individual artistic talent and the success of their musicals. Our findings show that some of the evolving topographical qualities of degree distributions, path lengths and assortativity are relatively stable with time even as collaboration patterns shift, which suggests their changes are only minimally associated with the ebb and flux of the success of new productions. In contrast, the clustering coefficient changed substantially over time and we found that it had a nonlinear association with the production of financially and artistically successful shows. When the clustering coefficient ratio is low or high, the financial and artistic success of the industry is low, while an intermediate level of clustering is associated with successful shows. We supported these findings with sociological theory on the relationship between social structure and collaboration and with tests of statistical inference. Our discussion focuses on connecting the statistical properties of social networks to their performance and the performance of the actors embedded within them.

  9. A social network's changing statistical properties and the quality of human innovation

    International Nuclear Information System (INIS)

    Uzzi, Brian

    2008-01-01

    We examined the entire network of creative artists that made Broadway musicals, in the post-War period, a collaboration network of international acclaim and influence, with an eye to investigating how the network's structural features condition the relationship between individual artistic talent and the success of their musicals. Our findings show that some of the evolving topographical qualities of degree distributions, path lengths and assortativity are relatively stable with time even as collaboration patterns shift, which suggests their changes are only minimally associated with the ebb and flux of the success of new productions. In contrast, the clustering coefficient changed substantially over time and we found that it had a nonlinear association with the production of financially and artistically successful shows. When the clustering coefficient ratio is low or high, the financial and artistic success of the industry is low, while an intermediate level of clustering is associated with successful shows. We supported these findings with sociological theory on the relationship between social structure and collaboration and with tests of statistical inference. Our discussion focuses on connecting the statistical properties of social networks to their performance and the performance of the actors embedded within them

  10. A new approach using artificial neural networks for determination of the thermodynamic properties of fluid couples

    International Nuclear Information System (INIS)

    Sencan, Arzu; Kalogirou, Soteris A.

    2005-01-01

    This paper presents a new approach using artificial neural networks (ANN) to determine the thermodynamic properties of two alternative refrigerant/absorbent couples (LiCl-H 2 O and LiBr + LiNO 3 + LiI + LiCl-H 2 O). These pairs can be used in absorption heat pump systems, and their main advantage is that they do not cause ozone depletion. In order to train the network, limited experimental measurements were used as training and test data. Two feedforward ANNs were trained, one for each pair, using the Levenberg-Marquardt algorithm. The training and validation were performed with good accuracy. The correlation coefficient obtained when unknown data were applied to the networks was 0.9997 and 0.9987 for the two pairs, respectively, which is very satisfactory. The present methodology proved to be much better than linear multiple regression analysis. Using the weights obtained from the trained network, a new formulation is presented for determination of the vapor pressures of the two refrigerant/absorbent couples. The use of this new formulation, which can be employed with any programming language or spreadsheet program for estimation of the vapor pressures of fluid couples, as described in this paper, may make the use of dedicated ANN software unnecessary

  11. A social network's changing statistical properties and the quality of human innovation

    Science.gov (United States)

    Uzzi, Brian

    2008-06-01

    We examined the entire network of creative artists that made Broadway musicals, in the post-War period, a collaboration network of international acclaim and influence, with an eye to investigating how the network's structural features condition the relationship between individual artistic talent and the success of their musicals. Our findings show that some of the evolving topographical qualities of degree distributions, path lengths and assortativity are relatively stable with time even as collaboration patterns shift, which suggests their changes are only minimally associated with the ebb and flux of the success of new productions. In contrast, the clustering coefficient changed substantially over time and we found that it had a nonlinear association with the production of financially and artistically successful shows. When the clustering coefficient ratio is low or high, the financial and artistic success of the industry is low, while an intermediate level of clustering is associated with successful shows. We supported these findings with sociological theory on the relationship between social structure and collaboration and with tests of statistical inference. Our discussion focuses on connecting the statistical properties of social networks to their performance and the performance of the actors embedded within them.

  12. THE MORPHOLOGIC PROPERTIES OF MAGNETIC NETWORKS OVER THE SOLAR CYCLE 23

    Energy Technology Data Exchange (ETDEWEB)

    Huang Chong; Yan Yihua; Zhang Yin; Tan Baolin; Li Gang, E-mail: chuang@nao.cas.cn, E-mail: yyh@nao.cas.cn [Key Laboratory of Solar Activity, National Astronomical Observatories of Chinese Academy of Sciences, Beijing 100012 (China)

    2012-11-10

    The morphologic properties of the magnetic networks during Carrington Rotations (CRs) 1955-2091 (from 1999 to 2010) have been analyzed by applying the watershed algorithm to magnetograms observed by the Michelson Doppler Interferometer on board the Solar and Heliospheric Observatory spacecraft. We find that the average area of magnetic cells on the solar surface at lower latitudes (within {+-}50 Degree-Sign ) is smaller than that at higher latitudes (beyond {+-}50 Degree-Sign ). Statistical analysis of these data indicates that the magnetic networks are fractal in nature and the average fractal dimension is D{sub f} = 1.253 {+-} 0.011. We also find that both the fractal dimension and the size of the magnetic networks are anti-correlated with the sunspot area. This is perhaps because a strong magnetic field can suppress spatially modulated oscillation and compress the boundaries of network cells, leading to smoother cell boundaries. The fractal dimension of the cell deviates from that predicted from an isobar of Kolmogorov k {sup -5/3} homogeneous turbulence.

  13. The Effects of Long-term Abacus Training on Topological Properties of Brain Functional Networks.

    Science.gov (United States)

    Weng, Jian; Xie, Ye; Wang, Chunjie; Chen, Feiyan

    2017-08-18

    Previous studies in the field of abacus-based mental calculation (AMC) training have shown that this training has the potential to enhance a wide variety of cognitive abilities. It can also generate specific changes in brain structure and function. However, there is lack of studies investigating the impact of AMC training on the characteristics of brain networks. In this study, utilizing graph-based network analysis, we compared topological properties of brain functional networks between an AMC group and a matched control group. Relative to the control group, the AMC group exhibited higher nodal degrees in bilateral calcarine sulcus and increased local efficiency in bilateral superior occipital gyrus and right cuneus. The AMC group also showed higher nodal local efficiency in right fusiform gyrus, which was associated with better math ability. However, no relationship was significant in the control group. These findings provide evidence that long-term AMC training may improve information processing efficiency in visual-spatial related regions, which extend our understanding of training plasticity at the brain network level.

  14. Network structure and functional properties of transparent hydrogel sanxan produced by Sphingomonas sanxanigenens NX02.

    Science.gov (United States)

    Wu, Mengmeng; Shi, Zhong; Huang, Haidong; Qu, Jianmei; Dai, Xiaohui; Tian, Xuefeng; Wei, Weiying; Li, Guoqiang; Ma, Ting

    2017-11-15

    The micro-network structure and functional properties of sanxan, a novel polysaccharide produced by Sphingomonas sanxanigenens NX02, were investigated. Transparent hydrogel sanxan was a high acyl polymer containing 8.96% acetyl and 4.75% glyceroyl. The micro-network structure of sanxan was mainly cyclic configurations composed of side-by-side intermolecular associations, with many rounded nodes found. Sanxan exhibited predominant gelation behavior at concentrations above 0.1%, which was enhanced by adding cations, especially Ca 2+ . The gel strength of sanxan was much higher than that of low acyl gellan, but slightly lower than that of high acyl gellan. Furthermore, the conformation transition temperature was increased in the presence of added cations. Moreover, sanxan showed excellent emulsifying and emulsion stabilizing properties. Consequently, such excellent functional properties make sanxan a good candidate as a gelling, stabilizing, emulsifying, or suspending agent in food and cosmetics industries, and in medical and pharmaceutical usage. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Comprehensive risk assessment method of catastrophic accident based on complex network properties

    Science.gov (United States)

    Cui, Zhen; Pang, Jun; Shen, Xiaohong

    2017-09-01

    On the macro level, the structural properties of the network and the electrical characteristics of the micro components determine the risk of cascading failures. And the cascading failures, as a process with dynamic development, not only the direct risk but also potential risk should be considered. In this paper, comprehensively considered the direct risk and potential risk of failures based on uncertain risk analysis theory and connection number theory, quantified uncertain correlation by the node degree and node clustering coefficient, then established a comprehensive risk indicator of failure. The proposed method has been proved by simulation on the actual power grid. Modeling a network according to the actual power grid, and verified the rationality of the proposed method.

  16. Asymptotic stability and disturbance attenuation properties for a class of networked control systems

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In this paper, stability and disturbance attenuation issues for a class of Networked Control Systems (NCSs)under uncertain access delay and packet dropout effects are considered. Our aim is to find conditions on the delay and packet dropout rate, under which the system stability and H∞ disturbance attenuation properties are preserved to a desired level. The basic idea in this paper is to formulate such Networked Control System as a discrete-time switched system. Then the NCSs' stability and performance problems can be reduced to the corresponding problems for switched systems, which have been studied for decades and for which a number of results are available in the literature. The techniques in this paper are based on recent progress in the discrete-time switched systems and piecewise Lyapunov functions.

  17. On the structural properties of small-world networks with range-limited shortcut links

    Science.gov (United States)

    Jia, Tao; Kulkarni, Rahul V.

    2013-12-01

    We explore a new variant of Small-World Networks (SWNs), in which an additional parameter (r) sets the length scale over which shortcuts are uniformly distributed. When r=0 we have an ordered network, whereas r=1 corresponds to the original Watts-Strogatz SWN model. These limited range SWNs have a similar degree distribution and scaling properties as the original SWN model. We observe the small-world phenomenon for r≪1, indicating that global shortcuts are not necessary for the small-world effect. For limited range SWNs, the average path length changes nonmonotonically with system size, whereas for the original SWN model it increases monotonically. We propose an expression for the average path length for limited range SWNs based on numerical simulations and analytical approximations.

  18. Impact of Cross-Tie Properties on the Modal Behavior of Cable Networks on Cable-Stayed Bridges.

    Science.gov (United States)

    Ahmad, Javaid; Cheng, Shaohong; Ghrib, Faouzi

    2015-01-01

    Dynamic behaviour of cable networks is highly dependent on the installation location, stiffness, and damping of cross-ties. Thus, these are the important design parameters for a cable network. While the effects of the former two on the network response have been investigated to some extent in the past, the impact of cross-tie damping has rarely been addressed. To comprehend our knowledge of mechanics associated with cable networks, in the current study, an analytical model of a cable network will be proposed by taking into account both cross-tie stiffness and damping. In addition, the damping property of main cables in the network will also be considered in the formulation. This would allow exploring not only the effectiveness of a cross-tie design on enhancing the in-plane stiffness of a constituted cable network, but also its energy dissipation capacity. The proposed analytical model will be applied to networks with different configurations. The influence of cross-tie stiffness and damping on the modal response of various types of networks will be investigated by using the corresponding undamped rigid cross-tie network as a reference base. Results will provide valuable information on the selection of cross-tie properties to achieve more effective cable vibration control.

  19. Impact of Cross-Tie Properties on the Modal Behavior of Cable Networks on Cable-Stayed Bridges

    Directory of Open Access Journals (Sweden)

    Javaid Ahmad

    2015-01-01

    Full Text Available Dynamic behaviour of cable networks is highly dependent on the installation location, stiffness, and damping of cross-ties. Thus, these are the important design parameters for a cable network. While the effects of the former two on the network response have been investigated to some extent in the past, the impact of cross-tie damping has rarely been addressed. To comprehend our knowledge of mechanics associated with cable networks, in the current study, an analytical model of a cable network will be proposed by taking into account both cross-tie stiffness and damping. In addition, the damping property of main cables in the network will also be considered in the formulation. This would allow exploring not only the effectiveness of a cross-tie design on enhancing the in-plane stiffness of a constituted cable network, but also its energy dissipation capacity. The proposed analytical model will be applied to networks with different configurations. The influence of cross-tie stiffness and damping on the modal response of various types of networks will be investigated by using the corresponding undamped rigid cross-tie network as a reference base. Results will provide valuable information on the selection of cross-tie properties to achieve more effective cable vibration control.

  20. Formulation based on artificial neural network of thermodynamic properties of ozone friendly refrigerant/absorbent couples

    International Nuclear Information System (INIS)

    Soezen, Adnan; Arcaklioglu, Erol; Oezalp, Mehmet

    2005-01-01

    This paper presents a new approach based on artificial neural networks (ANNs) to determine the properties of liquid and two phase boiling and condensing of two alternative refrigerant/absorbent couples (methanol/LiBr and methanol/LiCl). These couples do not cause ozone depletion and use in the absorption thermal systems (ATSs). ANNs are able to learn the key information patterns within multidimensional information domain. ANNs operate such as a 'black box' model, requiring no detailed information about the system. On the other hand, they learn the relationship between the input and the output. In order to train the neural network, limited experimental measurements were used as training data and test data. In this study, in input layer, there are temperatures in the range of 298-498 K, pressures (0.1-40 MPa) and concentrations of 2%, 7%, 12% of the couples; specific volume is in output layer. The back-propagation learning algorithm with three different variants, namely scaled conjugate gradient (SCG), Pola-Ribiere conjugate gradient (CGP), and Levenberg-Marquardt (LM), and logistic sigmoid transfer function were used in the network so that the best approach can find. The most suitable algorithm and neuron number in the hidden layer are found as SCG with 8 neurons. For this number level, after the training, it is found that maximum error is less than 3%, average error is about 1% and R 2 value are 99.999%. As seen from the results obtained the thermodynamic equations for each pair by using the weights of network have been obviously predicted within acceptable errors. This paper shows that values predicted with ANN can be used to define the thermodynamic properties instead of approximate and complex analytic equations

  1. Gene expression profiling in the stress control brain region hypothalamic paraventricular nucleus reveals a novel gene network including Amyloid beta Precursor Protein

    Directory of Open Access Journals (Sweden)

    Deussing Jan M

    2010-10-01

    Full Text Available Abstract Background The pivotal role of stress in the precipitation of psychiatric diseases such as depression is generally accepted. This study aims at the identification of genes that are directly or indirectly responding to stress. Inbred mouse strains that had been evidenced to differ in their stress response as well as in their response to antidepressant treatment were chosen for RNA profiling after stress exposure. Gene expression and regulation was determined by microarray analyses and further evaluated by bioinformatics tools including pathway and cluster analyses. Results Forced swimming as acute stressor was applied to C57BL/6J and DBA/2J mice and resulted in sets of regulated genes in the paraventricular nucleus of the hypothalamus (PVN, 4 h or 8 h after stress. Although the expression changes between the mouse strains were quite different, they unfolded in phases over time in both strains. Our search for connections between the regulated genes resulted in potential novel signalling pathways in stress. In particular, Guanine nucleotide binding protein, alpha inhibiting 2 (GNAi2 and Amyloid β (A4 precursor protein (APP were detected as stress-regulated genes, and together with other genes, seem to be integrated into stress-responsive pathways and gene networks in the PVN. Conclusions This search for stress-regulated genes in the PVN revealed its impact on interesting genes (GNAi2 and APP and a novel gene network. In particular the expression of APP in the PVN that is governing stress hormone balance, is of great interest. The reported neuroprotective role of this molecule in the CNS supports the idea that a short acute stress can elicit positive adaptational effects in the brain.

  2. Including 10-Gigabit-capable Passive Optical Network under End-to-End Generalized Multi-Protocol Label Switching Provisioned Quality of Service

    DEFF Research Database (Denmark)

    Brewka, Lukasz Jerzy; Gavler, Anders; Wessing, Henrik

    2012-01-01

    of the network where quality of service signaling is bridged. This article proposes strategies for generalized multi-protocol label switching control over next emerging passive optical network standard, i.e., the 10-gigabit-capable passive optical network. Node management and resource allocation approaches...... are discussed, and possible issues are raised. The analysis shows that consideration of a 10-gigabit-capable passive optical network as a generalized multi-protocol label switching controlled domain is valid and may advance end-to-end quality of service provisioning for passive optical network based customers.......End-to-end quality of service provisioning is still a challenging task despite many years of research and development in this area. Considering a generalized multi-protocol label switching based core/metro network and resource reservation protocol capable home gateways, it is the access part...

  3. The relations between network-operation and topological-property in a scale-free and small-world network with community structure

    Science.gov (United States)

    Ma, Fei; Yao, Bing

    2017-10-01

    It is always an open, demanding and difficult task for generating available model to simulate dynamical functions and reveal inner principles from complex systems and networks. In this article, due to lots of real-life and artificial networks are built from series of simple and small groups (components), we discuss some interesting and helpful network-operation to generate more realistic network models. In view of community structure (modular topology), we present a class of sparse network models N(t , m) . At the moment, we capture the fact the N(t , 4) has not only scale-free feature, which means that the probability that a randomly selected vertex with degree k decays as a power-law, following P(k) ∼k-γ, where γ is the degree exponent, but also small-world property, which indicates that the typical distance between two uniform randomly chosen vertices grows proportionally to logarithm of the order of N(t , 4) , namely, relatively shorter diameter and lower average path length, simultaneously displays higher clustering coefficient. Next, as a new topological parameter correlating to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees over a network is studied in more detail, an exact analytical solution for the number of spanning trees of the N(t , 4) is obtained. Based on the network-operation, part hub-vertex linking with each other will be helpful for structuring various network models and investigating the rules related with real-life networks.

  4. Dynamical properties of fractal networks: Scaling, numerical simulations, and physical realizations

    International Nuclear Information System (INIS)

    Nakayama, T.; Yakubo, K.; Orbach, R.L.

    1994-01-01

    This article describes the advances that have been made over the past ten years on the problem of fracton excitations in fractal structures. The relevant systems to this subject are so numerous that focus is limited to a specific structure, the percolating network. Recent progress has followed three directions: scaling, numerical simulations, and experiment. In a happy coincidence, large-scale computations, especially those involving array processors, have become possible in recent years. Experimental techniques such as light- and neutron-scattering experiments have also been developed. Together, they form the basis for a review article useful as a guide to understanding these developments and for charting future research directions. In addition, new numerical simulation results for the dynamical properties of diluted antiferromagnets are presented and interpreted in terms of scaling arguments. The authors hope this article will bring the major advances and future issues facing this field into clearer focus, and will stimulate further research on the dynamical properties of random systems

  5. Neural networks applied to determine the thermophysical properties of amino acid based ionic liquids.

    Science.gov (United States)

    Cancilla, John C; Perez, Ana; Wierzchoś, Kacper; Torrecilla, José S

    2016-03-14

    A series of models based on artificial neural networks (ANNs) have been designed to estimate the thermophysical properties of different amino acid-based ionic liquids (AAILs). Three different databases of AAILs were modeled using these algorithms with the goal set to estimate the density, viscosity, refractive index, ionic conductivity, and thermal expansion coefficient, and requiring only data regarding temperature and electronic polarizability of the chemicals. Additionally, a global model was designed combining all of the databases to determine the robustness of the method. In general, the results were successful, reaching mean prediction errors below 1% in many cases, as well as a statistically reliable and accurate global model. Attaining these successful models is a relevant fact as AAILs are novel biodegradable and biocompatible compounds which may soon make their way into the health sector forming a part of useful biomedical applications. Therefore, understanding the behavior and being able to estimate their thermophysical properties becomes crucial.

  6. Gonorrhoea and gonococcal antimicrobial resistance surveillance networks in the WHO European Region, including the independent countries of the former Soviet Union.

    Science.gov (United States)

    Unemo, Magnus; Ison, Catherine A; Cole, Michelle; Spiteri, Gianfranco; van de Laar, Marita; Khotenashvili, Lali

    2013-12-01

    Antimicrobial resistance (AMR) in Neisseria gonorrhoeae has emerged for essentially all antimicrobials following their introduction into clinical practice. During the latest decade, susceptibility to the last remaining options for antimicrobial monotherapy, the extended-spectrum cephalosporins (ESC), has markedly decreased internationally and treatment failures with these ESCs have been verified. In response to this developing situation, WHO and the European Centre for Disease Prevention and Control (ECDC) have published global and region-specific response plans, respectively. One main component of these action/response plans is to enhance the surveillance of AMR and treatment failures. This paper describes the perspectives from the diverse WHO European Region (53 countries), including the independent countries of the former Soviet Union, regarding gonococcal AMR surveillance networks. The WHO European Region has a high prevalence of resistance to all previously recommended antimicrobials, and most of the first strictly verified treatment failures with cefixime and ceftriaxone were also reported from Europe. In the European Union/European Economic Area (EU/EEA), the European gonococcal antimicrobial surveillance programme (Euro-GASP) funded by the ECDC is running. In 2011, the Euro-GASP included 21/31 (68%) EU/EEA countries, and the programme is further strengthened annually. However, in the non-EU/EEA countries, internationally reported and quality assured gonococcal AMR data are lacking in 87% of the countries and, worryingly, appropriate support for establishment of a GASP is still lacking. Accordingly, national and international support, including political and financial commitment, for gonococcal AMR surveillance in the non-EU/EEA countries of the WHO European Region is essential.

  7. Study Under AC Stimulation on Excitement Properties of Weighted Small-World Biological Neural Networks with Side-Restrain Mechanism

    International Nuclear Information System (INIS)

    Yuan Wujie; Luo Xiaoshu; Jiang Pinqun

    2007-01-01

    In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.

  8. Topological and functional properties of the small GTPases protein interaction network.

    Directory of Open Access Journals (Sweden)

    Anna Delprato

    Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

  9. 3D printing of an interpenetrating network hydrogel material with tunable viscoelastic properties.

    Science.gov (United States)

    Bootsma, Katherine; Fitzgerald, Martha M; Free, Brandon; Dimbath, Elizabeth; Conjerti, Joe; Reese, Greg; Konkolewicz, Dominik; Berberich, Jason A; Sparks, Jessica L

    2017-06-01

    Interpenetrating network (IPN) hydrogel materials are recognized for their unique mechanical properties. While IPN elasticity and toughness properties have been explored in previous studies, the factors that impact the time-dependent stress relaxation behavior of IPN materials are not well understood. Time-dependent (i.e. viscoelastic) mechanical behavior is a critical design parameter in the development of materials for a variety of applications, such as medical simulation devices, flexible substrate materials, cellular mechanobiology substrates, or regenerative medicine applications. This study reports a novel technique for 3D printing alginate-polyacrylamide IPN gels with tunable elastic and viscoelastic properties. The viscoelastic stress relaxation behavior of the 3D printed alginate-polyacrylamide IPN hydrogels was influenced most strongly by varying the concentration of the acrylamide cross-linker (MBAA), while the elastic modulus was affected most by varying the concentration of total monomer material. The material properties of our 3D printed IPN constructs were consistent with those reported in the biomechanics literature for soft tissues such as skeletal muscle, cardiac muscle, skin and subcutaneous tissue. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

    Science.gov (United States)

    Jie, Biao; Liu, Mingxia; Shen, Dinggang

    2018-07-01

    Functional connectivity networks (FCNs) using resting-state functional magnetic resonance imaging (rs-fMRI) have been applied to the analysis and diagnosis of brain disease, such as Alzheimer's disease (AD) and its prodrome, i.e., mild cognitive impairment (MCI). Different from conventional studies focusing on static descriptions on functional connectivity (FC) between brain regions in rs-fMRI, recent studies have resorted to dynamic connectivity networks (DCNs) to characterize the dynamic changes of FC, since dynamic changes of FC may indicate changes in macroscopic neural activity patterns in cognitive and behavioral aspects. However, most of the existing studies only investigate the temporal properties of DCNs (e.g., temporal variability of FC between specific brain regions), ignoring the important spatial properties of the network (e.g., spatial variability of FC associated with a specific brain region). Also, emerging evidence on FCNs has suggested that, besides temporal variability, there is significant spatial variability of activity foci over time. Hence, integrating both temporal and spatial properties of DCNs can intuitively promote the performance of connectivity-network-based learning methods. In this paper, we first define a new measure to characterize the spatial variability of DCNs, and then propose a novel learning framework to integrate both temporal and spatial variabilities of DCNs for automatic brain disease diagnosis. Specifically, we first construct DCNs from the rs-fMRI time series at successive non-overlapping time windows. Then, we characterize the spatial variability of a specific brain region by computing the correlation of functional sequences (i.e., the changing profile of FC between a pair of brain regions within all time windows) associated with this region. Furthermore, we extract both temporal variabilities and spatial variabilities from DCNs as features, and integrate them for classification by using manifold regularized multi

  11. Relation between the development of structure and the properties of network polymers

    International Nuclear Information System (INIS)

    Williams, D.R.G.; Allen, P.E.M.; Simon, G.P.

    1989-01-01

    It was shown by various techniques that the development of structure in the early stages of cure determines the final structure and properties of glassy three-dimensional networks. Solid state [ 13 C]-nuclear magnetic resonance (NMR) techniques identified the structure groupings and the extent of heterogeneity soon after the commencement of polymerization through to the glassy state. Observations of the changes in mobility of groups during cure were correlated with the development of bulk properties such as the glass transition and compressive strength. Computer simulation of the kinetics of the polymerization based on a three-dimensional lattice closely followed the trends observed by experiment and provided insight into the formation of clusters of reacted polymer surrounded by pools of unreacted monomer. The difficulty in obtaining full cure was clearly associated with the presence of trapped reactive centres within the cluster. Observation of the behaviour of small probe or tracer molecules by NMR was shown to be a potent technique for investigating the organization of networks. 28 refs., 12 figs

  12. ODMBP: Behavior Forwarding for Multiple Property Destinations in Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Jia Xu

    2016-01-01

    Full Text Available The smartphones are widely available in recent years. Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. The behavior based forwarding has become a new transmission paradigm for supporting many novel applications. However, the commodities, services, and individuals usually have multiple properties of their interests and behaviors. In this paper, we profile these multiple properties and propose an Opportunistic Dissemination Protocol based on Multiple Behavior Profile, ODMBP, in mobile social networks. We first map the interest space to the behavior space and extract the multiple behavior profiles from the behavior space. Then, we propose the correlation computing model based on the principle of BM25 to calculate the correlation metric of multiple behavior profiles. The correlation metric is used to forward the message to the users who are more similar to the target in our protocol. ODMBP consists of three stages: user initialization, gradient ascent, and group spread. Through extensive simulations, we demonstrate that the proposed multiple behavior profile and correlation computing model are correct and efficient. Compared to other classical routing protocols, ODMBP can significantly improve the performance in the aspect of delivery ratio, delay, and overhead ratio.

  13. Self-Healing Natural Rubber with Tailorable Mechanical Properties Based on Ionic Supramolecular Hybrid Network.

    Science.gov (United States)

    Xu, Chuanhui; Cao, Liming; Huang, Xunhui; Chen, Yukun; Lin, Baofeng; Fu, Lihua

    2017-08-30

    In most cases, the strength of self-healing supramolecular rubber based on noncovalent bonds is in the order of KPa, which is a challenge for their further applications. Incorporation of conventional fillers can effectively enhance the strength of rubbers, but usually accompanied by a sacrifice of self-healing capability due to that the filler system is independent of the reversible supramolecular network. In the present work, in situ reaction of methacrylic acid (MAA) and excess zinc oxide (ZnO) was realized in natural rubber (NR). Ionic cross-links in NR matrix were obtained by limiting the covalent cross-linking of NR molecules and allowing the in situ polymerization of MAA/ZnO. Because of the natural affinity between Zn 2+ ion-rich domains and ZnO, the residual nano ZnO participated in formation of a reversible ionic supramolecular hybrid network, thus having little obstructions on the reconstruction of ionic cross-links. Meanwhile, the well dispersed residual ZnO could tailor the mechanical properties of NR by changing the MAA/ZnO molar ratios. The present study thus provides a simple method to fabricate a new self-healing NR with tailorable mechanical properties that may have more potential applications.

  14. Influence of the Training Set Value on the Quality of the Neural Network to Identify Selected Moulding Sand Properties

    Directory of Open Access Journals (Sweden)

    Jakubski J.

    2013-06-01

    Full Text Available Artificial neural networks are one of the modern methods of the production optimisation. An attempt to apply neural networks for controlling the quality of bentonite moulding sands is presented in this paper. This is the assessment method of sands suitability by means of detecting correlations between their individual parameters. This paper presents the next part of the study on usefulness of artificial neural networks to support rebonding of green moulding sand, using chosen properties of moulding sands, which can be determined fast. The effect of changes in the training set quantity on the quality of the network is presented in this article. It has been shown that a small change in the data set would change the quality of the network, and may also make it necessary to change the type of network in order to obtain good results.

  15. Enhancing Electrophoretic Display Lifetime: Thiol-Polybutadiene Evaporation Barrier Property Response to Network Microstructure

    Energy Technology Data Exchange (ETDEWEB)

    Cook, Caitlyn Christian [California State Polytechnic State Univ., San Luis Obispo, CA (United States)

    2017-02-27

    An evaporation barrier is required to enhance the lifetime of electrophoretic deposition (EPD) displays. As EPD functions on the basis of reversible deposition and resuspension of colloids suspended in a solvent, evaporation of the solvent ultimately leads to device failure. Incorporation of a thiol-polybutadiene elastomer into EPD displays enabled display lifetime surpassing six months in counting and catalyzed rigid display transition into a flexible package. Final flexible display transition to mass production compels an electronic-ink approach to encapsulate display suspension within an elastomer shell. Final thiol-polybutadiene photosensitive resin network microstructure was idealized to be dense, homogeneous, and expose an elastic response to deformation. Research at hand details an approach to understanding microstructural change within display elastomers. Polybutadiene-based resin properties are modified via polymer chain structure, with and without added aromatic urethane methacrylate difunctionality, and in measuring network response to variation in thiol and initiator concentration. Dynamic mechanical analysis results signify that cross-linked segments within a difunctionalized polybutadiene network were on average eight times more elastically active than that of linked segments within a non-functionalized polybutadiene network. Difunctionalized polybutadiene samples also showed a 2.5 times greater maximum elastic modulus than non-functionalized samples. Hybrid polymer composed of both polybutadiene chains encompassed TE-2000 stiffness and B-1000 elasticity for use in encapsulating display suspension. Later experiments measured kinetic and rheological response due to alteration in dithiol cross-linker chain length via real time Fourier transform infrared spectroscopy and real-time dynamic rheology. Distinct differences were discovered between dithiol resin systems, as maximum thiol conversion achieved in short and long chain length dithiols was 86% and

  16. Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

    Science.gov (United States)

    More, Simon J.; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E.; Martínez-López, Beatriz

    2018-01-01

    Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm’s disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and

  17. Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

    Directory of Open Access Journals (Sweden)

    Tadaishi Yatabe

    Full Text Available Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1, were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon farms had the highest biosecurity scores with a median (interquartile range of 82.3 (5.4, followed by freshwater salmon (FW salmon with 75.2 (8.2, and freshwater trout (FW trout farms with 74.8 (4.5. For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic was the null model (looic = 46.1. For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3. Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm's disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and

  18. Wood Modification at High Temperature and Pressurized Steam: a Relational Model of Mechanical Properties Based on a Neural Network

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2015-07-01

    Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.

  19. Networks of networks – An introduction

    International Nuclear Information System (INIS)

    Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

    2015-01-01

    Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

  20. GABAergic synapse properties may explain genetic variation in hippocampal network oscillations in mice

    Directory of Open Access Journals (Sweden)

    Tim S Heistek

    2010-06-01

    Full Text Available Cognitive ability and the properties of brain oscillation are highly heritable in humans. Genetic variation underlying oscillatory activity might give rise to differences in cognition and behavior. How genetic diversity translates into altered properties of oscillations and synchronization of neuronal activity is unknown. To address this issue, we investigated cellular and synaptic mechanisms of hippocampal fast network oscillations in eight genetically distinct inbred mouse strains. The frequency of carbachol-induced oscillations differed substantially between mouse strains. Since GABAergic inhibition sets oscillation frequency, we studied the properties of inhibitory synaptic inputs (IPSCs received by CA3 and CA1 pyramidal cells of three mouse strains that showed the highest, lowest and intermediate frequencies of oscillations. In CA3 pyramidal cells, the frequency of rhythmic IPSC input showed the same strain differences as the frequency of field oscillations. Furthermore, IPSC decay times in both CA1 and CA3 pyramidal cells were faster in mouse strains with higher oscillation frequencies than in mouse strains with lower oscillation frequency, suggesting that differences in GABAA-receptor subunit composition exist between these strains. Indeed, gene expression of GABAA-receptor β2 (Gabrb2 and β3 (Gabrb2 subunits was higher in mouse strains with faster decay kinetics compared with mouse strains with slower decay kinetics. Hippocampal pyramidal neurons in mouse strains with higher oscillation frequencies and faster decay kinetics fired action potential at higher frequencies. These data indicate that differences in genetic background may result in different GABAA-receptor subunit expression, which affects the rhythm of pyramidal neuron firing and fast network activity through GABA synapse kinetics.

  1. Prediction of properties of polymer concrete composite with tire rubber using neural networks

    International Nuclear Information System (INIS)

    Diaconescu, Rodica-Mariana; Barbuta, Marinela; Harja, Maria

    2013-01-01

    Highlights: ► Using waste a new composite material was obtained with specific characteristics. ► The objective was to maximize tire powder content with the minimum resin content. ► By direct modeling, the maximum compressive strength was obtained for 30% tire powder. ► Inverse neural modeling was used for obtaining maximum values of strengths. -- Abstract: The neural network method was used to investigate the influence of filler and resin content on the mechanical properties of polymer concrete with powdered tire waste. The mechanical strengths of 10 experimentally determined combinations using mixed epoxy resin, aggregates and tire powder as filler were optimized using direct neural modeling and inverse neural modeling, by imposing a minimum cost (content in resin). Direct neural modeling gave the optimum composition for obtaining maximum values for compressive strength, flexural strength and split tensile strength. Inverse neural modeling analyzed the possibility of obtaining maximum values of mechanical properties by variations in the dosages of the epoxy resin and tire powder. Neural network modeling generated the mixes with the lowest cost and maximum strength. The modeling method has shown that two mechanical properties can be simultaneously optimized in the investigation domain. From direct modeling, the maximum compressive strength was obtained for a composition with 0.215 (fraction weight) epoxy resin and 0.3 (fraction weight) tire powder. Maximum flexural strength was obtained for experimental values of 0.23 epoxy resin and 0.17 tire powder with a severe reduction noted for smaller resin dosages. The maximum split tensile strength was obtained for a resin dosage of 0.24 and tire powder dosage of 0.17

  2. Disrupted topological properties of brain white matter networks in left temporal lobe epilepsy: a diffusion tensor imaging study.

    Science.gov (United States)

    Xu, Y; Qiu, S; Wang, J; Liu, Z; Zhang, R; Li, S; Cheng, L; Liu, Z; Wang, W; Huang, R

    2014-10-24

    Mesial temporal lobe epilepsy (mTLE) is the most common drug-refractory focal epilepsy in adults. Although previous functional and morphological studies have revealed abnormalities in the brain networks of mTLE, the topological organization of the brain white matter (WM) networks in mTLE patients is still ambiguous. In this study, we constructed brain WM networks for 14 left mTLE patients and 22 age- and gender-matched normal controls using diffusion tensor tractography and estimated the alterations of network properties in the mTLE brain networks using graph theoretical analysis. We found that networks for both the mTLE patients and the controls exhibited prominent small-world properties, suggesting a balanced topology of integration and segregation. However, the brain WM networks of mTLE patients showed a significant increased characteristic path length but significant decreased global efficiency, which indicate a disruption in the organization of the brain WM networks in mTLE patients. Moreover, we found significant between-group differences in the nodal properties in several brain regions, such as the left superior temporal gyrus, left hippocampus, the right occipital and right temporal cortices. The robustness analysis showed that the results were likely to be consistent for the networks constructed with different definitions of node and edge weight. Taken together, our findings may suggest an adverse effect of epileptic seizures on the organization of large-scale brain WM networks in mTLE patients. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  3. R2 & NE: NAVTEQ 2011 Q3 Major Road Network for the United States, including Puerto Rico and the US Virgin Islands in SDC Format

    Data.gov (United States)

    U.S. Environmental Protection Agency — The MROADS layer contains the Major Roads network using NAVTEQ Functional Class=1,2,3,4, where 4 represents routes connecting minor towns or villages and collecting...

  4. R2 & NE: NAVTEQ 2011 Q3 Interstate Highway Network for the United States, including Puerto Rico and the US Virgin Islands in SDC Format

    Data.gov (United States)

    U.S. Environmental Protection Agency — The INTERSTATES layer contains the Interstate Highway network, using NAVTEQ Functional Class=1 for United States and Canada. This 5 layer SDC dataset represents a...

  5. Prediction of oxidation parameters of purified Kilka fish oil including gallic acid and methyl gallate by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network.

    Science.gov (United States)

    Asnaashari, Maryam; Farhoosh, Reza; Farahmandfar, Reza

    2016-10-01

    As a result of concerns regarding possible health hazards of synthetic antioxidants, gallic acid and methyl gallate may be introduced as natural antioxidants to improve oxidative stability of marine oil. Since conventional modelling could not predict the oxidative parameters precisely, artificial neural network (ANN) and neuro-fuzzy inference system (ANFIS) modelling with three inputs, including type of antioxidant (gallic acid and methyl gallate), temperature (35, 45 and 55 °C) and concentration (0, 200, 400, 800 and 1600 mg L(-1) ) and four outputs containing induction period (IP), slope of initial stage of oxidation curve (k1 ) and slope of propagation stage of oxidation curve (k2 ) and peroxide value at the IP (PVIP ) were performed to predict the oxidation parameters of Kilka oil triacylglycerols and were compared to multiple linear regression (MLR). The results showed ANFIS was the best model with high coefficient of determination (R(2)  = 0.99, 0.99, 0.92 and 0.77 for IP, k1 , k2 and PVIP , respectively). So, the RMSE and MAE values for IP were 7.49 and 4.92 in ANFIS model. However, they were to be 15.95 and 10.88 and 34.14 and 3.60 for the best MLP structure and MLR, respectively. So, MLR showed the minimum accuracy among the constructed models. Sensitivity analysis based on the ANFIS model suggested a high sensitivity of oxidation parameters, particularly the induction period on concentrations of gallic acid and methyl gallate due to their high antioxidant activity to retard oil oxidation and enhanced Kilka oil shelf life. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  6. Molecular network including eIF1AX, RPS7, and 14-3-3γ regulates protein translation and cell proliferation in bovine mammary epithelial cells.

    Science.gov (United States)

    Yu, Cuiping; Luo, Chaochao; Qu, Bo; Khudhair, Nagam; Gu, Xinyu; Zang, Yanli; Wang, Chunmei; Zhang, Na; Li, Qingzhang; Gao, Xuejun

    2014-12-15

    14-3-3γ, an isoform of the 14-3-3 protein family, was proved to be a positive regulator of mTOR pathway. Here, we analyzed the function of 14-3-3γ in protein synthesis using bovine mammary epithelial cells (BMECs). We found that 14-3-3γ interacted with eIF1AX and RPS7 by 14-3-3γ coimmunoprecipitation (CoIP) and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight (MALDI-TOF/TOF) peptide mass fingerprinting analysis. These interactions of 14-3-3γ with eIF1AX and RPS7 were further confirmed by colocalization and fluorescence resonance energy transfer (FRET) analysis. We also found that methionine could promote protein synthesis and trigger the protein expression levels of 14-3-3γ, eIF1AX and RPS7. Analysis of overexpression and inhibition of 14-3-3γ confirmed that it positively affected the protein expression levels of eIF1AX, RPS7, Stat5 and mTOR pathway to promote protein synthesis and cell proliferation in BMECs. We further showed that overexpression of eIF1AX and RPS7 also triggered protein translation and cell proliferation. From these results, we conclude that molecular network including eIF1AX, RPS7, and 14-3-3γ regulates protein translation and cell proliferation in BMECs. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.

    Science.gov (United States)

    Trentin, Edmondo; Lusnig, Luca; Cavalli, Fabio

    2018-01-01

    A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) pdf estimation techniques. Besides being profitably simple, the PNN turns out to have nice properties in terms of unbiased modeling capability, asymptotic convergence, and efficiency at test time. Several matters pertaining the practical application of the PNN are faced in the paper, too. Experiments are reported, involving (i) synthetic datasets, and (ii) a challenging sex determination task from 1400 scout-view CT-scan images of human crania. Incidentally, the empirical evidence entails also some conclusions of high anthropological relevance. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Isik, Nimet

    2016-04-01

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

  9. Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

    Science.gov (United States)

    Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

    2017-07-21

    Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

  10. Analysis of topological relationships and network properties in the interactions of human beings.

    Directory of Open Access Journals (Sweden)

    Ye Yuan

    Full Text Available In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors.

  11. Thermo-Mechanical Properties of Semi-Degradable Poly(β-amino ester)-co-Methyl Methacrylate Networks under Simulated Physiological Conditions

    Science.gov (United States)

    Safranski, David L.; Crabtree, Jacob C.; Huq, Yameen R.; Gall, Ken

    2011-01-01

    Poly(β-amino ester) networks are being explored for biomedical applications, but they may lack the mechanical properties necessary for long term implantation. The objective of this study is to evaluate the effect of adding methyl methacrylate on networks' mechanical properties under simulated physiological conditions. The networks were synthesized in two parts: (1) a biodegradable crosslinker was formed from a diacrylate and amine, (2) and then varying concentrations of methyl methacrylate were added prior to photopolymerizing the network. Degradation rate, mechanical properties, and glass transition temperature were studied as a function of methyl methacrylate composition. The crosslinking density played a limited role on mechanical properties for these networks, but increasing methyl methacrylate concentration improved the toughness by several orders of magnitude. Under simulated physiological conditions, networks showed increasing toughness or sustained toughness as degradation occurred. This work establishes a method of creating degradable networks with tailorable toughness while undergoing partial degradation. PMID:21966028

  12. Multifunctionality in coating films including Nb-doped TiO2 and Cs x WO3: near infrared shielding and photocatalytic properties

    Science.gov (United States)

    Asakura, Yusuke; Anada, Yuto; Hamanaka, Ryo; Sato, Tsugio; Katsumata, Ken-ichi; Wu, Xiaoyong; Yin, Shu

    2018-06-01

    Various types of coating films were obtained from hydrothermally synthesized Nb-doped TiO2 (NTO) and Cs x WO3 (CWO) nanoparticles. The coating films possessed multifunctionality including near infrared (NIR) absorption and photocatalysis abilities. The NTO and CWO nanoparticles were synthesized by a unique solvothermal reaction in which water induced by an esterification reaction between alcohol and carboxylic acid can act as a hydrolyzing agent for metal precursors. NTO was synthesized by the unique solvothermal reaction for the first time. The reaction accompanied by the reduction of Ti4+ to Ti3+ led to the formation of nanoparticles with both NIR absorption and photocatalytic properties. The effect of the ethanol–acetic acid ratio on the morphology of the obtained NTO was investigated, and the larger amount of acetic acid led to a larger nanoparticle size, indicating the size controllability. The two types of coating film, including CWO and NTO nanoparticles, were obtained for comparison: (1) coexistent coating film: one side of the quartz glass was coated with a dispersion, including both CWO and NTO nanoparticles, and (2) double-sided coating film: a quartz glass coated with a CWO dispersion on one side and an NTO dispersion on the other side. The double-sided coating led to higher multifunctionality. Furthermore, the optimized condition for the double-sided coating was investigated by using various NTO particles obtained using different ethanol–acetic acid ratios.

  13. The DSM-5 Dimensional Anxiety Scales in a Dutch non-clinical sample: psychometric properties including the adult separation anxiety disorder scale.

    Science.gov (United States)

    Möller, Eline L; Bögels, Susan M

    2016-09-01

    With DSM-5, the American Psychiatric Association encourages complementing categorical diagnoses with dimensional severity ratings. We therefore examined the psychometric properties of the DSM-5 Dimensional Anxiety Scales, a set of brief dimensional scales that are consistent in content and structure and assess DSM-5-based core features of anxiety disorders. Participants (285 males, 255 females) completed the DSM-5 Dimensional Anxiety Scales for social anxiety disorder, generalized anxiety disorder, specific phobia, agoraphobia, and panic disorder that were included in previous studies on the scales, and also for separation anxiety disorder, which is included in the DSM-5 chapter on anxiety disorders. Moreover, they completed the Screen for Child Anxiety Related Emotional Disorders Adult version (SCARED-A). The DSM-5 Dimensional Anxiety Scales demonstrated high internal consistency, and the scales correlated significantly and substantially with corresponding SCARED-A subscales, supporting convergent validity. Separation anxiety appeared present among adults, supporting the DSM-5 recognition of separation anxiety as an anxiety disorder across the life span. To conclude, the DSM-5 Dimensional Anxiety Scales are a valuable tool to screen for specific adult anxiety disorders, including separation anxiety. Research in more diverse and clinical samples with anxiety disorders is needed. © 2016 The Authors International Journal of Methods in Psychiatric Research Published by John Wiley & Sons Ltd. © 2016 The Authors International Journal of Methods in Psychiatric Research Published by John Wiley & Sons Ltd.

  14. Walking- and cycling track networks in Norwegian cities : cost-benefit analyses including health effects and external costs of road traffic : summary

    Science.gov (United States)

    2002-04-01

    Cost- benefit analyses of walking- and cycling track net-works in three Norwegian cities are presented in this study. A project group working with a National Cycling Strategy in Norway initialised the study. Motivation for starting the study is the P...

  15. Relationships between nanostructure and dynamic-mechanical properties of epoxy network containing PMMA-modified silsesquioxane

    Directory of Open Access Journals (Sweden)

    2009-06-01

    Full Text Available A new class of organic-inorganic hybrid nanocomposites was obtained by blending PMMA-modified silsesquioxane hybrid materials with epoxy matrix followed by curing with methyl tetrahydrophthalic anhydride. The hybrid materials were obtained by sol-gel method through the hydrolysis and polycondensation of the silicon species of the hybrid precursor, 3-methacryloxypropyltrimethoxysilane (MPTS, simultaneously to the polymerization of the methacrylate (MMA groups covalently bonded to the silicon atoms. The nanostructure of these materials was investigated by small angle X-ray scattering (SAXS and correlated to their dynamic mechanical properties. The SAXS results revealed a hierarchical nanostructure consisting on two structural levels. The first level is related to the siloxane nanoparticles spatially correlated in the epoxy matrix, forming larger hybrid secondary aggregates. The dispersion of siloxane nanoparticles in epoxy matrix was favored by increasing the MMA content in the hybrid material. The presence of small amount of hybrid material affected significantly the dynamic mechanical properties of the epoxy networks.

  16. Electrogenerated networks from poly[4-(diphenylaminobenzyl methacrylate] and their electrochromic properties

    Directory of Open Access Journals (Sweden)

    O. I. Negru

    2014-09-01

    Full Text Available Poly[4-(diphenylaminobenzyl methacrylate] with well-defined molecular weight and low polydispersity was prepared by atom transfer radical polymerization (ATRP using 4-(diphenylamino benzyl 2-bromo-2-methyl-propanoate as initiator and CuBr/2,2'-bipyridine as catalytic complex. Electrochemical behavior and optical properties of the polymers were investigated by cyclic voltammetry and UV-Vis and fluorescence spectroscopy. Cyclic votammetric studies revealed that the redox processes were accompanied by dimerization of triphenylamine pendant groups. The initial polymer was postmodified, in solution or bulk, by electrochemical oxidation leading to a crosslinked and insoluble network with electro -chromic properties, accompanied by strong color changes with high coloration efficiency. The crosslinking reaction took place between triphenylamine groups through para free positions leading to tetraphenylbenzidine bridges. The structure of polymers was confirmed by Fourier transform infrared (FT-IR spectroscopy and 1H and 13C-nuclear magnetic resonance spectroscopy. Morphology studies of the cross-linked film have evidenced a smooth and continuous aspect without any pinholes or defects.

  17. How optimal synchronization of oscillators depends on the network structure and the individual dynamical properties of the oscillators

    International Nuclear Information System (INIS)

    Markovic, R; Gosak, M; Marhl, M

    2013-01-01

    The problem of making a network of dynamical systems synchronize onto a common evolution is the subject of much ongoing research in several scientific disciplines. It is nowadays a well-known fact that the synchronization processes are gradually influenced by the interaction topology between the dynamically interacting units. A complex coupling configuration can significantly affect the synchronization abilities of a networked system. However, the question arises what is the optimal network topology that provides enhancement of the synchronization features under given circumstances. In order to address this issue we make use of a network model in which we can smoothly tune the topology from a highly heterogeneous and efficient scale-free network to a homogeneous and less efficient network. The network is then populated with Poincaré oscillators, a paradigmatic model for limit-cycle oscillations. This oscillator model exhibits a parameter that enables changes of the limit cycle attraction and is thus immediately related to flexibility/rigidity properties of the oscillator. Our results reveal that for weak attractions of the limit cycle, intermediate homogeneous topology ensures maximal synchronization, whereas highly heterogeneous scale-free topology ensures maximal synchronization for strong attractions of the limit cycle. We argue that the flexibility/rigidity of individual nodes of the networks defines the topology, where maximal global coherence is achieved.

  18. [Analysis of the Characteristics of Infantile Small World Neural Network Node Properties Correlated with the Influencing Factors].

    Science.gov (United States)

    Qu, Haibo; Lu, Su; Zhang, Wenjing; Xiao, Yuan; Ning, Gang; Sun, Huaiqiang

    2016-10-01

    We applied resting-state functional magnetic resonance imaging(rfMRI)combined with graph theory to analyze 90 regions of the infantile small world neural network of the whole brain.We tried to get the following two points clear:1 whether the parameters of the node property of the infantile small world neural network are correlated with the level of infantile intelligence development;2 whether the parameters of the infantile small world neural network are correlated with the children’s baseline parameters,i.e.,the demographic parameters such as gender,age,parents’ education level,etc.Twelve cases of healthy infants were included in the investigation(9males and 3females with the average age of 33.42±8.42 months.)We then evaluated the level of infantile intelligence of all the cases and graded by Gesell Development Scale Test.We used a Siemens 3.0T Trio imaging system to perform resting-state(rs)EPI scans,and collected the BOLD functional Magnetic Resonance Imaging(fMRI)data.We performed the data processing with Statistical Parametric Mapping 5(SPM5)based on Matlab environment.Furthermore,we got the attributes of the whole brain small world and node attributes of 90 encephalic regions of templates of Anatomatic Automatic Labeling(ALL).At last,we carried out correlation study between the above-mentioned attitudes,intelligence scale parameters and demographic data.The results showed that many node attributes of small world neural network were closely correlated with intelligence scale parameters.Betweeness was mainly centered in thalamus,superior frontal gyrus,and occipital lobe(negative correlation).The r value of superior occipital gyrus associated with the individual and social intelligent scale was-0.729(P=0.007);degree was mainly centered in amygdaloid nucleus,superior frontal gyrus,and inferior parietal gyrus(positive correlation).The r value of inferior parietal gyrus associated with the gross motor intelligent scale was 0.725(P=0.008);efficiency was mainly

  19. Novel amphiphilic poly(dimethylsiloxane) based polyurethane networks tethered with carboxybetaine and their combined antibacterial and anti-adhesive property

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Jingxian; Fu, Yuchen; Zhang, Qinghua, E-mail: qhzhang@zju.edu.cn; Zhan, Xiaoli; Chen, Fengqiu

    2017-08-01

    Highlights: • An amphiphilic poly(dimethylsiloxane) (PDMS) based polyurethane (PU) network tethered with carboxybetaine is prepared. • The surface distribution of PDMS and zwitterionic segments produces an obvious amphiphilic heterogeneous surface. • This designed PDMS-based amphiphilic PU network exhibits combined antibacterial and anti-adhesive properties. - Abstract: The traditional nonfouling materials are powerless against bacterial cells attachment, while the hydrophobic bactericidal surfaces always suffer from nonspecific protein adsorption and dead bacterial cells accumulation. Here, amphiphilic polyurethane (PU) networks modified with poly(dimethylsiloxane) (PDMS) and cationic carboxybetaine diol through simple crosslinking reaction were developed, which had an antibacterial efficiency of 97.7%. Thereafter, the hydrolysis of carboxybetaine ester into zwitterionic groups brought about anti-adhesive properties against bacteria and proteins. The surface chemical composition and wettability performance of the PU network surfaces were investigated by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The surface distribution of PDMS and zwitterionic segments produced an obvious amphiphilic heterogeneous surface, which was demonstrated by atomic force microscopy (AFM). Enzyme-linked immunosorbent assays (ELISA) were used to test the nonspecific protein adsorption behaviors. With the advantages of the transition from excellent bactericidal performance to anti-adhesion and the combination of fouling resistance and fouling release property, the designed PDMS-based amphiphilic PU network shows great application potential in biomedical devices and marine facilities.

  20. Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory

    Science.gov (United States)

    Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N.

    2016-01-01

    We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

  1. Social Networks in context of cyberspace. Consumers, electronic commerce and intellectual property in the light of the Cuban case

    Directory of Open Access Journals (Sweden)

    Nelvys Mendoza Gurdián

    2018-06-01

    Full Text Available Face the state of vulnerability in the context of cyberspace, it is necessary to reflect on the social networks and law, from a holistic approach aimed at the vulnerability of rights associated with the information in this environment. This work general objective is to analyse the phenomenon of online social networks and the information society, emphasizing on the study of the legal aspects related to consumers, electronic commerce and intellectual property. The methodology used aims to conceptualize the category of social networks, examinate the aspects associated with law in the use of social networks and establish the conceptual, legal and conflicting points of relevance. This will allow describing the problems under study and propose alternatives for a sphere of integrative protection that harmonizes the edges of the preventive, the corrective and the prophylactic.

  2. How the amygdala affects emotional memory by altering brain network properties.

    Science.gov (United States)

    Hermans, Erno J; Battaglia, Francesco P; Atsak, Piray; de Voogd, Lycia D; Fernández, Guillén; Roozendaal, Benno

    2014-07-01

    The amygdala has long been known to play a key role in supporting memory for emotionally arousing experiences. For example, classical fear conditioning depends on neural plasticity within this anterior medial temporal lobe region. Beneficial effects of emotional arousal on memory, however, are not restricted to simple associative learning. Our recollection of emotional experiences often includes rich representations of, e.g., spatiotemporal context, visceral states, and stimulus-response associations. Critically, such memory features are known to bear heavily on regions elsewhere in the brain. These observations led to the modulation account of amygdala function, which postulates that amygdala activation enhances memory consolidation by facilitating neural plasticity and information storage processes in its target regions. Rodent work in past decades has identified the most important brain regions and neurochemical processes involved in these modulatory actions, and neuropsychological and neuroimaging work in humans has produced a large body of convergent data. Importantly, recent methodological developments make it increasingly realistic to monitor neural interactions underlying such modulatory effects as they unfold. For instance, functional connectivity network modeling in humans has demonstrated how information exchanges between the amygdala and specific target regions occur within the context of large-scale neural network interactions. Furthermore, electrophysiological and optogenetic techniques in rodents are beginning to make it possible to quantify and even manipulate such interactions with millisecond precision. In this paper we will discuss that these developments will likely lead to an updated view of the amygdala as a critical nexus within large-scale networks supporting different aspects of memory processing for emotionally arousing experiences. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks.

    Science.gov (United States)

    Constantinou, Anthony C; Fenton, Norman

    2017-01-01

    In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attention since there has been widespread belief that the new measures were sufficiently skewed against landlords that they could signal the end of the Buy-To-Let (BTL) investment era in the UK. This paper assesses the prospective performance of BTL investments in London from the investor's perspective, and examines the impact of incoming tax reforms using a novel Temporal Bayesian Network model. The model captures uncertainties of interest by simulating the impact of changing circumstances and the interventions available to an investor at various time-steps of a BTL investment portfolio. The simulation results suggest that the new tax reforms are likely to have a detrimental effect on net profits from rental income, and this hits risk-seeking investors who favour leverage much harder than risk-averse investors who do not seek to expand their property portfolio. The impact on net profits also poses substantial risks for lossmaking returns excluding capital gains, especially in the case of rising interest rates. While this makes it less desirable or even non-viable for some to continue being a landlord, based on the current status of all factors taken into consideration for simulation, investment prospects are still likely to remain good within a reasonable range of interest rate and capital growth rate variations. The results also suggest that the recent trend of property prices in London increasing faster than rents will not continue for much longer; either capital growth rates will have to decrease, rental growth rates will have to increase, or we shall observe a combination of the two events.

  4. The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks.

    Directory of Open Access Journals (Sweden)

    Anthony C Constantinou

    Full Text Available In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attention since there has been widespread belief that the new measures were sufficiently skewed against landlords that they could signal the end of the Buy-To-Let (BTL investment era in the UK. This paper assesses the prospective performance of BTL investments in London from the investor's perspective, and examines the impact of incoming tax reforms using a novel Temporal Bayesian Network model. The model captures uncertainties of interest by simulating the impact of changing circumstances and the interventions available to an investor at various time-steps of a BTL investment portfolio. The simulation results suggest that the new tax reforms are likely to have a detrimental effect on net profits from rental income, and this hits risk-seeking investors who favour leverage much harder than risk-averse investors who do not seek to expand their property portfolio. The impact on net profits also poses substantial risks for lossmaking returns excluding capital gains, especially in the case of rising interest rates. While this makes it less desirable or even non-viable for some to continue being a landlord, based on the current status of all factors taken into consideration for simulation, investment prospects are still likely to remain good within a reasonable range of interest rate and capital growth rate variations. The results also suggest that the recent trend of property prices in London increasing faster than rents will not continue for much longer; either capital growth rates will have to decrease, rental growth rates will have to increase, or we shall observe a combination of the two events.

  5. The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks

    Science.gov (United States)

    Fenton, Norman

    2017-01-01

    In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attention since there has been widespread belief that the new measures were sufficiently skewed against landlords that they could signal the end of the Buy-To-Let (BTL) investment era in the UK. This paper assesses the prospective performance of BTL investments in London from the investor’s perspective, and examines the impact of incoming tax reforms using a novel Temporal Bayesian Network model. The model captures uncertainties of interest by simulating the impact of changing circumstances and the interventions available to an investor at various time-steps of a BTL investment portfolio. The simulation results suggest that the new tax reforms are likely to have a detrimental effect on net profits from rental income, and this hits risk-seeking investors who favour leverage much harder than risk-averse investors who do not seek to expand their property portfolio. The impact on net profits also poses substantial risks for lossmaking returns excluding capital gains, especially in the case of rising interest rates. While this makes it less desirable or even non-viable for some to continue being a landlord, based on the current status of all factors taken into consideration for simulation, investment prospects are still likely to remain good within a reasonable range of interest rate and capital growth rate variations. The results also suggest that the recent trend of property prices in London increasing faster than rents will not continue for much longer; either capital growth rates will have to decrease, rental growth rates will have to increase, or we shall observe a combination of the two events. PMID:28654698

  6. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  7. Assessing artificial neural network performance in estimating the layer properties of pavements

    Directory of Open Access Journals (Sweden)

    Gloria Inés Beltran

    2014-05-01

    Full Text Available A major concern in assessing the structural condition of existing flexible pavements is the estimation of the mechanical properties of constituent layers, which is useful for the design and decision-making process in road management systems. This parameter identification problem is truly complex due to the large number of variables involved in pavement behavior. To this end, non-conventional adaptive or approximate solutions via Artificial Neural Networks – ANNs – are considered to properly map pavement response field measurements. Previous investigations have demonstrated the exceptional ability of ANNs in layer moduli estimation from non-destructive deflection tests, but most of the reported cases were developed using synthetic deflection data or hypothetical pavement systems. This paper presents further attempts to back-calculate layer moduli via ANN modeling, using a database gathered from field tests performed on three- and four-layer pavement systems. Traditional layer structuring and pavements with a stabilized subbase were considered. A three-stage methodology is developed in this study to design and validate an “optimum” ANN-based model, i.e., the best architecture possible along with adequate learning rules. An assessment of the resulting ANN model demonstrates its forecasting capabilities and efficiency in solving a complex parameter identification problem concerning pavements.

  8. Artificial neural network methodology: Application to predict magnetic properties of nanocrystalline alloys

    International Nuclear Information System (INIS)

    Hamzaoui, R.; Cherigui, M.; Guessasma, S.; ElKedim, O.; Fenineche, N.

    2009-01-01

    This paper is dedicated to the optimization of magnetic properties of iron based magnetic materials with regard to milling and coating process conditions using artificial neural network methodology. Fe-20 wt.% Ni and Fe-6.5 wt.% Si, alloys were obtained using two high-energy ball milling technologies, namely a planetary ball mill P4 vario ball mill from Fritsch and planetary ball mill from Retch. Further processing of Fe-Si powder allowed the spraying of the feedstock material using high-velocity oxy-fuel (HVOF) process to obtain a relatively dense coating. Input parameters were the disc Ω and vial ω speed rotations for the milling technique, and spray distance and oxygen flow rate in the case of coating process. Two main magnetic parameters are optimized namely the saturation magnetization and the coercivity. Predicted results depict clearly coupled effects of input parameters to vary magnetic parameters. In particular, the increase of saturation magnetization is correlated to the increase of the product Ωω (shock power) and the product of spray parameters. Largest coercivity values are correlated to the increase of the ratio Ω/ω (shock mode process) and the increase of the product of spray parameters.

  9. Understanding the doping effects on the structural and electrical properties of ultrathin carbon nanotube networks

    International Nuclear Information System (INIS)

    Zhou, Ying; Shimada, Satoru; Azumi, Reiko; Saito, Takeshi

    2015-01-01

    Similar to other semiconductor technology, doping of carbon nanotube (CNT) thin film is of great significance for performance improvement or modification. However, it still remains a challenge to seek a stable and effective dopant. In this paper, we unitize several spectroscopic techniques and electrical characterizations under various conditions to investigate the effects of typical dopants and related methods. Nitric acid (HNO 3 ) solution, I 2 vapor, and CuI nanoparticles are used to modify a series of ultrathin CNT networks. Although efficient charge transfer is achieved initially after doping, HNO 3 is not applicable because it suffers from severe reliability problems in structural and electrical properties, and it also causes a number of undesired structural defects. I 2 vapor doping at 150 °C can form some stable C-I bonding structures, resulting in relatively more stable but less efficient electrical performances. CuI nanoparticles seem to be an ideal dopant. Photonic curing enables the manipulation of CuI, which not only results in the construction of novel CNT-CuI hybrid structures but also encourages the deepest level of charge transfer doping. The excellent reliability as well as processing feasibility identify the bright perspective of CNT-CuI hybrid film for practical applications

  10. Understanding the doping effects on the structural and electrical properties of ultrathin carbon nanotube networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Ying, E-mail: y-shuu@aist.go.jp; Shimada, Satoru; Azumi, Reiko [Electronics and Photonics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, 305-8565 Tsukuba (Japan); Saito, Takeshi [Nanomaterials Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, 305-8565 Tsukuba (Japan)

    2015-12-07

    Similar to other semiconductor technology, doping of carbon nanotube (CNT) thin film is of great significance for performance improvement or modification. However, it still remains a challenge to seek a stable and effective dopant. In this paper, we unitize several spectroscopic techniques and electrical characterizations under various conditions to investigate the effects of typical dopants and related methods. Nitric acid (HNO{sub 3}) solution, I{sub 2} vapor, and CuI nanoparticles are used to modify a series of ultrathin CNT networks. Although efficient charge transfer is achieved initially after doping, HNO{sub 3} is not applicable because it suffers from severe reliability problems in structural and electrical properties, and it also causes a number of undesired structural defects. I{sub 2} vapor doping at 150 °C can form some stable C-I bonding structures, resulting in relatively more stable but less efficient electrical performances. CuI nanoparticles seem to be an ideal dopant. Photonic curing enables the manipulation of CuI, which not only results in the construction of novel CNT-CuI hybrid structures but also encourages the deepest level of charge transfer doping. The excellent reliability as well as processing feasibility identify the bright perspective of CNT-CuI hybrid film for practical applications.

  11. Correlation Between Fracture Network Properties and Stress Variability in Geological Media

    Science.gov (United States)

    Lei, Qinghua; Gao, Ke

    2018-05-01

    We quantitatively investigate the stress variability in fractured geological media under tectonic stresses. The fracture systems studied include synthetic fracture networks following power law length scaling and natural fracture patterns based on outcrop mapping. The stress field is derived from a finite-discrete element model, and its variability is analyzed using a set of mathematical formulations that honor the tensorial nature of stress data. We show that local stress perturbation, quantified by the Euclidean distance of a local stress tensor to the mean stress tensor, has a positive, linear correlation with local fracture intensity, defined as the total fracture length per unit area within a local sampling window. We also evaluate the stress dispersion of the entire stress field using the effective variance, that is, a scalar-valued measure of the overall stress variability. The results show that a well-connected fracture system under a critically stressed state exhibits strong local and global stress variabilities.

  12. Exact critical properties of two-dimensional polymer networks from conformal invariance

    International Nuclear Information System (INIS)

    Duplantier, B.

    1988-03-01

    An infinity of exact critical exponents for two-dimensional self-avoiding walks can be derived from conformal invariance and Coulomb gas techniques applied to the O(n) model and to the Potts model. They apply to polymer networks of any topology, for which a general scaling theory is given, valid in any dimension d. The infinite set of exponents has also been calculated to O(ε 2 ), for d=4-ε. The 2D study also includes other universality classes like the dense polymers, the Hamiltonian walks, the polymers at their θ-point. Exact correlation functions can be further given for Hamiltonian walks, and exact winding angle probability distributions for the self-avoiding walks

  13. A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network

    Directory of Open Access Journals (Sweden)

    De Graaf David

    2007-07-01

    Full Text Available Abstract Background The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. Results Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. Conclusion We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

  14. Looking for robust properties in the growth of an academic network: the case of the Uruguayan biological research community.

    Science.gov (United States)

    Cabana, Alvaro; Mizraji, Eduardo; Pomi, Andrés; Valle-Lisboa, Juan Carlos

    2008-04-01

    Graph-theoretical methods have recently been used to analyze certain properties of natural and social networks. In this work, we have investigated the early stages in the growth of a Uruguayan academic network, the Biology Area of the Programme for the Development of Basic Science (PEDECIBA). This transparent social network is a territory for the exploration of the reliability of clustering methods that can potentially be used when we are confronted with opaque natural systems that provide us with a limited spectrum of observables (happens in research on the relations between brain, thought and language). From our social net, we constructed two different graph representations based on the relationships among researchers revealed by their co-participation in Master's thesis committees. We studied these networks at different times and found that they achieve connectedness early in their evolution and exhibit the small-world property (i.e. high clustering with short path lengths). The data seem compatible with power law distributions of connectivity, clustering coefficients and betweenness centrality. Evidence of preferential attachment of new nodes and of new links between old nodes was also found in both representations. These results suggest that there are topological properties observed throughout the growth of the network that do not depend on the representations we have chosen but reflect intrinsic properties of the academic collective under study. Researchers in PEDECIBA are classified according to their specialties. We analysed the community structure detected by a standard algorithm in both representations. We found that much of the pre-specified structure is recovered and part of the mismatches can be attributed to convergent interests between scientists from different sub-disciplines. This result shows the potentiality of some clustering methods for the analysis of partially known natural systems.

  15. Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

    Science.gov (United States)

    Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

    2013-01-01

    Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

  16. High-pressure phase diagram of hydrogen and deuterium sulfides from first principles: Structural and vibrational properties including quantum and anharmonic effects

    Science.gov (United States)

    Bianco, Raffaello; Errea, Ion; Calandra, Matteo; Mauri, Francesco

    2018-06-01

    We study the structural and vibrational properties of the high-temperature superconducting sulfur trihydride and trideuteride in the high-pressure I m 3 ¯m and R 3 m phases by first-principles density-functional-theory calculations. On lowering pressure, the rhombohedral transition I m 3 ¯m →R 3 m is expected, with hydrogen-bond desymmetrization and occurrence of trigonal lattice distortion. With both Perdew-Burke-Ernzerhof (PBE) and Becke-Lee-Yang-Parr (BLYP) exchange-correlation functional, in hydrostatic conditions we find that, contrary to what is suggested in some recent experiments, if the rhombohedral distortion exists it affects mainly the hydrogen bonds, whereas the resulting cell distortion is minimal. We estimate that the occurrence of a stress anisotropy of approximately 10 % could explain this discrepancy. Assuming hydrostatic conditions, we calculate the critical pressure at which the rhombohedral transition occurs. Quantum and anharmonic effects, which are relevant in this system, are included at nonperturbative level with the stochastic self-consistent harmonic approximation. Within this approach, we determine the transition pressure by calculating the free-energy Hessian, a method that allows to estimate the critical pressure with much higher precision (and much lower computational cost) compared with the free-energy "finite-difference" approach previously used. Using PBE and BLYP, we find that quantum anharmonic effects are responsible for a strong reduction of the critical pressure with respect to the one obtained with the classical harmonic approach. Interestingly, for the two functionals, even if the transition pressures at classical harmonic level differ by 83 GPa, the transition pressures including quantum anharmonic effects differ only by 23 GPa. Moreover, we observe a prominent isotope effect, as we estimate higher transition pressure for D3S than for H3S . Finally, within the stochastic self-consistent harmonic approximation, with PBE

  17. Semi-Degradable Poly(β-amino ester) Networks with Temporally-Controlled Enhancement of Mechanical Properties

    Science.gov (United States)

    Safranski, David L.; Weiss, Daiana; Clark, J. Brian; Taylor, W.R.; Gall, Ken

    2014-01-01

    Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss in mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. PMID:24769113

  18. Stabilizing weighted complex networks

    International Nuclear Information System (INIS)

    Xiang Linying; Chen Zengqiang; Liu Zhongxin; Chen Fei; Yuan Zhuzhi

    2007-01-01

    Real networks often consist of local units which interact with each other via asymmetric and heterogeneous connections. In this paper, the V-stability problem is investigated for a class of asymmetric weighted coupled networks with nonidentical node dynamics, which includes the unweighted network as a special case. Pinning control is suggested to stabilize such a coupled network. The complicated stabilization problem is reduced to measuring the semi-negative property of the characteristic matrix which embodies not only the network topology, but also the node self-dynamics and the control gains. It is found that network stabilizability depends critically on the second largest eigenvalue of the characteristic matrix. The smaller the second largest eigenvalue is, the more the network is pinning controllable. Numerical simulations of two representative networks composed of non-chaotic systems and chaotic systems, respectively, are shown for illustration and verification

  19. Calculation for the thermodynamic properties of an alternative refrigerant (R508b) using artificial neural network

    International Nuclear Information System (INIS)

    Soezen, Adnan; Ozalp, Mehmet; Arcaklioglu, Erol

    2007-01-01

    This study proposes a alternative approach based on artificial neural networks (ANNs) to determine the thermodynamic properties - specific volume, enthalpy and entropy - of an alternative refrigerant (R508b) for both saturated liquid-vapor region (wet vapor) and superheated vapor region. In the ANN, the back-propagation learning algorithm with two different variants, namely scaled conjugate gradient (SCG) and Levenberg-Marquardt (LM), and Logistic Sigmoid transfer function were used to determine the best approach. The most suitable algorithm and with appropriate number of neurons (i.e. 7) in the hidden layer is found to be the LM algorithm which has provided the minimum error. For wet vapor region, R 2 values - which are errors known as absolute fraction of variance - are 0.983495, 0.969027, 0.999984, 0.999963, 0.999981, and 0.999975, for specific volume, enthalpy and entropy for training and testing, respectively. Similarly, for superheated vapor, they are: 0.995346, 0.996947, 0.999996, 0.999997, 0.999974, and 0.999975, for training and testing, respectively. According to the regression analysis results, R 2 values are 0.9312, 0.9708, 0.9428, 0.9343, 0.967 and 0.9546 for specific volume, enthalpy and entropy for wet vapor region and superheated vapor, respectively. The comparisons of the results suggest that, ANN provided results comfortably within the acceptable range. This study, deals with the potential application of the ANNs to represent PVTx (pressure-specific volume-temperature-vapor quality) data. Therefore, reducing the risk of experimental uncertainties and also removing the need for complex analytic equations requiring long computational time and efforts

  20. Parcels and Land Ownership, Square-mile, section-wide, property ownerhip parcel and lot-block boundaries. Includes original platted lot lines. These coverages are maintained interactively by GIS staff. Primary attributes include Parcel IDS (Control, Key, and PIN), platted lot and, Published in 2008, 1:1200 (1in=100ft) scale, Sedgwick County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Parcels and Land Ownership dataset current as of 2008. Square-mile, section-wide, property ownerhip parcel and lot-block boundaries. Includes original platted lot...

  1. Photocrosslinked PLA-PEO-PLA Hydrogels from Self-Assembled Physical Networks: Mechanical Properties and Influence of Assumed Constitutive Relationships

    OpenAIRE

    Sanabria-DeLong, Naomi; Crosby, Alfred J.; Tew, Gregory N.

    2008-01-01

    Poly(lactide) – block – poly(ethylene oxide) – block – poly(lactide) [PLA-PEO-PLA] triblock copolymers are known to form physical hydrogels in water, due to the polymer's amphiphilicity. Their mechanical properties, biocompatibility, and biodegradability have made them attractive for use as soft tissue scaffolds. However, the network junction points are not covalently crosslinked and in a highly aqueous environment these hydrogels adsorb more water, transform from gel to sol, and lose the des...

  2. Altered small-world properties of gray matter networks in breast cancer

    Directory of Open Access Journals (Sweden)

    Hosseini S M

    2012-05-01

    Full Text Available Abstract Background Breast cancer survivors, particularly those treated with chemotherapy, are at significantly increased risk for long-term cognitive and neurobiologic impairments. These deficits tend to involve skills that are subserved by distributed brain networks. Additionally, neuroimaging studies have shown a diffuse pattern of brain structure changes in chemotherapy-treated breast cancer survivors that might impact large-scale brain networks. Methods We therefore applied graph theoretical analysis to compare the gray matter structural networks of female breast cancer survivors with a history of chemotherapy treatment and healthy age and education matched female controls. Results Results revealed reduced clustering coefficient and small-world index in the brain network of the breast cancer patients across a range of network densities. In addition, the network of the breast cancer group had less highly interactive nodes and reduced degree/centrality in the frontotemporal regions compared to controls, which may help explain the common impairments of memory and executive functioning among these patients. Conclusions These results suggest that breast cancer and chemotherapy may decrease regional connectivity as well as global network organization and integration, reducing efficiency of the network. To our knowledge, this is the first report of altered large-scale brain networks associated with breast cancer and chemotherapy.

  3. Dynamical Properties of Discrete-Time Background Neural Networks with Uniform Firing Rate

    Directory of Open Access Journals (Sweden)

    Min Wan

    2013-01-01

    Full Text Available The dynamics of a discrete-time background network with uniform firing rate and background input is investigated. The conditions for stability are firstly derived. An invariant set is then obtained so that the nondivergence of the network can be guaranteed. In the invariant set, it is proved that all trajectories of the network starting from any nonnegative value will converge to a fixed point under some conditions. In addition, bifurcation and chaos are discussed. It is shown that the network can engender bifurcation and chaos with the increase of background input. The computations of Lyapunov exponents confirm the chaotic behaviors.

  4. Characterisation of anisotropic etching in KOH using network etch rate function model: influence of an applied potential in terms of microscopic properties

    International Nuclear Information System (INIS)

    Nguyen, Q D; Elwenspoek, M

    2006-01-01

    Using the network etch rate function model, the anisotropic etch rate of p-type single crystal silicon was characterised in terms of microscopic properties including step velocity, step and terrace roughening. The anisotropic etch rate data needed have been obtained using a combination of 2 wagon wheel patterns on different substrate and 1 offset trench pattern. Using this procedure the influence of an applied potential has been investigated in terms of microscopic properties. Model parameter trends show a good correlation with chemical/electrochemical reaction mechanism and mono- and dihydride terminated steps reactivity difference. Results also indicate a minimum in (111) terrace roughening which results in a peak in anisotropic ratio at the non-OCP applied potential of -1250 mV vs OCP

  5. Spike-timing computation properties of a feed-forward neural network model

    Directory of Open Access Journals (Sweden)

    Drew Benjamin Sinha

    2014-01-01

    Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

  6. Graph properties of synchronized cortical networks during visual working memory maintenance.

    Science.gov (United States)

    Palva, Satu; Monto, Simo; Palva, J Matias

    2010-02-15

    Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

  7. The DSM-5 Dimensional Anxiety Scales in a Dutch non-clinical sample : Psychometric properties including the adult separation anxiety disorder scale

    NARCIS (Netherlands)

    Möller, E.L.; Bögels, S.M.

    With DSM-5, the American Psychiatric Association encourages complementing categorical diagnoses with dimensional severity ratings. We therefore examined the psychometric properties of the DSM-5 Dimensional Anxiety Scales, a set of brief dimensional scales that are consistent in content and structure

  8. Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

    Directory of Open Access Journals (Sweden)

    Yashna Paul

    2016-01-01

    Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

  9. NAIAD - a computer program for calculation of the steady state and transient behaviour (including LOCA) of compressible two-phase coolant in networks

    International Nuclear Information System (INIS)

    Trimble, G.D.; Turner, W.J.

    1976-04-01

    The three one-dimensional conservation equations of mass, momentum and energy are solved by a stable finite difference scheme which allows the time step to be varied in response to accuracy requirements. Consideration of numerical stability is not necessary. Slip between the phases is allowed and descriptions of complex hydraulic components can be added into specially provided user routines. Intrinsic choking using any of the nine slip models is possible. A pipe or fuel model and detailed surface heat transfer are included. (author)

  10. Voxel Scale Complex Networks of Functional Connectivity in the Rat Brain: Neurochemical State Dependence of Global and Local Topological Properties

    Directory of Open Access Journals (Sweden)

    Adam J. Schwarz

    2012-01-01

    Full Text Available Network analysis of functional imaging data reveals emergent features of the brain as a function of its topological properties. However, the brain is not a homogeneous network, and the dependence of functional connectivity parameters on neuroanatomical substrate and parcellation scale is a key issue. Moreover, the extent to which these topological properties depend on underlying neurochemical changes remains unclear. In the present study, we investigated both global statistical properties and the local, voxel-scale distribution of connectivity parameters of the rat brain. Different neurotransmitter systems were stimulated by pharmacological challenge (d-amphetamine, fluoxetine, and nicotine to discriminate between stimulus-specific functional connectivity and more general features of the rat brain architecture. Although global connectivity parameters were similar, mapping of local connectivity parameters at high spatial resolution revealed strong neuroanatomical dependence of functional connectivity in the rat brain, with clear differentiation between the neocortex and older brain regions. Localized foci of high functional connectivity independent of drug challenge were found in the sensorimotor cortices, consistent with the high neuronal connectivity in these regions. Conversely, the topological properties and node roles in subcortical regions varied with neurochemical state and were dependent on the specific dynamics of the different functional processes elicited.

  11. Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

    Science.gov (United States)

    Arbabi, Vahid; Pouran, Behdad; Campoli, Gianni; Weinans, Harrie; Zadpoor, Amir A

    2016-03-21

    One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to simulate the indentation test with finite element models and use an optimization algorithm to estimate the mechanical properties of cartilage. The modeling procedure is cumbersome, and the simulations need to be repeated for every new experiment. For the first time, we propose a method for fast and accurate estimation of the mechanical and physical properties of cartilage as a poroelastic material with the aid of artificial neural networks. In our study, we used finite element models to simulate the indentation for poroelastic materials with wide combinations of mechanical and physical properties. The obtained force-time curves are then divided into three parts: the first two parts of the data is used for training and validation of an artificial neural network, while the third part is used for testing the trained network. The trained neural network receives the force-time curves as the input and provides the properties of cartilage as the output. We observed that the trained network could accurately predict the properties of cartilage within the range of properties for which it was trained. The mechanical and physical properties of cartilage could therefore be estimated very fast, since no additional finite element modeling is required once the neural network is trained. The robustness of the trained artificial neural network in determining the properties of cartilage based on noisy force-time data was assessed by introducing noise to the simulated force-time data. We found that the training procedure could be optimized so as to maximize the robustness of the neural network against noisy force-time data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

    Directory of Open Access Journals (Sweden)

    Zheng Wang

    Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

  13. Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

    Science.gov (United States)

    Nacif el Alaoui, Reda

    Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

  14. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    International Nuclear Information System (INIS)

    Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

    2015-01-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified

  15. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Energy Technology Data Exchange (ETDEWEB)

    Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  16. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago Vanderlei; Giannitsarou, Chrysi; Johnson, CR

    2017-01-01

    We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and define a network aggregator that preserves network cohesion.

  17. The microstructure network and thermoelectric properties of bulk (Bi,Sb)2Te3

    DEFF Research Database (Denmark)

    Xie, Wenjie; Hitchcock, Dale A.; Kang, Hye J.

    2012-01-01

    We report small-angle neutron scattering studies on the microstructure network in bulk (Bi,Sb)(2)Te-3 synthesized by the melt-spinning (MS) and the spark-plasma-sintering (SPS) process. We find that rough interfaces of multiscale microstructures generated by the MS are responsible for the large...... reduction of both lattice thermal conductivity and electrical conductivity. Our study also finds that subsequent SPS forms a microstructure network of similar to 10 nm thick lamellae and smooth interfaces between them. This nanoscale microstructure network with smooth interfaces increases electrical...... conductivity while keeping a low thermal conductivity, making it an ideal microstructure for high thermoelectric efficiency....

  18. Audiovisual synchrony enhances BOLD responses in a brain network including multisensory STS while also enhancing target-detection performance for both modalities

    Science.gov (United States)

    Marchant, Jennifer L; Ruff, Christian C; Driver, Jon

    2012-01-01

    The brain seeks to combine related inputs from different senses (e.g., hearing and vision), via multisensory integration. Temporal information can indicate whether stimuli in different senses are related or not. A recent human fMRI study (Noesselt et al. [2007]: J Neurosci 27:11431–11441) used auditory and visual trains of beeps and flashes with erratic timing, manipulating whether auditory and visual trains were synchronous or unrelated in temporal pattern. A region of superior temporal sulcus (STS) showed higher BOLD signal for the synchronous condition. But this could not be related to performance, and it remained unclear if the erratic, unpredictable nature of the stimulus trains was important. Here we compared synchronous audiovisual trains to asynchronous trains, while using a behavioral task requiring detection of higher-intensity target events in either modality. We further varied whether the stimulus trains had predictable temporal pattern or not. Synchrony (versus lag) between auditory and visual trains enhanced behavioral sensitivity (d') to intensity targets in either modality, regardless of predictable versus unpredictable patterning. The analogous contrast in fMRI revealed BOLD increases in several brain areas, including the left STS region reported by Noesselt et al. [2007: J Neurosci 27:11431–11441]. The synchrony effect on BOLD here correlated with the subject-by-subject impact on performance. Predictability of temporal pattern did not affect target detection performance or STS activity, but did lead to an interaction with audiovisual synchrony for BOLD in inferior parietal cortex. PMID:21953980

  19. Evaluating the hydraulic and transport properties of peat soil using pore network modeling and X-ray micro computed tomography

    Science.gov (United States)

    Gharedaghloo, Behrad; Price, Jonathan S.; Rezanezhad, Fereidoun; Quinton, William L.

    2018-06-01

    Micro-scale properties of peat pore space and their influence on hydraulic and transport properties of peat soils have been given little attention so far. Characterizing the variation of these properties in a peat profile can increase our knowledge on the processes controlling contaminant transport through peatlands. As opposed to the common macro-scale (or bulk) representation of groundwater flow and transport processes, a pore network model (PNM) simulates flow and transport processes within individual pores. Here, a pore network modeling code capable of simulating advective and diffusive transport processes through a 3D unstructured pore network was developed; its predictive performance was evaluated by comparing its results to empirical values and to the results of computational fluid dynamics (CFD) simulations. This is the first time that peat pore networks have been extracted from X-ray micro-computed tomography (μCT) images of peat deposits and peat pore characteristics evaluated in a 3D approach. Water flow and solute transport were modeled in the unstructured pore networks mapped directly from μCT images. The modeling results were processed to determine the bulk properties of peat deposits. Results portray the commonly observed decrease in hydraulic conductivity with depth, which was attributed to the reduction of pore radius and increase in pore tortuosity. The increase in pore tortuosity with depth was associated with more decomposed peat soil and decreasing pore coordination number with depth, which extended the flow path of fluid particles. Results also revealed that hydraulic conductivity is isotropic locally, but becomes anisotropic after upscaling to core-scale; this suggests the anisotropy of peat hydraulic conductivity observed in core-scale and field-scale is due to the strong heterogeneity in the vertical dimension that is imposed by the layered structure of peat soils. Transport simulations revealed that for a given solute, the effective

  20. Analysis of transmission properties in an indoor wireless sensor network based on a full-factorial design

    International Nuclear Information System (INIS)

    Christmann, Dennis; Martinovic, Ivan; Schmitt, Jens B

    2010-01-01

    In this paper, we systematically investigate different factors and their effects on the wireless transmission properties using a full-factorial experimental design of a wireless sensor network in a real-world indoor environment. We quantify the impact of primary factors such as the wireless channel, physical position, transmission power and line of sight, as well as their interactions on the received signal strength (RSS). While some of our results support conventional assumptions, this study also shows that there are several properties which are in contrast to existing findings. For example, there is no significant correlation in the measured RSS between differently located but equally distant transmitters, yet the correlation coefficient for the two directions of a single link between two transmitters is above 94%, leading to very symmetric links that differ only in a few dBm for the two directions. Further analysis reveals the strong interaction of transmission frequency and physical position, while the transmission power has only an isolated, non-interacting effect on the RSS. Since the analyzed network consists of commodity motes utilizing TI's well-known IEEE 802.15.4 compliant CC2420 transceiver, the results of this experimental analysis can serve as valuable insights in planning and deploying wireless sensor networks in different application scenarios

  1. Novel amphiphilic poly(dimethylsiloxane) based polyurethane networks tethered with carboxybetaine and their combined antibacterial and anti-adhesive property

    Science.gov (United States)

    Jiang, Jingxian; Fu, Yuchen; Zhang, Qinghua; Zhan, Xiaoli; Chen, Fengqiu

    2017-08-01

    The traditional nonfouling materials are powerless against bacterial cells attachment, while the hydrophobic bactericidal surfaces always suffer from nonspecific protein adsorption and dead bacterial cells accumulation. Here, amphiphilic polyurethane (PU) networks modified with poly(dimethylsiloxane) (PDMS) and cationic carboxybetaine diol through simple crosslinking reaction were developed, which had an antibacterial efficiency of 97.7%. Thereafter, the hydrolysis of carboxybetaine ester into zwitterionic groups brought about anti-adhesive properties against bacteria and proteins. The surface chemical composition and wettability performance of the PU network surfaces were investigated by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The surface distribution of PDMS and zwitterionic segments produced an obvious amphiphilic heterogeneous surface, which was demonstrated by atomic force microscopy (AFM). Enzyme-linked immunosorbent assays (ELISA) were used to test the nonspecific protein adsorption behaviors. With the advantages of the transition from excellent bactericidal performance to anti-adhesion and the combination of fouling resistance and fouling release property, the designed PDMS-based amphiphilic PU network shows great application potential in biomedical devices and marine facilities.

  2. Effect of diluent on the gel point and mechanical properties of polyurethane networks

    Czech Academy of Sciences Publication Activity Database

    Ďuračková, Andrea; Valentová, H.; Dušková, Miroslava; Dušek, Karel

    2007-01-01

    Roč. 58, č. 1 (2007), s. 201-211 ISSN 0170-0839. [Microsymposium on Poly mer Gels and Networks /44./. Prague, 10.07.2005-14.07.2005] EU Projects: European Commission(XE) 500361 - NANOFUN- POLY Institutional research plan: CEZ:AV0Z40500505 Keywords : gelation * cyclization * network structure formation Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.022, year: 2007

  3. Resilient Amorphous Networks Prepared by Photo-Crosslinking High-Molecular-Weight D,L-Lactide and Trimethylene Carbonate Macromers: Mechanical Properties and Shape-Memory Behavior

    NARCIS (Netherlands)

    Sharifi, Shahriar; Grijpma, Dirk W.

    2012-01-01

    Tough networks are prepared by photo-crosslinking high-molecular-weight DLLA and TMC macromers. These amorphous networks exhibit tunable thermal and mechanical properties and have excellent shape-memory features. Variation of the monomer ratio allows adjustment of Tg between approximately −13 and

  4. Structure and Properties of Ti-19.7Nb-5.8Ta Shape Memory Alloy Subjected to Thermomechanical Processing Including Aging

    Science.gov (United States)

    Dubinskiy, S.; Brailovski, Vladimir; Prokoshkin, S.; Pushin, V.; Inaekyan, K.; Sheremetyev, V.; Petrzhik, M.; Filonov, M.

    2013-09-01

    In this work, the ternary Ti-19.7Nb-5.8Ta (at.%) alloy for biomedical applications was studied. The ingot was manufactured by vacuum arc melting with a consumable electrode and then subjected to hot forging. Specimens were cut from the ingot and processed by cold rolling with e = 0.37 of logarithmic thickness reduction and post-deformation annealing (PDA) between 400 and 750 °C (1 h). Selected samples were subjected to aging at 300 °C (10 min to 3 h). The influence of the thermomechanical processing on the alloy's structure, phase composition, and mechanical and functional properties was studied. It was shown that thermomechanical processing leads to the formation of a nanosubgrained structure (polygonized with subgrains below 100 nm) in the 500-600 °C PDA range, which transforms to a recrystallized structure of β-phase when PDA temperature increases. Simultaneously, the phase composition and the β → α″ transformation kinetics vary. It was found that after conventional cold rolling and PDA, Ti-Nb-Ta alloy manifests superelastic and shape memory behaviors. During aging at 300 °C (1 h), an important quantity of randomly scattered equiaxed ω-precipitates forms, which results in improved superelastic cyclic properties. On the other hand, aging at 300 °C (3 h) changes the ω-precipitates' particle morphology from equiaxed to elongated and leads to their coarsening, which negatively affects the superelastic and shape memory functional properties of Ti-Nb-Ta alloy.

  5. Effects of Ceramic Density and Sintering Temperature on the Mechanical Properties of a Novel Polymer-Infiltrated Ceramic-Network Zirconia Dental Restorative (Filling) Material.

    Science.gov (United States)

    Li, Weiyan; Sun, Jian

    2018-05-10

    BACKGROUND Polymer-infiltrated ceramic-network (PICN) dental material is a new and practical development in orthodontics. Sintering is the process of forming a stable solid mass from a powder by heating without melting. The aim of this study was to evaluate the effects of sintering temperature on the mechanical properties of a PICN zirconia dental material. MATERIAL AND METHODS A dense zirconia ceramic and four PICN zirconia dental materials, with varying porosities, were sintered at three different temperatures; 12 PICN zirconia dental materials based on these porous ceramics were prepared, as well as a pure polymer. After the specimen preparation, flexural strength and elastic modulus values were measured using the three-point bending test, and fracture toughness were determined by the single-edge notched beam (SENB) method. The Vickers hardness test method was used with an indentation strength (IS) test. Scanning electron microscopy (SEM) was used to examine the microstructure of the ceramic surface and the fracture surface. RESULTS Mechanical properties of the PICN dental materials, including flexural strength, elastic modulus, fracture toughness, and hardness, were more similar to the properties of natural teeth when compared with traditional dental ceramic materials, and were affected by the density and sintering temperature. SEM showed that the porous ceramic network became cohesive and that the length of cracks in the PICN dental material was reduced. CONCLUSIONS PICN zirconia dental materials were characterized by similar mechanical properties to natural dental tissues, but further studies are required continue to improve the similarities with natural human enamel and dentin.

  6. Prediction of Thermal Properties of Sweet Sorghum Bagasse as a Function of Moisture Content Using Artificial Neural Networks and Regression Models

    Directory of Open Access Journals (Sweden)

    Gosukonda Ramana

    2017-06-01

    Full Text Available Artificial neural networks (ANN and traditional regression models were developed for prediction of thermal properties of sweet sorghum bagasse as a function of moisture content and room temperature. Predictions were made for three thermal properties: 1 thermal conductivity, 2 volumetric specific heat, and 3 thermal diffusivity. Each thermal property had five levels of moisture content (8.52%, 12.93%, 18.94%, 24.63%, and 28.62%, w. b. and room temperature as inputs. Data were sub-partitioned for training, testing, and validation of models. Backpropagation (BP and Kalman Filter (KF learning algorithms were employed to develop nonparametric models between input and output data sets. Statistical indices including correlation coefficient (R between actual and predicted outputs were produced for selecting the suitable models. Prediction plots for thermal properties indicated that the ANN models had better accuracy from unseen patterns as compared to regression models. In general, ANN models were able to strongly generalize and interpolate unseen patterns within the domain of training.

  7. Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

    Science.gov (United States)

    Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

    2018-05-01

    The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

  8. Dually cross-linked single network poly(acrylic acid) hydrogels with superior mechanical properties and water absorbency.

    Science.gov (United States)

    Zhong, Ming; Liu, Yi-Tao; Liu, Xiao-Ying; Shi, Fu-Kuan; Zhang, Li-Qin; Zhu, Mei-Fang; Xie, Xu-Ming

    2016-06-28

    Poly(acrylic acid) (PAA) hydrogels with superior mechanical properties, based on a single network structure with dual cross-linking, are prepared by one-pot free radical polymerization. The network structure of the PAA hydrogels is composed of dual cross-linking: a dynamic and reversible ionic cross-linking among the PAA chains enabled by Fe(3+) ions, and a sparse covalent cross-linking enabled by a covalent cross-linker (Bis). Under deformation, the covalently cross-linked PAA chains remain intact to maintain their original configuration, while the Fe(3+)-enabled ionic cross-linking among the PAA chains is broken to dissipate energy and then recombined. It is found that the mechanical properties of the PAA hydrogels are significantly influenced by the contents of covalent cross-linkers, Fe(3+) ions and water, which can be adjusted within a substantial range and thus broaden the applications of the hydrogels. Meanwhile, the PAA hydrogels have excellent recoverability based on the dynamic and reversible ionic cross-linking enabled by Fe(3+) ions. Moreover, the swelling capacity of the PAA hydrogels is as high as 1800 times in deionized water due to the synergistic effects of ionic and covalent cross-linkings. The combination of balanced mechanical properties, efficient recoverability, high swelling capacity and facile preparation provides a new method to obtain high-performance hydrogels.

  9. Solution processed zinc oxide nanopyramid/silver nanowire transparent network films with highly tunable light scattering properties

    KAUST Repository

    Mehra, Saahil

    2013-01-01

    Metal nanowire transparent networks are promising replacements to indium tin oxide (ITO) transparent electrodes for optoelectronic devices. While the transparency and sheet resistance are key metrics for transparent electrode performance, independent control of the film light scattering properties is important to developing multifunctional electrodes for improved photovoltaic absorption. Here we show that controlled incorporation of ZnO nanopyramids into a metal nanowire network film affords independent, highly tunable control of the scattering properties (haze) with minimal effects on the transparency and sheet resistance. Varying the zinc oxide/silver nanostructure ratios prior to spray deposition results in sheet resistances, transmission (600 nm), and haze (600 nm) of 6-30 Ω □-1, 68-86%, and 34-66%, respectively. Incorporation of zinc oxide nanopyramid scattering agents into the conducting nanowire mesh has a negligible effect on mesh connectivity, providing a straightforward method of controlling electrode scattering properties. The decoupling of the film scattering power and electrical characteristics makes these films promising candidates for highly scattering transparent electrodes in optoelectronic devices and can be generalized to other metal nanowire films as well as carbon nanotube transparent electrodes. © 2013 The Royal Society of Chemistry.

  10. Determination of Elastic and Dissipative Properties of Material Using Combination of FEM and Complex Artificial Neural Networks

    Science.gov (United States)

    Soloviev, A. N.; Giang, N. D. T.; Chang, S.-H.

    This paper describes the application of complex artificial neural networks (CANN) in the inverse identification problem of the elastic and dissipative properties of solids. Additional information for the inverse problem serves the components of the displacement vector measured on the body boundary, which performs harmonic oscillations at the first resonant frequency. The process of displacement measurement in this paper is simulated using calculation of finite element (FE) software ANSYS. In the shown numerical example, we focus on the accurate identification of elastic modulus and quality of material depending on the number of measurement points and their locations as well as on the architecture of neural network and time of the training process, which is conducted by using algorithms RProp, QuickProp.

  11. Structural and electronic properties of InN nanowire network grown by vapor-liquid-solid method

    Directory of Open Access Journals (Sweden)

    B. K. Barick

    2015-05-01

    Full Text Available Growth of InN nanowires have been carried out on quartz substrates at different temperatures by vapor-liquid-solid (VLS technique using different thicknesses of Au catalyst layer. It has been found that a narrow window of Au layer thickness and growth temperature leads to multi-nucleation, in which each site acts as the origin of several nanowires. In this multi-nucleation regime, several tens of micrometer long wires with diameter as small as 20 nm are found to grow along [ 11 2 ̄ 0 ] direction (a-plane to form a dense network. Structural and electronic properties of these wires are studied. As grown nanowires show degenerate n-type behavior. Furthermore, x-ray photoemission study reveals an accumulation of electrons on the surface of these nanowires. Interestingly, the wire network shows persistence of photoconductivity for several hours after switching off the photoexcitation.

  12. Structural and electronic properties of InN nanowire network grown by vapor-liquid-solid method

    Science.gov (United States)

    Barick, B. K.; Rodríguez-Fernández, Carlos; Cantarero, Andres; Dhar, S.

    2015-05-01

    Growth of InN nanowires have been carried out on quartz substrates at different temperatures by vapor-liquid-solid (VLS) technique using different thicknesses of Au catalyst layer. It has been found that a narrow window of Au layer thickness and growth temperature leads to multi-nucleation, in which each site acts as the origin of several nanowires. In this multi-nucleation regime, several tens of micrometer long wires with diameter as small as 20 nm are found to grow along [ 11 2 ¯ 0 ] direction (a-plane) to form a dense network. Structural and electronic properties of these wires are studied. As grown nanowires show degenerate n-type behavior. Furthermore, x-ray photoemission study reveals an accumulation of electrons on the surface of these nanowires. Interestingly, the wire network shows persistence of photoconductivity for several hours after switching off the photoexcitation.

  13. Low percolation transitions in carbon nanotube networks dispersed in a polymer matrix: dielectric properties, simulations and experiments.

    Science.gov (United States)

    Simoes, Ricardo; Silva, Jaime; Vaia, Richard; Sencadas, Vítor; Costa, Pedro; Gomes, João; Lanceros-Méndez, Senentxu

    2009-01-21

    The low concentration behaviour and the increase of the dielectric constant in carbon nanotubes/polymer nanocomposites near the percolation threshold are still not well understood. In this work, a numerical model has been developed which focuses on the effect of the inclusion of conductive fillers in a dielectric polymer matrix on the dielectric constant and the dielectric strength. Experiments have been carried out in carbon nanotubes/poly(vinylidene fluoride) nanocomposites in order to compare to the simulation results. This work shows how the critical concentration is related to the formation of capacitor networks and that these networks give rise to high variations in the electrical properties of the composites. Based on numerical studies, the dependence of the percolation transition on the preparation of the nanocomposite is discussed. Finally, based on numerical and experimental results, both ours and from other authors, the causes of anomalous percolation behaviour of the dielectric constant are identified.

  14. Structural and electronic properties of InN nanowire network grown by vapor-liquid-solid method

    Energy Technology Data Exchange (ETDEWEB)

    Barick, B. K., E-mail: bkbarick@gmail.com, E-mail: subho-dh@yahoo.co.in; Dhar, S., E-mail: bkbarick@gmail.com, E-mail: subho-dh@yahoo.co.in [Department of Physics, Indian Institute of Technology, Bombay, Mumbai-400076 (India); Rodríguez-Fernández, Carlos; Cantarero, Andres [Materials Science Institute, University of Valencia, PO Box 22085, 46071 Valencia (Spain)

    2015-05-15

    Growth of InN nanowires have been carried out on quartz substrates at different temperatures by vapor-liquid-solid (VLS) technique using different thicknesses of Au catalyst layer. It has been found that a narrow window of Au layer thickness and growth temperature leads to multi-nucleation, in which each site acts as the origin of several nanowires. In this multi-nucleation regime, several tens of micrometer long wires with diameter as small as 20 nm are found to grow along [112{sup -}0] direction (a-plane) to form a dense network. Structural and electronic properties of these wires are studied. As grown nanowires show degenerate n-type behavior. Furthermore, x-ray photoemission study reveals an accumulation of electrons on the surface of these nanowires. Interestingly, the wire network shows persistence of photoconductivity for several hours after switching off the photoexcitation.

  15. Transport properties of field effect transistors with randomly networked single walled carbon nanotubes grown by plasma enhanced chemical vapour deposition

    International Nuclear Information System (INIS)

    Kim, Un Jeong; Park, Wanjun

    2009-01-01

    The transport properties of randomly networked single walled carbon nanotube (SWNT) transistors with different channel lengths of L c = 2-10 μm were investigated. Randomly networked SWNTs were directly grown for the two different densities of ρ ∼ 25 μm -2 and ρ ∼ 50 μm -2 by water plasma enhanced chemical vapour deposition. The field effect transport is governed mainly by formation of the current paths that is related to the nanotube density. On the other hand, the off-state conductivity deviates from linear dependence for both nanotube density and channel length. The field effect mobility of holes is estimated as 4-13 cm 2 V -1 s -1 for the nanotube transistors based on the simple MOS theory. The mobility is increased for the higher density without meaningful dependence on the channel lengths.

  16. Thermochemical properties of silver tellurides including empressite (AgTe) and phase diagrams for Ag-Te and Ag-Te-O

    Science.gov (United States)

    Voronin, Mikhail V.; Osadchii, Evgeniy G.; Brichkina, Ekaterina A.

    2017-10-01

    This study compiles original experimental and literature data on the thermodynamic properties (ΔfG°, S°, ΔfH°) of silver tellurides (α-Ag2Te, β-Ag2Te, Ag1.9Te, Ag5Te3, AgTe) obtained by the method of solid-state galvanic cell with the RbAg4I5 and AgI solid electrolytes. The thermodynamic data for empressite (AgTe, pure fraction from Empress Josephine Mine, Colorado USA) have been obtained for the first time by the electrochemical experiment with the virtual reaction Ag + Te = AgTe. The Ag-Te phase diagrams in the T - x and log fTe2 (gas) - 1/ T coordinates have been refined, and the ternary Ag-Te-O diagrams with Ag-Te-TeO2 (paratellurite) composition range have been calculated.

  17. Prediction of mechanical properties of a warm compacted molybdenum prealloy using artificial neural network and adaptive neuro-fuzzy models

    International Nuclear Information System (INIS)

    Zare, Mansour; Vahdati Khaki, Jalil

    2012-01-01

    Highlights: ► ANNs and ANFIS fairly predicted UTS and YS of warm compacted molybdenum prealloy. ► Effects of composition, temperature, compaction pressure on output were studied. ► ANFIS model was in better agreement with experimental data from published article. ► Sintering temperature had the most significant effect on UTS and YS. -- Abstract: Predictive models using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were successfully developed to predict yield strength and ultimate tensile strength of warm compacted 0.85 wt.% molybdenum prealloy samples. To construct these models, 48 different experimental data were gathered from the literature. A portion of the data set was randomly chosen to train both ANN with back propagation (BP) learning algorithm and ANFIS model with Gaussian membership function and the rest was implemented to verify the performance of the trained network against the unseen data. The generalization capability of the networks was also evaluated by applying new input data within the domain covered by the training pattern. To compare the obtained results, coefficient of determination (R 2 ), root mean squared error (RMSE) and average absolute error (AAE) indexes were chosen and calculated for both of the models. The results showed that artificial neural network and adaptive neuro-fuzzy system were both potentially strong for prediction of the mechanical properties of warm compacted 0.85 wt.% molybdenum prealloy; however, the proposed ANFIS showed better performance than the ANN model. Also, the ANFIS model was subjected to a sensitivity analysis to find the significant inputs affecting mechanical properties of the samples.

  18. Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

    2017-05-01

    The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  20. Controlled structure and properties of silicate nanoparticle networks for incorporation of biosystem components

    International Nuclear Information System (INIS)

    Sakai-Kato, Kumiko; Kawanishi, Toru; Hasegawa, Toshiaki; Takaoka, Akio; Kato, Masaru; Toyo'oka, Toshimasa; Utsunomiya-Tate, Naoko

    2011-01-01

    Inorganic nanoparticles are of technological interest in many fields. We created silicate nanoparticle hydrogels that effectively incorporated biomolecules that are unstable and involved in complicated reactions. The size of the silicate nanoparticles strongly affected both the physical characteristics of the resulting hydrogel and the activity of biomolecules incorporated within the hydrogel. We used high-resolution transmission electron microscopy (TEM) to analyze in detail the hydrogel network patterns formed by the silicate nanoparticles. We obtained clear nanostructured images of biomolecule-nanoparticle composite hydrogels. The TEM images also showed that larger silicate nanoparticles (22 nm) formed more loosely associated silicate networks than did smaller silicate nanoparticles (7 nm). The loosely associated networks formed from larger silicate nanoparticles might facilitate substrate diffusion through the network, thus promoting the observed increased activity of the entrapped biomolecules. This doubled the activity of the incorporated biosystems compared with that of biosystems prepared by our own previously reported method. We propose a reaction scheme to explain the formation of the silicate nanoparticle networks. The successful incorporation of biomolecules into the nanoparticle hydrogels, along with the high level of activity exhibited by the biomolecules required for complicated reaction within the gels, demonstrates the nanocomposites' potential for use in medical applications.

  1. Traders’ Networks of Interactions and Structural Properties of Financial Markets: An Agent-Based Approach

    Directory of Open Access Journals (Sweden)

    Linda Ponta

    2018-01-01

    Full Text Available An information-based multiasset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented and studied so as to determine the influences of agents’ networks on the market’s structure. Agents are organized in networks that are responsible for the formation of the sentiments of the agents. In the market, agents trade risky assets in exchange for cash and share their sentiments by means of interactions that are determined by sparsely connected graphs. A central market maker (clearing house mechanism determines the price process for each stock at the intersection of the demand and the supply curves. A set of market’s structure indicators based on the main single-assets and multiassets stylized facts have been defined, in order to study the effects of the agents’ networks. Results point out an intrinsic structural resilience of the stock market. In fact, the network is necessary in order to archive the ability to reproduce the main stylized facts, but also the market has some characteristics that are independent from the network and depend on the finiteness of traders’ wealth.

  2. Synthesis of CdS nanowire networks and their optical and electrical properties

    International Nuclear Information System (INIS)

    Ma, R M; Wei, X L; Dai, L; Huo, H B; Qin, G G

    2007-01-01

    High quality single-crystal CdS nanowire (NW) networks have been synthesized on Si(111) substrates via the chemical vapour deposition method. X-ray diffraction and selected area electron diffraction show that the NWs in the networks grow along the directions and their (0001) crystal planes are parallel to the Si(111) substrates. Room-temperature photoluminescence (PL) spectra of single CdS NWs in the networks are dominated by a near-band-edge emission and free from deep-level defect emissions. The PLs resulting from free-exciton and bound-exciton recombinations are detected at 77 K. The results of the electrical transport measurement on the CdS NW networks show that the current can flow through different NWs via the cross-junctions. The resistivity, electron concentration and electron mobility of single NWs in the networks are estimated by fitting the I-V curves measured on single NWs with the metal-semiconductor-metal model suggested by Zhang et al (2006 Appl. Phys. Lett. 88 073102; 2007 Adv. Funct. Mater. at press)

  3. Coarse graining for synchronization in directed networks

    Science.gov (United States)

    Zeng, An; Lü, Linyuan

    2011-05-01

    Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.

  4. Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    P. Noorunnisa Khanam

    2016-01-01

    Full Text Available The focus of this work is to develop the knowledge of prediction of the physical and chemical properties of processed linear low density polyethylene (LLDPE/graphene nanoplatelets composites. Composites made from LLDPE reinforced with 1, 2, 4, 6, 8, and 10 wt% grade C graphene nanoplatelets (C-GNP were processed in a twin screw extruder with three different screw speeds and feeder speeds (50, 100, and 150 rpm. These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN. The three first properties increased with increase in both screw speed and C-GNP content. The tensile strength reached a maximum value at 4 wt% C-GNP and a speed of 150 rpm as this represented the optimum condition for the stress transfer through the amorphous chains of the matrix to the C-GNP. ANN can be confidently used as a tool to predict the above material properties before investing in development programs and actual manufacturing, thus significantly saving money, time, and effort.

  5. Photocrosslinked PLA-PEO-PLA Hydrogels from Self-Assembled Physical Networks: Mechanical Properties and Influence of Assumed Constitutive Relationships

    Science.gov (United States)

    Sanabria-DeLong, Naomi; Crosby, Alfred J.; Tew, Gregory N.

    2014-01-01

    Poly(lactide) – block – poly(ethylene oxide) – block – poly(lactide) [PLA-PEO-PLA] triblock copolymers are known to form physical hydrogels in water, due to the polymer's amphiphilicity. Their mechanical properties, biocompatibility, and biodegradability have made them attractive for use as soft tissue scaffolds. However, the network junction points are not covalently crosslinked and in a highly aqueous environment these hydrogels adsorb more water, transform from gel to sol, and lose the designed mechanical properties. In this report, a hydrogel was formed by using a novel two step approach. In the first step end-functionalized PLA-PEOPLA triblock was self-assembled into a physical hydrogel through hydrophobic micelle network junctions, and then, in the second step, this self-assembled physical network structure was locked into place by photocrosslinking the terminal acrylate groups. In contrast to physical hydrogels, the photocrosslinked gels remained intact in phosphate buffered solution at body temperature. The swelling, degradation, and mechanical properties were characterized and demonstrated extended degradation time (~ 65 days), exponential decrease in modulus with degradation time, and tunable shear modulus (1.6 – 133 kPa) by varying concentration. We also discuss the various constitutive relationships (Hookean, Neo-Hookean, and Mooney-Rivlin) that can be used to describe the stress-strain behavior of these hydrogels. The chosen model and assumptions used for data fitting influences the obtained modulus values by as much as a factor of 3.5, demonstrating the importance of clearly stating one's data fitting parameters so that accurate comparisons can be made within the literature. PMID:18817440

  6. Rock property estimates using multiple seismic attributes and neural networks; Pegasus Field, West Texas

    Energy Technology Data Exchange (ETDEWEB)

    Schuelke, J.S.; Quirein, J.A.; Sarg, J.F.

    1998-12-31

    This case study shows the benefit of using multiple seismic trace attributes and the pattern recognition capabilities of neural networks to predict reservoir architecture and porosity distribution in the Pegasus Field, West Texas. The study used the power of neural networks to integrate geologic, borehole and seismic data. Illustrated are the improvements between the new neural network approach and the more traditional method of seismic trace inversion for porosity estimation. Comprehensive statistical methods and interpretational/subjective measures are used in the prediction of porosity from seismic attributes. A 3-D volume of seismic derived porosity estimates for the Devonian reservoir provide a very detailed estimate of porosity, both spatially and vertically, for the field. The additional reservoir porosity detail provided, between the well control, allows for optimal placement of horizontal wells and improved field development. 6 refs., 2 figs.

  7. Petri neural network model for the effect of controlled thermomechanical process parameters on the mechanical properties of HSLA steels

    Energy Technology Data Exchange (ETDEWEB)

    Datta, S.

    1999-10-01

    The effect of composition and controlled thermomechanical process parameters on the mechanical properties of HSLA steels is modelled using the Widrow-Hoff's concept of training a neural net with feed-forward topology by applying Rumelhart's back propagation type algorithm for supervised learning, using a Petri like net structure. The data used are from laboratory experiments as well as from the published literature. The results from the neural network are found to be consistent and in good agreement with the experimented results. (author)

  8. Study Modules for Calculus-Based General Physics. [Includes Modules 31-34: Inductance; Wave Properties of Light; Interference; and Introduction to Quantum Physics].

    Science.gov (United States)

    Fuller, Robert G., Ed.; And Others

    This is Part of a series of 41 Calculus Based Physics (CBP) modules totaling about 1,000 Pages. The modules include study guides, practice tests, and mastery tests for a full-year individualized courses in calculus-based physics based on the Personalized System of Instruction (PSI). The units are not intended to be used without outside materials;…

  9. First-principles study of paraelectric and ferroelectric CsH2PO4 including dispersion forces: Stability and related vibrational, dielectric, and elastic properties

    Science.gov (United States)

    Van Troeye, Benoit; van Setten, Michiel Jan; Giantomassi, Matteo; Torrent, Marc; Rignanese, Gian-Marco; Gonze, Xavier

    2017-01-01

    Using density functional theory (DFT) and density functional perturbation theory (DFPT), we investigate the stability and response functions of CsH2PO4 , a ferroelectric material at low temperature. This material cannot be described properly by the usual (semi)local approximations within DFT. The long-range e--e- correlation needs to be properly taken into account, using, for instance, Grimme's DFT-D methods, as investigated in this work. We find that DFT-D3(BJ) performs the best for the members of the dihydrogenated alkali phosphate family (KH2PO4 , RbH2PO4 , CsH2PO4 ), leading to experimental lattice parameters reproduced with an average deviation of 0.5%. With these DFT-D methods, the structural, dielectric, vibrational, and mechanical properties of CsH2PO4 are globally in excellent agreement with the available experiments (<2 % MAPE for Raman-active phonons). Our study suggests the possible existence of a new low-temperature phase of CsH2PO4 , not yet reported experimentally. Finally, we report the implementation of DFT-D contributions to elastic constants within DFPT.

  10. Multiscale network model for simulating liquid water and water vapour transfer properties of porous materials

    NARCIS (Netherlands)

    Carmeliet, J.; Descamps, F.; Houvenaghel, G.

    1999-01-01

    A multiscale network model is presented to model unsaturated moisture transfer in hygroscopic capillary-porous materials showing a broad pore-size distribution. Both capillary effects and water sorption phenomena, water vapour and liquid water transfer are considered. The multiscale approach is

  11. Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

    Directory of Open Access Journals (Sweden)

    Lorenzo L. Pesce

    2013-01-01

    Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  12. Diffusion in random networks: Asymptotic properties, and numerical and engineering approximations

    Science.gov (United States)

    Padrino, Juan C.; Zhang, Duan Z.

    2016-11-01

    The ensemble phase averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of a set of pockets connected by tortuous channels. Inside a channel, we assume that fluid transport is governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pores mass density. The so-called dual porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem, we consider the one-dimensional mass diffusion in a semi-infinite domain, whose solution is sought numerically. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt- 1 / 4 rather than xt- 1 / 2 as in the traditional theory. This early time sub-diffusive similarity can be explained by random walk theory through the network. In addition, by applying concepts of fractional calculus, we show that, for small time, the governing equation reduces to a fractional diffusion equation with known solution. We recast this solution in terms of special functions easier to compute. Comparison of the numerical and exact solutions shows excellent agreement.

  13. Mechanical properties of the collagen network in human articular cartilage as measured by osmotic stress technique

    NARCIS (Netherlands)

    Basser, P.J.; Schneiderman, R.; Bank, R.A.; Wachtel, E.; Maroudas, A.

    1998-01-01

    We have used an isotropic osmotic stress technique to assess the swelling pressures of human articular cartilage over a wide range of hydrations in order to determine from these measurements, for the first time, the tensile stress in the collagen network, P(c), as a function of hydration. Osmotic

  14. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    Science.gov (United States)

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    2013-01-01

    Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

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

    NARCIS (Netherlands)

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

    2004-01-01

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

  16. Interdisciplinary and physics challenges of network theory

    Science.gov (United States)

    Bianconi, Ginestra

    2015-09-01

    Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

  17. Extraversion and neuroticism relate to topological properties of resting-state brain networks.

    Science.gov (United States)

    Gao, Qing; Xu, Qiang; Duan, Xujun; Liao, Wei; Ding, Jurong; Zhang, Zhiqiang; Li, Yuan; Lu, Guangming; Chen, Huafu

    2013-01-01

    With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here, we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI) data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e., betweenness centrality (BC), was positively associated with neuroticism scores in the right precentral gyrus (PreCG), right caudate nucleus, right olfactory cortex, and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus (MTG), indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.

  18. Extraversion and Neuroticism relate to topological properties of resting-state brain networks

    Directory of Open Access Journals (Sweden)

    Qing eGao

    2013-06-01

    Full Text Available With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e. betweenness centrality (BC, was positively associated with neuroticism scores in the right precentral gyrus, right caudate nucleus, right olfactory cortex and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus, indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.

  19. Study on the influence of stochastic properties of correction terms on the reliability of instantaneous network RTK

    Science.gov (United States)

    Próchniewicz, Dominik

    2014-03-01

    The reliability of precision GNSS positioning primarily depends on correct carrier-phase ambiguity resolution. An optimal estimation and correct validation of ambiguities necessitates a proper definition of mathematical positioning model. Of particular importance in the model definition is the taking into account of the atmospheric errors (ionospheric and tropospheric refraction) as well as orbital errors. The use of the network of reference stations in kinematic positioning, known as Network-based Real-Time Kinematic (Network RTK) solution, facilitates the modeling of such errors and their incorporation, in the form of correction terms, into the functional description of positioning model. Lowered accuracy of corrections, especially during atmospheric disturbances, results in the occurrence of unaccounted biases, the so-called residual errors. The taking into account of such errors in Network RTK positioning model is possible by incorporating the accuracy characteristics of the correction terms into the stochastic model of observations. In this paper we investigate the impact of the expansion of the stochastic model to include correction term variances on the reliability of the model solution. In particular the results of instantaneous solution that only utilizes a single epoch of GPS observations, is analyzed. Such a solution mode due to the low number of degrees of freedom is very sensitive to an inappropriate mathematical model definition. Thus the high level of the solution reliability is very difficult to achieve. Numerical tests performed for a test network located in mountain area during ionospheric disturbances allows to verify the described method for the poor measurement conditions. The results of the ambiguity resolution as well as the rover positioning accuracy shows that the proposed method of stochastic modeling can increase the reliability of instantaneous Network RTK performance.

  20. Study of self-organization in network glasses and physical properties in some non-crystalline systems

    International Nuclear Information System (INIS)

    Mohamed, M.A.M.

    2007-01-01

    to understand the effects of structural features of the Ag-As-Te glassy system, various properties are separately studied as functions of the average coordination number (r). the relation between the chemical ordered covalent network model and the constraint theory, of the structural features, is examined. the self-organization model is widely used as a realistic description for the structure of both covalent glasses and amorphous solids. the overall mean energy, (E) , of a covalent network for the Ag-As-Te ternary glasses is determined. the average coordination number (r) for the Ag-As-Te system based on recently suggested models for network glasses has been examined. it was found that, two topological effects namely; the rigid to floppy transition and the structural transition, occurred resulting in some changes in the chemical ordering. the values of the glass transition temperature, T g were found to depend on the compositions. the thermal stability and the glass-forming tendency were calculated and they were found to have the same trend

  1. Horton Ratios Link Self-Similarity with Maximum Entropy of Eco-Geomorphological Properties in Stream Networks

    Directory of Open Access Journals (Sweden)

    Bruce T. Milne

    2017-05-01

    Full Text Available Stream networks are branched structures wherein water and energy move between land and atmosphere, modulated by evapotranspiration and its interaction with the gravitational dissipation of potential energy as runoff. These actions vary among climates characterized by Budyko theory, yet have not been integrated with Horton scaling, the ubiquitous pattern of eco-hydrological variation among Strahler streams that populate river basins. From Budyko theory, we reveal optimum entropy coincident with high biodiversity. Basins on either side of optimum respond in opposite ways to precipitation, which we evaluated for the classic Hubbard Brook experiment in New Hampshire and for the Whitewater River basin in Kansas. We demonstrate that Horton ratios are equivalent to Lagrange multipliers used in the extremum function leading to Shannon information entropy being maximal, subject to constraints. Properties of stream networks vary with constraints and inter-annual variation in water balance that challenge vegetation to match expected resource supply throughout the network. The entropy-Horton framework informs questions of biodiversity, resilience to perturbations in water supply, changes in potential evapotranspiration, and land use changes that move ecosystems away from optimal entropy with concomitant loss of productivity and biodiversity.

  2. Artificial Neural Networks for the Prediction of Wear Properties of Al6061-TiO2 Composites

    Science.gov (United States)

    Veeresh Kumar, G. B.; Pramod, R.; Shivakumar Gouda, P. S.; Rao, C. S. P.

    2017-08-01

    The exceptional performance of composite materials in comparison with the monolithic materials have been extensively studied by researchers. Among the metal matrix composites Aluminium matrix based composites have displayed superior mechanical properties. The aluminium 6061 alloy has been used in aeronautical and automotive components, but their resistance against the wear is poor. To enhance the wear properties, Titanium dioxide (TiO2) particulates have been used as reinforcements. In the present investigation Back propagation (BP) technique has been adopted for Artificial Neural Network [ANN] modelling. The wear experimentations were carried out on a pin-on-disc wear monitoring apparatus. For conduction of wear tests ASTM G99 was adopted. Experimental design was carried out using Taguchi L27 orthogonal array. The sliding distance, weight percentage of the reinforcement material and applied load have a substantial influence on the height damage due to wear of the Al6061 and Al6061-TiO2 filled composites. The Al6061 with 3 wt% TiO2 composite displayed an excellent wear resistance in comparison with other composites investigated. A non-linear relationship between density, applied load, weight percentage of reinforcement, sliding distance and height decrease due to wear has been established using an artificial neural network. A good agreement has been observed between experimental and ANN model predicted results.

  3. Modeling and Vulnerability Analysis of Cyber-Physical Power Systems Considering Network Topology and Power Flow Properties

    Directory of Open Access Journals (Sweden)

    Jia Guo

    2017-01-01

    Full Text Available Conventional power systems are developing into cyber-physical power systems (CPPS with wide applications of communication, computer and control technologies. However, multiple practical cases show that the failure of cyber layers is a major factor leading to blackouts. Therefore, it is necessary to discuss the cascading failure process considering cyber layer failures and analyze the vulnerability of CPPS. In this paper, a CPPS model, which consists of cyber layer, physical layer and cyber-physical interface, is presented using complex network theory. Considering power flow properties, the impacts of cyber node failures on the cascading failure propagation process are studied. Moreover, two vulnerability indices are established from the perspective of both network structure and power flow properties. A vulnerability analysis method is proposed, and the CPPS performance before and after cascading failures is analyzed by the proposed method to calculate vulnerability indices. In the case study, three typical scenarios are analyzed to illustrate the method, and vulnerabilities under different interface strategies and attack strategies are compared. Two thresholds are proposed to value the CPPS vulnerability roughly. The results show that CPPS is more vulnerable under malicious attacks and cyber nodes with high indices are vulnerable points which should be reinforced.

  4. Structure and properties of semi-interpenetrating network hydrogel based on starch.

    Science.gov (United States)

    Zhu, Baodong; Ma, Dongzhuo; Wang, Jian; Zhang, Shuang

    2015-11-20

    Starch-g-P(acrylic acid-co-acrylamide)/PVA semi-interpenetrating network (semi-IPN) hydrogels were prepared by aqueous solution polymerization method. Starch grafting copolymerization reaction, semi-IPN structure and crystal morphology were characterized by Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The PVA in the form of partial crystallization distributing in the gel matrix uniformly were observed by Field emission scanning electron microscope (FESEM). The space network structure, finer microstructure and pore size in the interior of hydrogel were presented by biomicroscope. The results demonstrated that absorption ratio of water and salt generated different degree changes with the effect of PVA. In addition, the mechanical strength of hydrogel was improved. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Designing heavy metal oxide glasses with threshold properties from network rigidity.

    Science.gov (United States)

    Chakraborty, Shibalik; Boolchand, P; Malki, M; Micoulaut, M

    2014-01-07

    Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.

  6. Property relationships of the physical infrastructure and the traffic flow networks

    Science.gov (United States)

    Zhou, Ta; Zou, Sheng-Rong; He, Da-Ren

    2010-03-01

    We studied both empirically and analytically the correlation between the degrees or the clustering coefficients, respectively, of the networks in the physical infrastructure and the traffic flow layers in three Chinese transportation systems. The systems are bus transportation systems in Beijing and Hangzhou, and the railway system in the mainland. It is found that the correlation between the degrees obey a linear function; while the correlation between the clustering coefficients obey a power law. A possible dynamic explanation on the rules is presented.

  7. Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

    Science.gov (United States)

    Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

    2010-10-01

    Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

  8. Langevin-elasticity-theory-based description of the tensile properties of double network rubbers

    Czech Academy of Sciences Publication Activity Database

    Meissner, Bohumil; Matějka, Libor

    2003-01-01

    Roč. 44, č. 16 (2003), s. 4611-4617 ISSN 0032-3861 R&D Projects: GA ČR GA104/00/1311; GA AV ČR IAA4050008 Institutional research plan: CEZ:AV0Z4050913 Keywords : theory of rubber elasticity * double network rubbers * experimental testing Subject RIV: CD - Macromolecular Chemistry Impact factor: 2.340, year: 2003

  9. Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

    Directory of Open Access Journals (Sweden)

    E. M. A. Perrier

    2010-10-01

    Full Text Available Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009. Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

  10. Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

    Science.gov (United States)

    Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

    2018-02-01

    Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

  11. Critical properties of the SIS model dynamics on the Apollonian network

    International Nuclear Information System (INIS)

    Da Silva, L F; Costa Filho, R N; Cunha, A R; Macedo-Filho, A; Serva, M; Fulco, U L; Albuquerque, E L

    2013-01-01

    We present an analysis of the classical SIS (susceptible–infected–susceptible) model on the Apollonian network which is scale free and displays the small word effect. Numerical simulations show a continuous absorbing-state phase transition at a finite critical value λ c of the control parameter λ. Since the coordination number k of the vertices of the Apollonian network is cumulatively distributed according to a power-law P(k) ∝ 1/k η−1 , with exponent η ≃ 2.585, finite size effects are large and the infinite network limit cannot be reached in practice. Consequently, our study requires the application of finite size scaling theory, allowing us to characterize the transition by a set of critical exponents β/ν ⊥ , γ/ν ⊥ , ν ⊥ , β. We found that the phase transition belongs to the mean-field directed percolation universality class in regular lattices but, very peculiarly, is associated with a short-range distribution whose power-law distribution of k is defined by an exponent η larger than 3. (paper)

  12. The influence of molecular mobility on the properties of networks of gold nanoparticles and organic ligands

    Directory of Open Access Journals (Sweden)

    Edwin J. Devid

    2014-09-01

    Full Text Available We prepare and investigate two-dimensional (2D single-layer arrays and multilayered networks of gold nanoparticles derivatized with conjugated hetero-aromatic molecules, i.e., S-(4-{[2,6-bipyrazol-1-ylpyrid-4-yl]ethynyl}phenylthiolate (herein S-BPP, as capping ligands. These structures are fabricated by a combination of self-assembly and microcontact printing techniques, and are characterized by electron microscopy, UV–visible spectroscopy and Raman spectroscopy. Selective binding of the S-BPP molecules to the gold nanoparticles through Au–S bonds is found, with no evidence for the formation of N–Au bonds between the pyridine or pyrazole groups of BPP and the gold surface. Subtle, but significant shifts with temperature of specific Raman S-BPP modes are also observed. We attribute these to dynamic changes in the orientation and/or increased mobility of the molecules on the gold nanoparticle facets. As for their conductance, the temperature-dependence for S-BPP networks differs significantly from standard alkanethiol-capped networks, especially above 220 K. Relating the latter two observations, we propose that dynamic changes in the molecular layers effectively lower the molecular tunnel barrier for BPP-based arrays at higher temperatures.

  13. The influence of molecular mobility on the properties of networks of gold nanoparticles and organic ligands.

    Science.gov (United States)

    Devid, Edwin J; Martinho, Paulo N; Kamalakar, M Venkata; Prendergast, Úna; Kübel, Christian; Lemma, Tibebe; Dayen, Jean-François; Keyes, Tia E; Doudin, Bernard; Ruben, Mario; van der Molen, Sense Jan

    2014-01-01

    We prepare and investigate two-dimensional (2D) single-layer arrays and multilayered networks of gold nanoparticles derivatized with conjugated hetero-aromatic molecules, i.e., S-(4-{[2,6-bipyrazol-1-yl)pyrid-4-yl]ethynyl}phenyl)thiolate (herein S-BPP), as capping ligands. These structures are fabricated by a combination of self-assembly and microcontact printing techniques, and are characterized by electron microscopy, UV-visible spectroscopy and Raman spectroscopy. Selective binding of the S-BPP molecules to the gold nanoparticles through Au-S bonds is found, with no evidence for the formation of N-Au bonds between the pyridine or pyrazole groups of BPP and the gold surface. Subtle, but significant shifts with temperature of specific Raman S-BPP modes are also observed. We attribute these to dynamic changes in the orientation and/or increased mobility of the molecules on the gold nanoparticle facets. As for their conductance, the temperature-dependence for S-BPP networks differs significantly from standard alkanethiol-capped networks, especially above 220 K. Relating the latter two observations, we propose that dynamic changes in the molecular layers effectively lower the molecular tunnel barrier for BPP-based arrays at higher temperatures.

  14. Motor Cortical Networks for Skilled Movements Have Dynamic Properties That Are Related to Accurate Reaching

    Directory of Open Access Journals (Sweden)

    David F. Putrino

    2011-01-01

    Full Text Available Neurons in the Primary Motor Cortex (MI are known to form functional ensembles with one another in order to produce voluntary movement. Neural network changes during skill learning are thought to be involved in improved fluency and accuracy of motor tasks. Unforced errors during skilled tasks provide an avenue to study network connections related to motor learning. In order to investigate network activity in MI, microwires were implanted in the MI of cats trained to perform a reaching task. Spike trains from eight groups of simultaneously recorded cells (95 neurons in total were acquired. A point process generalized linear model (GLM was developed to assess simultaneously recorded cells for functional connectivity during reaching attempts where unforced errors or no errors were made. Whilst the same groups of neurons were often functionally connected regardless of trial success, functional connectivity between neurons was significantly different at fine time scales when the outcome of task performance changed. Furthermore, connections were shown to be significantly more robust across multiple latencies during successful trials of task performance. The results of this study indicate that reach-related neurons in MI form dynamic spiking dependencies whose temporal features are highly sensitive to unforced movement errors.

  15. [Network structures in biological systems].

    Science.gov (United States)

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  16. Prediction of some physical and drying properties of terebinth fruit (Pistacia atlantica L.) using Artificial Neural Networks.

    Science.gov (United States)

    Kaveh, Mohammad; Chayjan, Reza Amiri

    2014-01-01

    Drying of terebinth fruit was conducted to provide microbiological stability, reduce product deterioration due to chemical reactions, facilitate storage and lower transportation costs. Because terebinth fruit is susceptible to heat, the selection of a suitable drying technology is a challenging task. Artificial neural networks (ANNs) are used as a nonlinear mapping structures for modelling and prediction of some physical and drying properties of terebinth fruit. Drying characteristics of terebinth fruit with an initial moisture content of 1.16 (d.b.) was studied in an infrared fluidized bed dryer. Different levels of air temperatures (40, 55 and 70°C), air velocities (0.93, 1.76 and 2.6 m/s) and infrared (IR) radiation powers (500, 1000 and 1500 W) were applied. In the present study, the application of Artificial Neural Network (ANN) for predicting the drying moisture diffusivity, energy consumption, shrinkage, drying rate and moisture ratio (output parameter for ANN modelling) was investigated. Air temperature, air velocity, IR radiation and drying time were considered as input parameters. The results revealed that to predict drying rate and moisture ratio a network with the TANSIG-LOGSIG-TANSIG transfer function and Levenberg-Marquardt (LM) training algorithm made the most accurate predictions for the terebinth fruit drying. The best results for ANN at predications were R2 = 0.9678 for drying rate, R2 = 0.9945 for moisture ratio, R2 = 0.9857 for moisture diffusivity and R2 = 0.9893 for energy consumption. Results indicated that artificial neural network can be used as an alternative approach for modelling and predicting of terebinth fruit drying parameters with high correlation. Also ANN can be used in optimization of the process.

  17. Direct and inverse neural networks modelling applied to study the influence of the gas diffusion layer properties on PBI-based PEM fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Lobato, Justo; Canizares, Pablo; Rodrigo, Manuel A.; Linares, Jose J. [Chemical Engineering Department, University of Castilla-La Mancha, Campus Universitario s/n, 13004 Ciudad Real (Spain); Piuleac, Ciprian-George; Curteanu, Silvia [Faculty of Chemical Engineering and Environmental Protection, Department of Chemical Engineering, ' ' Gh. Asachi' ' Technical University Iasi Bd. D. Mangeron, No. 71A, 700050 IASI (Romania)

    2010-08-15

    This article shows the application of a very useful mathematical tool, artificial neural networks, to predict the fuel cells results (the value of the tortuosity and the cell voltage, at a given current density, and therefore, the power) on the basis of several properties that define a Gas Diffusion Layer: Teflon content, air permeability, porosity, mean pore size, hydrophobia level. Four neural networks types (multilayer perceptron, generalized feedforward network, modular neural network, and Jordan-Elman neural network) have been applied, with a good fitting between the predicted and the experimental values in the polarization curves. A simple feedforward neural network with one hidden layer proved to be an accurate model with good generalization capability (error about 1% in the validation phase). A procedure based on inverse neural network modelling was able to determine, with small errors, the initial conditions leading to imposed values for characteristics of the fuel cell. In addition, the use of this tool has been proved to be very attractive in order to predict the cell performance, and more interestingly, the influence of the properties of the gas diffusion layer on the cell performance, allowing possible enhancements of this material by changing some of its properties. (author)

  18. Aerosol physical and optical properties in the Eastern Mediterranean Basin, Crete, from Aerosol Robotic Network data

    Directory of Open Access Journals (Sweden)

    A. Fotiadi

    2006-01-01

    Full Text Available In this study, we investigate the aerosol optical properties, namely aerosol extinction optical thickness (AOT, Angström parameter and size distribution over the Eastern Mediterranean Basin, using spectral measurements from the recently established FORTH (Foundation for Research and Technology-Hellas AERONET station in Crete, for the two-year period 2003–2004. The location of the FORTH-AERONET station offers a unique opportunity to monitor aerosols from different sources. Maximum values of AOT are found primarily in spring, which together with small values of the Angström parameter indicate dust transported from African deserts, whereas the minimum values of AOT occur in winter. In autumn, large AOT values observed at near-infrared wavelengths arise also from dust transport. In summer, large AOT values at ultraviolet (340 nm and visible wavelengths (500 nm, together with large values of the Angström parameter, are associated with transport of fine aerosols of urban/industrial and biomass burning origin. The Angström parameter values vary on a daily basis within the range 0.05–2.20, and on a monthly basis within the range 0.68–1.9. This behaviour, together with broad frequency distributions and back-trajectory analyses, indicates a great variety of aerosol types over the study region including dust, urban-industrial and biomass-burning pollution, and maritime, as well as mixed aerosol types. Large temporal variability is observed in AOT, Angström parameter, aerosol content and size. The fine and coarse aerosol modes persist throughout the year, with the coarse mode dominant except in summer. The highest values of AOT are related primarily to southeasterly winds, associated with coarse aerosols, and to a less extent to northwesterly winds associated with fine aerosols. The results of this study show that the FORTH AERONET station in Crete is well suited for studying the transport and mixing of different types of aerosols from a variety

  19. Evaluating the impacts of membrane type, coating, fouling, chemical properties and water chemistry on reverse osmosis rejection of seven nitrosoalklyamines, including NDMA.

    Science.gov (United States)

    Steinle-Darling, Eva; Zedda, Marco; Plumlee, Megan H; Ridgway, Harry F; Reinhard, Martin

    2007-09-01

    Reverse osmosis (RO) treatment has been found to be effective for a wide range of organics but generally small, polar, uncharged molecules such as N-nitrosodimethylamine (NDMA) can be poorly rejected. The rejection of seven N-nitrosoalkylamines with molecular masses in the range of 78-158Da, including NDMA, N-nitrosodiethylamine (NDEA), N-nitrosomethylethylamine (NMEA), N-nitrosodipropylamine (NDPA), N-nitrosodibutylamine (NDBA), N-nitrosopyrrolidine (NPyr), N-nitrosopiperidine (NPip) by three commercial brackish-water reverse osmosis membranes was studied in flat-sheet cells under cross-flow conditions. The membranes used were ESPA3 (Hydranautics), LFC3 (Hydranautics) and BW-30 (Dow/Filmtec), commonly used in water reuse applications. The effects of varying ionic strength and pH, dip-coating membranes with PEBAX 1657, a hydrophilic polymer, and artificial fouling with alginate on nitrosamine rejection were quantified. Rejection in deionized (DI) water increased with molecular mass from 56 to 70% for NDMA, to 80-91% for NMEA, 89-97% for NPyr, 92-98% for NDEA, and to beyond the detection limits for NPip, NDPA and NDBA. For the nitrosamines with quantifiable transmission, linear correlations (r(2)>0.97) were found between the number of methyl groups and the log(transmission), with factor 0.35 to 0.55 decreases in transmission per added methyl group. A PEBAX coating lowered the ESPA3 rejection of NDMA by 11% but increased the LFC3 and BW30 rejection by 6% and 15%, respectively. Artificially fouling ESPA3 membrane coupons with 170g/m(2) alginate decreased the rejection of NDMA by 18%. A feed concentration of 100mM NaCl decreased rejection of NDMA by 15% and acidifying the DI water feed to pH=3 decreased the rejection by 5%, whereas increasing the pH to 10 did not have a significant (p<0.05) effect.

  20. Beyond nutrient-based food indices: a data mining approach to search for a quantitative holistic index reflecting the degree of food processing and including physicochemical properties.

    Science.gov (United States)

    Fardet, Anthony; Lakhssassi, Sanaé; Briffaz, Aurélien

    2018-01-24

    Processing has major impacts on both the structure and composition of food and hence on nutritional value. In particular, high consumption of ultra-processed foods (UPFs) is associated with increased risks of obesity and diabetes. Unfortunately, existing food indices only focus on food nutritional content while failing to consider either food structure or the degree of processing. The objectives of this study were thus to link non-nutrient food characteristics (texture, water activity (a w ), glycemic and satiety potentials (FF), and shelf life) to the degree of processing; search for associations between these characteristics with nutritional composition; search for a holistic quantitative technological index; and determine quantitative rules for a food to be defined as UPF using data mining. Among the 280 most widely consumed foods by the elderly in France, 139 solid/semi-solid foods were selected for textural and a w measurements, and classified according to three degrees of processing. Our results showed that minimally-processed foods were less hyperglycemic, more satiating, had better nutrient profile, higher a w , shorter shelf life, lower maximum stress, and higher energy at break than UPFs. Based on 72 food variables, multivariate analyses differentiated foods according to their degree of processing. Then technological indices including food nutritional composition, a w , FF and textural parameters were tested against technological groups. Finally, a LIM score (nutrients to limit) ≥8 per 100 kcal and a number of ingredients/additives >4 are relevant, but not sufficient, rules to define UPFs. We therefore suggest that food health potential should be first defined by its degree of processing.

  1. Multiscale pore networks and their effect on deformation and transport property alteration associated with hydraulic fracturing

    Science.gov (United States)

    Daigle, Hugh; Hayman, Nicholas; Jiang, Han; Tian, Xiao; Jiang, Chunbi

    2017-04-01

    Multiple lines of evidence indicate that, during a hydraulic fracture stimulation, the permeability of the unfractured matrix far from the main, induced tensile fracture increases by one to two orders of magnitude. This permeability enhancement is associated with pervasive shear failure in a large region surrounding the main induced fracture. We have performed low-pressure gas sorption, mercury intrusion, and nuclear magnetic resonance measurements along with high-resolution scanning electron microscope imaging on several preserved and unpreserved shale samples from North American basins before and after inducing failure in confined compressive strength tests. We have observed that the pore structure in intact samples exhibits multiscale behavior, with sub-micron-scale pores in organic matter connected in isolated, micron-scale clusters which themselves are connected to each other through a network of microcracks. The organic-hosted pore networks are poorly connected due to a significant number of dead-end pores within the organic matter. Following shear failure, we often observe an increase in pore volume in the sub-micron range, which appears to be related to the formation of microcracks that propagate along grain boundaries and other planes of mechanical strength contrast. This is consistent with other experimental and field evidence. In some cases these microcracks cross or terminate in organic matter, intersecting the organic-hosted pores. The induced microcrack networks typically have low connectivity and do not appreciably increase the connectivity of the overall pore network. However, in other cases the shear deformation results in an overall pore volume decrease; samples which exhibit this behavior tend to have more clay minerals. Our interpretation of these phenomena is as follows. As organic matter is converted to hydrocarbons, organic-hosted pores develop, and the hydrocarbons contained in these pores are overpressured. The disconnected nature of these

  2. Theoretical properties of the global optimizer of two layer neural network

    OpenAIRE

    Boob, Digvijay; Lan, Guanghui

    2017-01-01

    In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number of parameters is greater than the number of sampled points. We show that for a wide class of differentiable activation functions (this class involves "almost" all functions which are not piecewise linear), we have that first-order optimal solutions satisfy global optimality provided the hidden layer is non-singular. ...

  3. Complex quantum network geometries: Evolution and phase transitions

    Science.gov (United States)

    Bianconi, Ginestra; Rahmede, Christoph; Wu, Zhihao

    2015-08-01

    Networks are topological and geometric structures used to describe systems as different as the Internet, the brain, or the quantum structure of space-time. Here we define complex quantum network geometries, describing the underlying structure of growing simplicial 2-complexes, i.e., simplicial complexes formed by triangles. These networks are geometric networks with energies of the links that grow according to a nonequilibrium dynamics. The evolution in time of the geometric networks is a classical evolution describing a given path of a path integral defining the evolution of quantum network states. The quantum network states are characterized by quantum occupation numbers that can be mapped, respectively, to the nodes, links, and triangles incident to each link of the network. We call the geometric networks describing the evolution of quantum network states the quantum geometric networks. The quantum geometric networks have many properties common to complex networks, including small-world property, high clustering coefficient, high modularity, and scale-free degree distribution. Moreover, they can be distinguished between the Fermi-Dirac network and the Bose-Einstein network obeying, respectively, the Fermi-Dirac and Bose-Einstein statistics. We show that these networks can undergo structural phase transitions where the geometrical properties of the networks change drastically. Finally, we comment on the relation between quantum complex network geometries, spin networks, and triangulations.

  4. Elastomeric networks based on trimethylene carbonate polymers for biomedical applications : physical properties and degradation behaviour

    NARCIS (Netherlands)

    Bat, E.

    2010-01-01

    The number of applications for biomedical technologies is ever-increasing, and there is a need to develop new materials with properties that can conform to the requirements of a specific application. Synthetic polymers are of great importance in the biomedical field as they can be designed to

  5. Structure-property correlation study of novel poly(urethane-ester-siloxane) networks

    Czech Academy of Sciences Publication Activity Database

    Pergal, M. V.; Džunuzović, J. V.; Poreba, Rafal; Steinhart, Miloš; Pergal, M. M.; Vodnik, V. V.; Špírková, Milena

    2013-01-01

    Roč. 52, č. 18 (2013), s. 6164-6176 ISSN 0888-5885 R&D Projects: GA ČR GAP108/10/0195 Institutional support: RVO:61389013 Keywords : urethane-siloxane copolymers * hyperbranched poly ester * mechanical - properties Subject RIV: CD - Macromolecular Chemistry Impact factor: 2.235, year: 2013

  6. Enhanced mechanical properties of 1,3-trimethylene carbonate polymers and networks

    NARCIS (Netherlands)

    Pêgo, A.P.; Grijpma, Dirk W.; Feijen, Jan

    2003-01-01

    Poly(1,3-trimethylene carbonate), poly(TMC), has often been regarded as a rubbery polymer that cannot be applied in the biomedical field due to its poor dimensional stability, tackiness and inadequate mechanical properties. In this study we show that high molecular weight, amorphous poly(TMC) is

  7. Statistical analysis of modal properties of a cable-stayed bridge through long-term structural health monitoring with wireless smart sensor networks

    Science.gov (United States)

    Asadollahi, Parisa; Li, Jian

    2016-04-01

    Understanding the dynamic behavior of complex structures such as long-span bridges requires dense deployment of sensors. Traditional wired sensor systems are generally expensive and time-consuming to install due to cabling. With wireless communication and on-board computation capabilities, wireless smart sensor networks have the advantages of being low cost, easy to deploy and maintain and therefore facilitate dense instrumentation for structural health monitoring. A long-term monitoring project was recently carried out for a cable-stayed bridge in South Korea with a dense array of 113 smart sensors, which feature the world's largest wireless smart sensor network for civil structural monitoring. This paper presents a comprehensive statistical analysis of the modal properties including natural frequencies, damping ratios and mode shapes of the monitored cable-stayed bridge. Data analyzed in this paper is composed of structural vibration signals monitored during a 12-month period under ambient excitations. The correlation between environmental temperature and the modal frequencies is also investigated. The results showed the long-term statistical structural behavior of the bridge, which serves as the basis for Bayesian statistical updating for the numerical model.

  8. Magnetic properties of a metal-organic porous network [Ni2(BODC)2(TED)

    Science.gov (United States)

    Yuen, Tan; Danilovic, D.; Li, Kunhao; Li, Jing

    2008-04-01

    A new material [Ni2(BODC)2(TED)], (BODC =4,4'-bicyclo[2.2.2]octane dicarboxylate and TED =triethylene-4,4'-diamine), which is a guest-free, porous metal-organic coordination network, has been successfully synthesized. The crystal structure of this compound is tetragonal with the space group P4/mmm. It is a three-dimensional network that can be deconstructed into rectangular gridlike layers along ab planes. These planes are formed by BODC and Zn2O4 paddle-wheel-like clusters, and the TED ligands from the axial directions of the paddle-wheels connect the layers into a three-dimesional structure. There are no guest molecules found in the pores. The shortest Ni-Ni distance within the paddle wheel is found to be 2.613Å. Magnetic susceptibility χ(T )=M(T)/H and isothermal magnetization M(H ) measurements have been measured on powder samples of this compound. The results of χ(T ) show that there is a rapid increase in the susceptibility below 20K due to a spontaneous ordering of the Ni2+ moments. The effective moment μeff of Ni2+ is about 2.20μB at room temperature. The M(H ) result at 1.8K shows a clear hysteresis with a coercivity of Hcoe≈1700G. The behavior of this compound is discussed in terms of Ni-Ni coupling within the Ni dimers and dimer chains.

  9. ECO2M: A TOUGH2 Fluid Property Module for Mixtures of Water, NaCl, and CO2, Including Super- and Sub-Critical Conditions, and Phase Change Between Liquid and Gaseous CO2

    Energy Technology Data Exchange (ETDEWEB)

    Pruess, K.

    2011-04-01

    ECO2M is a fluid property module for the TOUGH2 simulator (Version 2.0) that was designed for applications to geologic storage of CO{sub 2} in saline aquifers. It includes a comprehensive description of the thermodynamics and thermophysical properties of H{sub 2}O - NaCl - CO{sub 2} mixtures, that reproduces fluid properties largely within experimental error for temperature, pressure and salinity conditions in the range of 10 C {le} T {le} 110 C, P {le} 600 bar, and salinity from zero up to full halite saturation. The fluid property correlations used in ECO2M are identical to the earlier ECO2N fluid property package, but whereas ECO2N could represent only a single CO{sub 2}-rich phase, ECO2M can describe all possible phase conditions for brine-CO{sub 2} mixtures, including transitions between super- and sub-critical conditions, and phase change between liquid and gaseous CO{sub 2}. This allows for seamless modeling of CO{sub 2} storage and leakage. Flow processes can be modeled isothermally or non-isothermally, and phase conditions represented may include a single (aqueous or CO{sub 2}-rich) phase, as well as two-and three-phase mixtures of aqueous, liquid CO{sub 2} and gaseous CO{sub 2} phases. Fluid phases may appear or disappear in the course of a simulation, and solid salt may precipitate or dissolve. TOUGH2/ECO2M is upwardly compatible with ECO2N and accepts ECO2N-style inputs. This report gives technical specifications of ECO2M and includes instructions for preparing input data. Code applications are illustrated by means of several sample problems, including problems that had been previously solved with TOUGH2/ECO2N.

  10. Altered Intrinsic Pyramidal Neuron Properties and Pathway-Specific Synaptic Dysfunction Underlie Aberrant Hippocampal Network Function in a Mouse Model of Tauopathy.

    Science.gov (United States)

    Booth, Clair A; Witton, Jonathan; Nowacki, Jakub; Tsaneva-Atanasova, Krasimira; Jones, Matthew W; Randall, Andrew D; Brown, Jonathan T

    2016-01-13

    The formation and deposition of tau protein aggregates is proposed to contribute to cognitive impairments in dementia by disrupting neuronal function in brain regions, including the hippocampus. We used a battery of in vivo and in vitro electrophysiological recordings in the rTg4510 transgenic mouse model, which overexpresses a mutant form of human tau protein, to investigate the effects of tau pathology on hippocampal neuronal function in area CA1 of 7- to 8-month-old mice, an age point at which rTg4510 animals exhibit advanced tau pathology and progressive neurodegeneration. In vitro recordings revealed shifted theta-frequency resonance properties of CA1 pyramidal neurons, deficits in synaptic transmission at Schaffer collateral synapses, and blunted plasticity and imbalanced inhibition at temporoammonic synapses. These changes were associated with aberrant CA1 network oscillations, pyramidal neuron bursting, and spatial information coding in vivo. Our findings relate tauopathy-associated changes in cellular neurophysiology to altered behavior-dependent network function. Dementia is characterized by the loss of learning and memory ability. The deposition of tau protein aggregates in the brain is a pathological hallmark of dementia; and the hippocampus, a brain structure known to be critical in processing learning and memory, is one of the first and most heavily affected regions. Our results show that, in area CA1 of hippocampus, a region involved in spatial learning and memory, tau pathology is associated with specific disturbances in synaptic, cellular, and network-level function, culminating in the aberrant encoding of spatial information and spatial memory impairment. These studies identify several novel ways in which hippocampal information processing may be disrupted in dementia, which may provide targets for future therapeutic intervention. Copyright © 2016 Booth, Witton et al.

  11. Synthesis and characterization of thiol-ene functionalized siloxanes and evaluation of their polymerization kinetics, network properties, and dental applications

    Science.gov (United States)

    Cole, Megan A.

    We explored formation-structure-property relationships in thiol-ene functionalized oligosiloxanes to create crosslinked networks. Specifically, nine oligomers were synthesized, three with thiol-functional silane repeats and three with allyl-functional silane repeats. Structural variations in each oligomer were systematically induced through the incorporation of non-reactive repeats bearing either diphenyl or di-n-octyl moieties, and the oligomer molecular weight was limited by the presence of monofunctional silane condensation species. The molecular weights and chain compositions of all oligomers were ascertained and subsequently used in the evaluation of network properties formed upon photopolymerization of thiol- and ene-functional reactants. Polymerization kinetics of the thiol-ene functionalized siloxanes were also investigated using photoinitiation owing to the spatial and temporal control afforded by this technique. In particular, the effects of the viscosity of the ene-functionalized oligomer and the degree of thiol functionalization on the observed polymerization rate were determined. Results showed that the speed of polymerization varied with changes to the rate-limiting step, which was heavily influenced by neighboring non-reactive functionalities. Moreover, the thiol-ene reaction was found to exhibity unimolecular termination exclusively in siloxane-based systems. Proposed use of the thiol-ene functionalized siloxane system as a dental impression material necessitated the development of a redox initiation scheme. Evaluation of the benzoylperoxide/dimethyl-p-toluidine redox pair in traditional systems showed bulk thiol-ene polymerizations comparable to photoinitiation with the added advantage of uninhibited depth control, as also demonstrated in small molecule thiol-ene coupling reactions initiated by this same redox system. Application of the redox pair to the siloxane system allowed for the viscoelastic properties as well as the feature replication

  12. Towards a "fingerprint" of paper network: separating forgeries from genuine by the properties of fibre structure

    Science.gov (United States)

    Takalo, Jouni; Timonen, Jussi; Sampo, Jouni; Rantala, Maaria; Siltanen, Samuli; Lassas, Matti

    2014-10-01

    A novel method is introduced for distinguishing counterfeit banknotes from genuine samples. The method is based on analyzing differences in the networks of paper fibers. The main tool is a curvelet-based algorithm for measuring the distribution of overall fiber orientation and quantifying its anisotropy. The use of a couple or more appropriate parameters makes it possible to distinguish forgeries from genuine samples as concentrated point clouds in a two- or three-dimensional parameter space. Furthermore, the techniques of making watermarks is investigated by comparing genuine and counterfeit €50 banknotes. In addition, the so-called wire markings are shown to differ significantly from each other in all of investigated banknotes.

  13. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Eric A Yen

    2014-05-01

    Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

  14. Targeting polyelectrolyte networks in purulent body fluids to modulate bactericidal properties of some antibiotics

    Directory of Open Access Journals (Sweden)

    Bucki R

    2018-01-01

    Full Text Available Robert Bucki,1,* Bonita Durnaś,2,* Marzena Wątek,2,3 Ewelina Piktel,1 Katrina Cruz,4 Przemysław Wolak,2 Paul B Savage,5 Paul A Janmey4 1Department of Microbiological and Nanobiomedical Engineering, Medical University of Białystok, Białystok, 2Department of Microbiology and Immunology, The Faculty of Health Sciences of the Jan Kochanowski University in Kielce, 3Holy Cross Oncology Center of Kielce, Kielce, Kielce, Poland; 4Department of Physiology, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, PA, 5Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA *These authors contributed equally to this work Abstract: The response of the human immune system to most bacterial infections results in accumulation of neutrophils at infection sites that release a significant quantity of DNA and F-actin. Both are negatively charged polyelectrolytes that can interact with positively charged host defense molecules such as cathelicidin-delivered LL-37 peptide or other cationic antibiotic agents. Evaluation of the ability of bacterial outgrowth (using luminescence measurements or counting colony-forming units to form a biofilm (quantified by crystal violet staining and analysis of the structure of DNA/F-actin network by optical microscopy in human pus samples treated with different antibiotics in combination with plasma gelsolin, DNAse 1, and/or poly-aspartic acid revealed that bactericidal activity of most tested antibacterial agents increases in the presence of DNA/F-actin depolymerizing factors. Keywords: antibiotic activity, polyelectrolyte network, depolymerizing factors, cathelicidin, ceragenins, DNase 1, cystic fibrosis

  15. Use of a three dimensional network model to predict equilibrium desaturation properties of coal filter cakes

    Energy Technology Data Exchange (ETDEWEB)

    Qamar, I.; Bayles, G.A.; Tierney, J.W.; Chiang, S.-H.; Klinzing, G.E.

    1987-01-01

    A three dimensional bond-flow correlated network model has been successfully used to calculate equilibrium desaturation curves for coal filter cakes. A simple cubic lattice with the pore sizes correlated in the direction of macroscopic flow is used as the network. A new method of pore volume assignment is presented in which the pore volume occupied by the large pores (which give rise to capillary pressures less than a calculated critical value) is assigned to the nodes and the rest is distributed to the bonds according to an experimentally determined micrographic pore size distribution. Equilibrium desaturation curves for -32 mesh, -200 mesh and -100 + 200 mesh coal cakes (Pittsburgh Seam coal), formed with distilled water have been calculated. A bond flow correlation factor, F/sub c/ is introduced to account for channeling of the displacing fluid through high volume, low resistance flow paths - a phenomenon which is displayed by many real systems. It is determined that a single value of 0.6 for F/sub c/ is required for -32 mesh and -200 mesh coals. However, for -100 + 200 mesh coal, where all small as well as large particles have been removed, a value of 1.0 is required. The results of six -32 mesh cakes formed with surfactants show that the effect of surfactants can be accounted for by modifying one of the model parameters, the entry diameter correction. A correlation is presented to estimate the modified correction using experimentally determined surface tension and contact angle values. Further, the predicted final saturations agree with the experimental values within an average absolute error of 5%. 16 refs., 11 figs., 2 tabs.

  16. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  17. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

    Science.gov (United States)

    Lindsay, Grace W.

    2017-01-01

    Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (

  18. Local dependency in networks

    Directory of Open Access Journals (Sweden)

    Kudĕlka Miloš

    2015-06-01

    Full Text Available Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network’s nodes from the structure in local surroundings of individual nodes. For the tasks we deal with in this article, the key technical parameter is locality. Since only the surroundings of the examined nodes are used in computations, there is no need to analyze the entire network. This allows the application of our approach in the area of large-scale networks. We present several experiments using small networks as well as large-scale artificial and real world networks. The results of the experiments show high effectiveness due to the locality of our approach and also high quality node ranking comparable to PageRank.

  19. Recyclable crosslinked polymer networks with full property recovery made via one-step controlled radical polymerization

    Science.gov (United States)

    Jin, Kailong; Li, Lingqiao; Torkelson, John

    Rubber tires illustrate well the issues ranging from economic loss to environmental problems and sustainability issues that arise with spent, covalently crosslinked polymers. A nitroxide-mediated polymerization (NMP) strategy has been developed that allows for one-step synthesis of recyclable crosslinked polymers from monomers or polymers that contain carbon-carbon double bonds amenable to radical polymerization. Resulting materials possess dynamic alkoxyamine crosslinks that undergo reversible decrosslinking as a function of temperature. Using polybutadiene as starting material, and styrene, an appropriate nitroxide molecule and bifunctional initiator for initial crosslinking, a model for tire rubber can be produced by reaction at temperatures comparable to those employed in tire molding. Upon cooling, the crosslinks are made permanent due to the extraordinarily strong temperature dependence of the reverisible nitroxide capping and uncapping reaction. Based on thermomechanical property characterization, when the original crosslinked model rubber is chopped into bits and remolded in the melt state, a well-consolidated material is obtained which exhibits full recovery of properties reflecting crosslink density after multiple recycling steps.

  20. Organizations as Cognitive Systems: is Knowledge AN Emergent Property of Information Networks?

    Science.gov (United States)

    Biggiero, Lucio

    The substitution of knowledge to information as the entity that organizations process and deliver raises a number of questions concerning the nature of knowledge. The dispute on the codifiability of tacit knowledge and that juxtaposing the epistemology of practice vs. the epistemology of possession can be better faced by revisiting two crucial debates. One concerns the nature of cognition and the other the famous mind-body problem. Cognition can be associated with the capability of manipulating symbols, like in the traditional computational view of organizations, interpreting facts or symbols, like in the narrative approach to organization theory, or developing mental states (events), like argued by the growing field of organizational cognition. Applied to the study of organizations, the mind-body problem concerns the possibility (if any) and the forms in which organizational mental events, like trust, identity, cultures, etc., can be derived from the structural aspects (technological, cognitive or communication networks) of organizations. By siding in extreme opposite positions, the two epistemologies appear irreducible one another and pay its own inner consistency with remarkable difficulties in describing and explaining some empirical phenomena. Conversely, by legitimating the existence of both tacit and explicit knowledge, by emphasizing the space of human interactions, and by assuming that mental events can be explained with the structural aspects of organizations, Nonaka's SECI model seems an interesting middle way between the two rival epistemologies.

  1. Assessment of system reliability for a stochastic-flow distribution network with the spoilage property

    Science.gov (United States)

    Lin, Yi-Kuei; Huang, Cheng-Fu; Yeh, Cheng-Ta

    2016-04-01

    In supply chain management, satisfying customer demand is the most concerned for the manager. However, the goods may rot or be spoilt during delivery owing to natural disasters, inclement weather, traffic accidents, collisions, and so on, such that the intact goods may not meet market demand. This paper concentrates on a stochastic-flow distribution network (SFDN), in which a node denotes a supplier, a transfer station, or a market, while a route denotes a carrier providing the delivery service for a pair of nodes. The available capacity of the carrier is stochastic because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the system reliability, the probability that the SFDN can satisfy the market demand with the spoilage rate under the budget constraint from multiple suppliers to the customer. An algorithm is developed in terms of minimal paths to evaluate the system reliability along with a numerical example to illustrate the solution procedure. A practical case of fruit distribution is presented accordingly to emphasise the management implication of the system reliability.

  2. Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

    Science.gov (United States)

    Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

    2010-12-16

    A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

  3. How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network

    Directory of Open Access Journals (Sweden)

    Holk eCruse

    2013-06-01

    Full Text Available An artificial neural network called reaCog is described which is based on a decentralized, reactive and embodied architecture to control non-trivial hexapod walking in unpredictable environment (Walknet as well as insect-like navigation (Navinet. In reaCog, these basic networks are extended in such a way that the complete system, reaCog, adopts the capability of inventing new behaviors and - via internal simulation - of planning ahead. This cognitive expansion enables the reactive system to be enriched with additional procedures. Here, we focus on the question to what extent properties of phenomena to be characterized on a different level of description as for example consciousness can be found in this minimally cognitive system. Adopting a monist view, we argue that the phenomenal aspect of mental phenomena can be neglected when discussing the function of such a system. Under this condition, reaCog is discussed to be equipped with properties as are bottom-up and top-down attention, intentions, volition and some aspects of Access Consciousness. These properties have not been explicitly implemented but emerge from the cooperation between the elements of the network. The aspects of access consciousness found in reaCog concern the above mentioned ability to plan ahead and to invent and guide (new actions. Furthermore, global accessibility of memory elements, another aspect characterizing Access Consciousness is realized by this network. reaCog allows for both reactive/automatic control and (access- conscious control of behavior. We discuss examples for interactions between both the reactive domain and the conscious domain. Metacognition or Reflexive Consciousness is not a property of reaCog. Possible expansions are discussed to allow for further properties of Access Consciousness, verbal report on internal states, and for Metacognition. In summary, we argue that already simple networks allow for properties of consciousness if leaving the phenomenal

  4. How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network.

    Science.gov (United States)

    Cruse, Holk; Schilling, Malte

    2013-01-01

    An artificial neural network called reaCog is described which is based on a decentralized, reactive and embodied architecture developed to control non-trivial hexapod walking in an unpredictable environment (Walknet) while using insect-like navigation (Navinet). In reaCog, these basic networks are extended in such a way that the complete system, reaCog, adopts the capability of inventing new behaviors and - via internal simulation - of planning ahead. This cognitive expansion enables the reactive system to be enriched with additional procedures. Here, we focus on the question to what extent properties of phenomena to be characterized on a different level of description as for example consciousness can be found in this minimally cognitive system. Adopting a monist view, we argue that the phenomenal aspect of mental phenomena can be neglected when discussing the function of such a system. Under this condition, reaCog is discussed to be equipped with properties as are bottom-up and top-down attention, intentions, volition, and some aspects of Access Consciousness. These properties have not been explicitly implemented but emerge from the cooperation between the elements of the network. The aspects of Access Consciousness found in reaCog concern the above mentioned ability to plan ahead and to invent and guide (new) actions. Furthermore, global accessibility of memory elements, another aspect characterizing Access Consciousness is realized by this network. reaCog allows for both reactive/automatic control and (access-) conscious control of behavior. We discuss examples for interactions between both the reactive domain and the conscious domain. Metacognition or Reflexive Consciousness is not a property of reaCog. Possible expansions are discussed to allow for further properties of Access Consciousness, verbal report on internal states, and for Metacognition. In summary, we argue that already simple networks allow for properties of consciousness if leaving the phenomenal

  5. Transport properties and pore-network structure in variably-saturated Sphagnum peat soil

    DEFF Research Database (Denmark)

    Hamamoto, Shoichiro; Dissanayaka, Shiromi Himalika; Kawamoto, K.

    2016-01-01

    Gas and water transport in peat soil are of increasing interest because of their potentially large environmental and climatic effects under different types of land use. In this research, the water retention curve (WRC), gas diffusion coefficient (Dg) and air and water permeabilities (ka and kw......) of layers in peat soil from two profiles were measured under different moisture conditions. A two-region Archie's Law (2RAL)-type model was applied successfully to the four properties; the reference point was taken at -9.8kPa of soil-water matric potential where volume shrinkage typically started to occur....... For WRC in the very decomposed peat soil, the 2RAL saturation exponents (n) obtained for both the wetter (nw) and drier regions (nd) were smaller than those for the less decomposed peat. For Dg, the saturation exponent in the wetter region was larger than that in the drier one for all layers, which...

  6. Experimental and modelling studies of the shape memory properties of amorphous polymer network composites

    International Nuclear Information System (INIS)

    Arrieta, J S; Diani, J; Gilormini, P

    2014-01-01

    Shape memory polymer composites (SMPCs) have become an important way to leverage improvements in the development of applications featuring shape memory polymers (SMPs). In this study, an amorphous SMP matrix has been filled with different types of reinforcements. An experimental set of results is presented and then compared to three-dimensional (3D) finite-element simulations. Thermomechanical shape memory cycles were performed in uniaxial tension. The fillers effect was studied in stress-free and constrained-strain recoveries. Experimental observations indicate complete shape recovery and put in evidence the increased sensitivity of constrained length stress recoveries to the heating ramp on the tested composites. The simulations reproduced a simplified periodic reinforced composite and used a model for the matrix material that has been previously tested on regular SMPs. The latter combines viscoelasticity at finite strain and time-temperature superposition. The simulations easily allow representation of the recovery properties of a reinforced SMP. (paper)

  7. Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

    Science.gov (United States)

    Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

    2017-03-01

    Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (pdifferences in some regions of the inferior frontal and parietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

  8. Synaptic properties of SOM- and CCK-expressing cells in dentate gyrus interneuron networks.

    Science.gov (United States)

    Savanthrapadian, Shakuntala; Meyer, Thomas; Elgueta, Claudio; Booker, Sam A; Vida, Imre; Bartos, Marlene

    2014-06-11

    Hippocampal GABAergic cells are highly heterogeneous, but the functional significance of this diversity is not fully understood. By using paired recordings of synaptically connected interneurons in slice preparations of the rat and mouse dentate gyrus (DG), we show that morphologically identified interneurons form complex neuronal networks. Synaptic inhibitory interactions exist between cholecystokinin (CCK)-expressing hilar commissural associational path (HICAP) cells and among somatostatin (SOM)-containing hilar perforant path-associated (HIPP) interneurons. Moreover, both interneuron types inhibit parvalbumin (PV)-expressing perisomatic inhibitory basket cells (BCs), whereas BCs and HICAPs rarely target HIPP cells. HICAP and HIPP cells produce slow, weak, and unreliable inhibition onto postsynaptic interneurons. The time course of inhibitory signaling is defined by the identity of the presynaptic and postsynaptic cell. It is the slowest for HIPP-HIPP, intermediately slow for HICAP-HICAP, but fast for BC-BC synapses. GABA release at interneuron-interneuron synapses also shows cell type-specific short-term dynamics, ranging from multiple-pulse facilitation at HICAP-HICAP, biphasic modulation at HIPP-HIPP to depression at BC-BC synapses. Although dendritic inhibition at HICAP-BC and HIPP-BC synapses appears weak and slow, channelrhodopsin 2-mediated excitation of SOM terminals demonstrates that they effectively control the activity of target interneurons. They markedly reduce the discharge probability but sharpen the temporal precision of action potential generation. Thus, dendritic inhibition seems to play an important role in determining the activity pattern of GABAergic interneuron populations and thereby the flow of information through the DG circuitry. Copyright © 2014 the authors 0270-6474/14/348197-13$15.00/0.

  9. Drug-selected human lung cancer stem cells: cytokine network, tumorigenic and metastatic properties.

    Directory of Open Access Journals (Sweden)

    Vera Levina

    2008-08-01

    Full Text Available Cancer stem cells (CSCs are thought to be responsible for tumor regeneration after chemotherapy, although direct confirmation of this remains forthcoming. We therefore investigated whether drug treatment could enrich and maintain CSCs and whether the high tumorogenic and metastatic abilities of CSCs were based on their marked ability to produce growth and angiogenic factors and express their cognate receptors to stimulate tumor cell proliferation and stroma formation.Treatment of lung tumor cells with doxorubicin, cisplatin, or etoposide resulted in the selection of drug surviving cells (DSCs. These cells expressed CD133, CD117, SSEA-3, TRA1-81, Oct-4, and nuclear beta-catenin and lost expression of the differentiation markers cytokeratins 8/18 (CK 8/18. DSCs were able to grow as tumor spheres, maintain self-renewal capacity, and differentiate. Differentiated progenitors lost expression of CD133, gained CK 8/18 and acquired drug sensitivity. In the presence of drugs, differentiation of DSCs was abrogated allowing propagation of cells with CSC-like characteristics. Lung DSCs demonstrated high tumorogenic and metastatic potential following inoculation into SCID mice, which supported their classification as CSCs. Luminex analysis of human and murine cytokines in sonicated lysates of parental- and CSC-derived tumors revealed that CSC-derived tumors contained two- to three-fold higher levels of human angiogenic and growth factors (VEGF, bFGF, IL-6, IL-8, HGF, PDGF-BB, G-CSF, and SCGF-beta. CSCs also showed elevated levels of expression of human VEGFR2, FGFR2, CXCR1, 2 and 4 receptors. Moreover, human CSCs growing in SCID mice stimulated murine stroma to produce elevated levels of angiogenic and growth factors.These findings suggest that chemotherapy can lead to propagation of CSCs and prevention of their differentiation. The high tumorigenic and metastatic potentials of CSCs are associated with efficient cytokine network production that may represent

  10. Altering the swelling pressures within in vitro engineered cartilage is predicted to modulate the configuration of the collagen network and hence improve tissue mechanical properties.

    Science.gov (United States)

    Nagel, Thomas; Kelly, Daniel J

    2013-06-01

    Prestress in the collagen network has a significant impact on the material properties of cartilaginous tissues. It is closely related to the recruitment configuration of the collagen network which defines the transition from lax collagen fibres to uncrimped, load-bearing collagen fibres. This recruitment configuration can change in response to alterations in the external environmental conditions. In this study, the influence of changes in external salt concentration or sequential proteoglycan digestion on the configuration of the collagen network of tissue engineered cartilage is investigated using a previously developed computational model. Collagen synthesis and network assembly are assumed to occur in the tissue configuration present during in vitro culture. The model assumes that if this configuration is more compact due to changes in tissue swelling, the collagen network will adapt by lowering its recruitment stretch. When returned to normal physiological conditions, these tissues will then have a higher prestress in the collagen network. Based on these assumptions, the model demonstrates that proteoglycan digestion at discrete time points during culture as well as culture in a hypertonic medium can improve the functionality of tissue engineered cartilage, while culture in hypotonic solution is detrimental to the apparent mechanical properties of the graft. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. [Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].

    Science.gov (United States)

    Zhang, Lingling; Liu, Bin; Xu, Yangwen; Yang, Ming; Feng, Yuan; Huang, Yaqing; Huan, Zhichun; Hou, Zhaorui

    2015-02-03

    To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients. In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables. Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss. Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.

  12. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  13. The use of artificial neural networks for mathematical modeling of the effect of composition and production conditions on the properties of PVC floor coverings

    Directory of Open Access Journals (Sweden)

    Radovanović Rajko M.

    2017-01-01

    Full Text Available The application of PVC floor coverings is strongly connected with their end-use properties, which depend on the composition and processing conditions. It is very difficult to estimate the proper influence of the production parameters on the characteristics of PVC floor coverings due to their complex composition and various preparation procedures. The effect of different processing variables (such as time of bowling, temperature of bowling and composition of PVC plastisol on the mechanical properties of PVC floor coverings was investigated. The influence of different input parameters on the mechanical properties was successfully determined using an artificial neural network with an optimized number of hidden neurons. The Garson and Yoon models were applied to calculate and describe the variable contributions in the artificial neural networks. [Projekat Ministarstva nauke Republike Srbije, br. III 45022

  14. Fractal and multifractal analyses of bipartite networks

    Science.gov (United States)

    Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua

    2017-03-01

    Bipartite networks have attracted considerable interest in various fields. Fractality and multifractality of unipartite (classical) networks have been studied in recent years, but there is no work to study these properties of bipartite networks. In this paper, we try to unfold the self-similarity structure of bipartite networks by performing the fractal and multifractal analyses for a variety of real-world bipartite network data sets and models. First, we find the fractality in some bipartite networks, including the CiteULike, Netflix, MovieLens (ml-20m), Delicious data sets and (u, v)-flower model. Meanwhile, we observe the shifted power-law or exponential behavior in other several networks. We then focus on the multifractal properties of bipartite networks. Our results indicate that the multifractality exists in those bipartite networks possessing fractality. To capture the inherent attribute of bipartite network with two types different nodes, we give the different weights for the nodes of different classes, and show the existence of multifractality in these node-weighted bipartite networks. In addition, for the data sets with ratings, we modify the two existing algorithms for fractal and multifractal analyses of edge-weighted unipartite networks to study the self-similarity of the corresponding edge-weighted bipartite networks. The results show that our modified algorithms are feasible and can effectively uncover the self-similarity structure of these edge-weighted bipartite networks and their corresponding node-weighted versions.

  15. Automatically assessing properties of dynamic cameras for camera selection and rapid deployment of video content analysis tasks in large-scale ad-hoc networks

    Science.gov (United States)

    den Hollander, Richard J. M.; Bouma, Henri; van Rest, Jeroen H. C.; ten Hove, Johan-Martijn; ter Haar, Frank B.; Burghouts, Gertjan J.

    2017-10-01

    Video analytics is essential for managing large quantities of raw data that are produced by video surveillance systems (VSS) for the prevention, repression and investigation of crime and terrorism. Analytics is highly sensitive to changes in the scene, and for changes in the optical chain so a VSS with analytics needs careful configuration and prompt maintenance to avoid false alarms. However, there is a trend from static VSS consisting of fixed CCTV cameras towards more dynamic VSS deployments over public/private multi-organization networks, consisting of a wider variety of visual sensors, including pan-tilt-zoom (PTZ) cameras, body-worn cameras and cameras on moving platforms. This trend will lead to more dynamic scenes and more frequent changes in the optical chain, creating structural problems for analytics. If these problems are not adequately addressed, analytics will not be able to continue to meet end users' developing needs. In this paper, we present a three-part solution for managing the performance of complex analytics deployments. The first part is a register containing meta data describing relevant properties of the optical chain, such as intrinsic and extrinsic calibration, and parameters of the scene such as lighting conditions or measures for scene complexity (e.g. number of people). A second part frequently assesses these parameters in the deployed VSS, stores changes in the register, and signals relevant changes in the setup to the VSS administrator. A third part uses the information in the register to dynamically configure analytics tasks based on VSS operator input. In order to support the feasibility of this solution, we give an overview of related state-of-the-art technologies for autocalibration (self-calibration), scene recognition and lighting estimation in relation to person detection. The presented solution allows for rapid and robust deployment of Video Content Analysis (VCA) tasks in large scale ad-hoc networks.

  16. Postnatal changes to the mechanical properties of articular cartilage are driven by the evolution of its collagen network

    Directory of Open Access Journals (Sweden)

    AR Gannon

    2015-01-01

    Full Text Available While it is well established that the composition and organisation of articular cartilage dramatically change during skeletal maturation, relatively little is known about how this impacts the mechanical properties of the tissue. In this study, digital image correlation was first used to quantify spatial deformation within mechanically compressed skeletally immature (4 and 8 week old and mature (1 and 3 year old porcine articular cartilage. The compressive modulus of the immature tissue was relatively homogeneous, while the stiffness of mature articular cartilage dramatically increased with depth from the articular surface. Other, well documented, biomechanical characteristics of the tissue also emerged with skeletal maturity, such as strain-softening and a depth-dependent Poisson’s ratio. The most significant changes that occurred with age were in the deep zone of the tissue, where an order of magnitude increase in compressive modulus (from 0.97 MPa to 9.4 MPa for low applied strains was observed from 4 weeks postnatal to skeletal maturity. These temporal increases in compressive stiffness occurred despite a decrease in tissue sulphated glycosaminoglycan content, but were accompanied by increases in tissue collagen content. Furthermore, helium ion microscopy revealed dramatic changes in collagen fibril alignment through the depth of the tissue with skeletal maturity, as well as a fivefold increase in fibril diameter with age. Finally, computational modelling was used to demonstrate how both collagen network reorganisation and collagen stiffening play a key role in determining the final compressive mechanical properties of the tissue. Together these findings provide a unique insight into evolving structure-function relations in articular cartilage.

  17. Google matrix analysis of directed networks

    Science.gov (United States)

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

    2015-10-01

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

  18. Properties and toughening mechanisms of PVA/PAM double-network hydrogels prepared by freeze-thawing and anneal-swelling.

    Science.gov (United States)

    Ou, Kangkang; Dong, Xia; Qin, Chengling; Ji, Xinan; He, Jinxin

    2017-08-01

    It is well known that preparation method of hydrogels has a significant effect on their properties. In this paper, freeze-thawing and anneal-swelling were applied to prepare poly(vinyl alcohol)/polyacrylamide (PVA/PAM) double-network hydrogels with covalently and physically cross-linked networks. The properties of these hydrogels were investigated and compared to control hydrogels. Results indicated that hydrogels fabricated by freeze-thawing show larger pores size and higher swelling capacity than those made by anneal-swelling and control hydrogels. Hydrogels prepared by anneal-swelling exhibit higher mechanical strength, energy dissipation, fracture energy, gel fraction and crystallinity than those made by freeze-thawing and control hydrogels. Physical cross-linking plays a key role in formation of physical-chemical double-network. The toughening mechanism of double-network hydrogel is related to their chain-fracture behavior and elasticity. The results also indicated that appropriate methods can endow hydrogels with specific microstructures and properties which would broaden current hydrogels research and applications in biomedical fields. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Property.

    Science.gov (United States)

    Piele, Philip K.

    Numerous cases in this year's chapter dealt with the same topics of previous years--contracts and bids for building construction, and detachment and annexation of a portion of a school district. The courts continued to attribute board discretionary authority to school boards in school property matters. Intergovernmental disputes over ownership or…

  20. Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

    Directory of Open Access Journals (Sweden)

    H. Andersen

    2017-08-01

    Full Text Available The role of aerosols, clouds and their interactions with radiation remain among the largest unknowns in the climate system. Even though the processes involved are complex, aerosol–cloud interactions are often analyzed by means of bivariate relationships. In this study, 15 years (2001–2015 of monthly satellite-retrieved near-global aerosol products are combined with reanalysis data of various meteorological parameters to predict satellite-derived marine liquid-water cloud occurrence and properties by means of region-specific artificial neural networks. The statistical models used are shown to be capable of predicting clouds, especially in regions of high cloud variability. On this monthly scale, lower-tropospheric stability is shown to be the main determinant of cloud fraction and droplet size, especially in stratocumulus regions, while boundary layer height controls the liquid-water amount and thus the optical thickness of clouds. While aerosols show the expected impact on clouds, at this scale they are less relevant than some meteorological factors. Global patterns of the derived sensitivities point to regional characteristics of aerosol and cloud processes.

  1. A membrane actuator based on an ionic polymer network and carbon nanotubes: the synergy of ionic transport and mechanical properties

    International Nuclear Information System (INIS)

    Dai, Chi-An; Hsiao, Chih-Chun; Weng, Shih-Chun; Kao, An-Cheng; Liu, Chien-Pan; Tsai, Wei-Bor; Chen, Wen-Shiang; Liu, Wei-Ming; Shih, Wen-Pin; Ma, Chien-Ching

    2009-01-01

    There is a growing interest in the development of ionic polymer–metal composites (IPMC) as sensors and actuators for biomedical applications due to their large deformation under low driving voltage. In this study, we employed poly(vinyl alcohol)/poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PVA/PAMPS) blend membranes as semi-interpenetrating polymer networks for ion exchange in IPMC construction. To improve the mechanical and electrical properties of the IPMC, multi-walled carbon nanotubes (MWNT) were added into PVA/PAMPS membranes. The actuator performance of the membranes was measured as a function of their water uptake, ion exchange capacity, ionic conductivity and the amount of MWNT in the membrane. The dispersion quality of the modified MWNT in the PVA/PAMPS membrane was measured using transmission electron microscopy. The cantilever-type IPMC actuator bends under applied voltage and its bending angle and the generative tip force were measured. Under an applied voltage, IPMC with ∼1 wt% MWNT showed the largest deflection and generated the largest blocking tip force compared with those of IPMC with other various amounts of MWNT. These results show that a small addition of MWNT can optimize the actuation performance of IPMC. The result indicates that IPMC with MWNT shows potential for use as biomimetic artificial muscle

  2. Effective Hydro-Mechanical Properties of Fluid-Saturated Fracture Networks

    Science.gov (United States)

    Pollmann, N.; Vinci, C.; Renner, J.; Steeb, H.

    2015-12-01

    Consideration of hydro-mechanical processes is essential for the characterization of liquid-resources as well as for many engineering applications. Furthermore, the modeling of seismic waves in fractured porous media finds application not only in geophysical exploration but also reservoir management. Fractures exhibit high-aspect-ratio geometries, i.e. they constitute thin and long hydraulic conduits. Motivated by this peculiar geometry, the investigation of the hydro-mechanically coupled processes is performed by means of a hybrid-dimensional modeling approach. The effective material behavior of domains including complex fracture patterns in a porous rock is assessed by investigating the fluid pressure and the solid displacement of the skeleton saturated by compressible fluids. Classical balance equations are combined with a Poiseuille-type flow in the dimensionally reduced fracture. In the porous surrounding rock, the classical Biot-theory is applied. For simple geometries, our findings show that two main fluid-flow processes occur, leak-off from fractures to the surrounding rock and fracture flow within and between the connected fractures. The separation of critical frequencies of the two flow processes is not straightforward, in particular for systems containing a large number of fractures. Our aim is to model three dimensional hydro-mechanically coupled processes within complex fracture patterns and in particular determine the frequency-dependent attenuation characteristics. Furthermore, the effect of asperities of the fracture surfaces on the fracture stiffness and on the hydraulic conductivity will be added to the approach.

  3. Modeling interacting dynamic networks: II. Systematic study of the statistical properties of cross-links between two networks with preferred degrees

    International Nuclear Information System (INIS)

    Liu, Wenjia; Schmittmann, B; Zia, R K P

    2014-01-01

    In a recent work (Liu et al, 2013 J. Stat. Mech. P08001), we introduced dynamic networks with preferred degrees and presented simulation and analytic studies of a single, homogeneous system as well as two interacting networks. Here, we extend these studies to a wider range of parameter space, in a more systematic fashion. Though the interaction we introduced seems simple and intuitive, it produced dramatically different behavior in the single- and two-network systems. Specifically, partitioning the single network into two identical sectors, we find the cross-link distribution to be a sharply peaked Gaussian. In stark contrast, we find a very broad and flat plateau in the case of two interacting identical networks. A sound understanding of this phenomenon remains elusive. Exploring more asymmetric interacting networks, we discover a kind of ‘universal behavior’ for systems in which the ‘introverts’ (nodes with smaller preferred degree) are far outnumbered. Remarkably, an approximation scheme for their degree distribution can be formulated, leading to very successful predictions. (paper)

  4. Endogenous network of firms and systemic risk

    Science.gov (United States)

    Ma, Qianting; He, Jianmin; Li, Shouwei

    2018-02-01

    We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.

  5. Vulnerability of complex networks

    Science.gov (United States)

    Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco

    2011-01-01

    We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.

  6. Thermal and Electrical Properties of Nanocomposites, Including Material Properties

    NARCIS (Netherlands)

    Kochetov, R.

    2012-01-01

    The research described in this thesis is part of a state-funded IOP-EMVT project in cooperation with industrial companies, aiming at the design, assessment and implementation of new, environmental friendly (e.g. oil and SF6 - free) solid dielectric materials. A large disadvantage of solid polymer

  7. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  8. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells.

    Directory of Open Access Journals (Sweden)

    Pablo Martínez-Cañada

    2018-01-01

    Full Text Available Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs and interneurons (INs not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY. We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed ('push-pull' and phase-matched ('push-push', as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli

  9. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells

    Science.gov (United States)

    Martínez-Cañada, Pablo; Halnes, Geir; Fyhn, Marianne

    2018-01-01

    Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when

  10. On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

    Science.gov (United States)

    Krein, Michael

    After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the

  11. Latent geometry of bipartite networks

    Science.gov (United States)

    Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

    2017-03-01

    Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

  12. Poly(ethylene glycol)-grafted cyclic acetals based polymer networks with non-water-swellable, biodegradable and surface hydrophilic properties

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Ruixue, E-mail: qdruinyan@hotmail.com [Complex and Intelligent Research Center, School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai (China); Zhang, Nan; Wu, Wentao [School of Materials Science and Engineering, Changzhou University, Changzhou 213164 (China); Wang, Kemin, E-mail: kemin-wang@hotmail.com [School of Materials Science and Engineering, Changzhou University, Changzhou 213164 (China)

    2016-05-01

    Cyclic acetals based biomaterial without acidic products during hydrolytic degradation is a promising candidate for tissue engineering applications; however, low hydrophilicity is still one limitation for its biomedical application. In this work, we aim to achieve non-water-swellable cyclic acetal networks with improved hydrophilicity and surface wettability by copolymerization of cyclic acetal units based monomer, 5-ethyl-5-(hydroxymethyl)-β,β-dimethyl-1, 3-dioxane-2-ethanol diacrylate (EHD) and methoxy poly(ethylene glycol) monoacrylate (mPEGA) under UV irradiation, to avoid swelling of conventional hydrogels which could limit their applicability in particular of the mechanical properties and geometry integrity. Various EHD/mPEGA networks were fabricated with different concentrations of mPEGA from 0 to 30%, and the results showed photopolymerization behavior, mechanical property and thermal stability could not be significantly affected by addition of mPEGA, while the surface hydrophilicity was dramatically improved with the increase of mPEGA and could achieve a water contact angle of 37° with 30% mPEGA concentration. The obtained EHD/mPEGA network had comparative degradation rate to the PECA hydrogels reported previously, and MTT assay indicated it was biocompatible to L929 cells. - Highlights: • Cyclic acetals contained EHD/mPEGA networks were fabricated by photopolymerization. • It can be degraded under simulated physiological condition without acidic products. • Surface hydrophilicity was increased without swelling in water.

  13. Temporal networks

    CERN Document Server

    Saramäki, Jari

    2013-01-01

    The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach  the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and concept...

  14. Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application

    OpenAIRE

    Li, Xiang

    2005-01-01

    In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...

  15. Network Simulation

    CERN Document Server

    Fujimoto, Richard

    2006-01-01

    "Network Simulation" presents a detailed introduction to the design, implementation, and use of network simulation tools. Discussion topics include the requirements and issues faced for simulator design and use in wired networks, wireless networks, distributed simulation environments, and fluid model abstractions. Several existing simulations are given as examples, with details regarding design decisions and why those decisions were made. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the

  16. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  17. Nestedness of ectoparasite-vertebrate host networks.

    Directory of Open Access Journals (Sweden)

    Sean P Graham

    2009-11-01

    Full Text Available Determining the structure of ectoparasite-host networks will enable disease ecologists to better understand and predict the spread of vector-borne diseases. If these networks have consistent properties, then studying the structure of well-understood networks could lead to extrapolation of these properties to others, including those that support emerging pathogens. Borrowing a quantitative measure of network structure from studies of mutualistic relationships between plants and their pollinators, we analyzed 29 ectoparasite-vertebrate host networks--including three derived from molecular bloodmeal analysis of mosquito feeding patterns--using measures of nestedness to identify non-random interactions among species. We found significant nestedness in ectoparasite-vertebrate host lists for habitats ranging from tropical rainforests to polar environments. These networks showed non-random patterns of nesting, and did not differ significantly from published estimates of nestedness from mutualistic networks. Mutualistic and antagonistic networks appear to be organized similarly, with generalized ectoparasites interacting with hosts that attract many ectoparasites and more specialized ectoparasites usually interacting with these same "generalized" hosts. This finding has implications for understanding the network dynamics of vector-born pathogens. We suggest that nestedness (rather than random ectoparasite-host associations can allow rapid transfer of pathogens throughout a network, and expand upon such concepts as the dilution effect, bridge vectors, and host switching in the context of nested ectoparasite-vertebrate host networks.

  18. Network science

    CERN Document Server

    Barabasi, Albert-Laszlo

    2016-01-01

    Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network sci...

  19. Robustness and structure of complex networks

    Science.gov (United States)

    Shao, Shuai

    This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

  20. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago V. V.; Giannitsarou, Chryssi; Johnson, Charles R.

    2016-01-01

    This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00199-016-0992-1 We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and d...

  1. Spatial networks

    Science.gov (United States)

    Barthélemy, Marc

    2011-02-01

    Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

  2. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    Science.gov (United States)

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

  3. Animal transportation networks

    Science.gov (United States)

    Perna, Andrea; Latty, Tanya

    2014-01-01

    Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research. PMID:25165598

  4. Network workshop

    DEFF Research Database (Denmark)

    Bruun, Jesper; Evans, Robert Harry

    2014-01-01

    This paper describes the background for, realisation of and author reflections on a network workshop held at ESERA2013. As a new research area in science education, networks offer a unique opportunity to visualise and find patterns and relationships in complicated social or academic network data....... These include student relations and interactions and epistemic and linguistic networks of words, concepts and actions. Network methodology has already found use in science education research. However, while networks hold the potential for new insights, they have not yet found wide use in the science education...... research community. With this workshop, participants were offered a way into network science based on authentic educational research data. The workshop was constructed as an inquiry lesson with emphasis on user autonomy. Learning activities had participants choose to work with one of two cases of networks...

  5. Formation of actin networks in microfluidic concentration gradients

    Directory of Open Access Journals (Sweden)

    Natalja eStrelnikova

    2016-05-01

    Full Text Available The physical properties of cytoskeletal networks are contributors in a number of mechanical responses of cells including cellular deformation and locomotion, and are crucial for the proper action of living cells. Local chemical gradients modulate cytoskeletal functionality including the interactions of the cytoskeleton with other cellular components. Actin is a major constituent of the cytoskeleton. Introducing a microfluidic-based platform, we explored the impact of concentration gradients on the formation and structural properties of actin networks. Microfluidics-controlled flow-free steady state experimental conditions allow for the generation of chemical gradients of different profiles, such as linear or step-like. We discovered specific features of actin networks emerging in defined gradients. In particular, we analyzed the effects of spatial conditions on network properties, bending rigidities of network links, and the network elasticity.

  6. Prediction of phenotypic susceptibility to antiretroviral drugs using physiochemical properties of the primary enzymatic structure combined with artificial neural networks

    DEFF Research Database (Denmark)

    Kjaer, J; Høj, L; Fox, Z

    2008-01-01

    OBJECTIVES: Genotypic interpretation systems extrapolate observed associations in datasets to predict viral susceptibility to antiretroviral drugs (ARVs) for given isolates. We aimed to develop and validate an approach using artificial neural networks (ANNs) that employ descriptors...

  7. Concurrent conditional clustering of multiple networks: COCONETS.

    Directory of Open Access Journals (Sweden)

    Sabrina Kleessen

    Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

  8. Social inheritance can explain the structure of animal social networks

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-01-01

    The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

  9. Efficient methods for including quantum effects in Monte Carlo calculations of large systems: extension of the displaced points path integral method and other effective potential methods to calculate properties and distributions.

    Science.gov (United States)

    Mielke, Steven L; Dinpajooh, Mohammadhasan; Siepmann, J Ilja; Truhlar, Donald G

    2013-01-07

    We present a procedure to calculate ensemble averages, thermodynamic derivatives, and coordinate distributions by effective classical potential methods. In particular, we consider the displaced-points path integral (DPPI) method, which yields exact quantal partition functions and ensemble averages for a harmonic potential and approximate quantal ones for general potentials, and we discuss the implementation of the new procedure in two Monte Carlo simulation codes, one that uses uncorrelated samples to calculate absolute free energies, and another that employs Metropolis sampling to calculate relative free energies. The results of the new DPPI method are compared to those from accurate path integral calculations as well as to results of two other effective classical potential schemes for the case of an isolated water molecule. In addition to the partition function, we consider the heat capacity and expectation values of the energy, the potential energy, the bond angle, and the OH distance. We also consider coordinate distributions. The DPPI scheme performs best among the three effective potential schemes considered and achieves very good accuracy for all of the properties considered. A key advantage of the effective potential schemes is that they display much lower statistical sampling variances than those for accurate path integral calculations. The method presented here shows great promise for including quantum effects in calculations on large systems.

  10. Shape-memory properties of magnetically active triple-shape nanocomposites based on a grafted polymer network with two crystallizable switching segments

    Directory of Open Access Journals (Sweden)

    A. Lendlein

    2012-01-01

    Full Text Available Thermo-sensitive shape-memory polymers (SMP, which are capable of memorizing two or more different shapes, have generated significant research and technological interest. A triple-shape effect (TSE of SMP can be activated e.g. by increasing the environmental temperature (Tenv, whereby two switching temperatures (Tsw have to be exceeded to enable the subsequent shape changes from shape (A to shape (B and finally the original shape (C. In this work, we explored the thermally and magnetically initiated shape-memory properties of triple-shape nanocomposites with various compositions and particle contents using different shape-memory creation procedures (SMCP. The nanocomposites were prepared by the incorporation of magnetite nanoparticles into a multiphase polymer network matrix with grafted polymer network architecture containing crystallizable poly(ethylene glycol (PEG side chains and poly(ε-caprolactone (PCL crosslinks named CLEGC. Excellent triple-shape properties were achieved for nanocomposites with high PEG weight fraction when two-step programming procedures were applied. In contrast, single-step programming resulted in dual-shape properties for all investigated materials as here the temporary shape (A was predominantly fixed by PCL crystallites.

  11. Composing Music with Complex Networks

    Science.gov (United States)

    Liu, Xiaofan; Tse, Chi K.; Small, Michael

    In this paper we study the network structure in music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurrences. We analyze sample compositions from Bach, Mozart, Chopin, as well as other types of music including Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. Power-law exponents of degree distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be created by using a biased random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. The newly created music from complex networks will be played in the presentation.

  12. Correlation of the plasmon-enhanced photoconductance and photovoltaic properties of core-shell Au@TiO{sub 2} network

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Yiqun [Department of Chemistry, Kansas State University, Manhattan, Kansas 66506 (United States); Wu, Judy [Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas 66045 (United States); Li, Jun, E-mail: junli@ksu.edu [Department of Chemistry, Kansas State University, Manhattan, Kansas 66506 (United States); College of Chemistry and Chemical Engineering, Hubei Normal University, Huangshi, Hubei 435002 (China)

    2016-08-29

    This study reveals the contribution of hot electrons from the excited plasmonic nanoparticles in dye sensitized solar cells (DSSCs) by correlating the photoconductance of a core-shell Au@TiO{sub 2} network on a micro-gap electrode and the photovolatic properties of this material as photoanodes in DSSCs. The distinct wavelength dependence of these two devices reveals that the plasmon-excited hot electrons can easily overcome the Schottky barrier at Au/TiO{sub 2} interface in the whole visible wavelength range and transfer from Au nanoparticles into the TiO{sub 2} network. The enhanced charge carrier density leads to higher photoconductance and facilitates more efficient charge separation and photoelectron collection in the DSSCs.

  13. Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

    International Nuclear Information System (INIS)

    Tsarouchas, D.; Markaki, A.E.

    2011-01-01

    This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing.

  14. Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

    Science.gov (United States)

    Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

    2016-04-01

    Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  15. Photo-cross-linked PLA-PEO-PLA hydrogels from self-assembled physical networks: mechanical properties and influence of assumed constitutive relationships.

    Science.gov (United States)

    Sanabria-DeLong, Naomi; Crosby, Alfred J; Tew, Gregory N

    2008-10-01

    Poly(lactide)-block-poly(ethylene oxide)-block-poly(lactide) (PLA-PEO-PLA) triblock copolymers are known to form physical hydrogels in water as a result of the polymer's amphiphilicity. Their mechanical properties, biocompatibility, and biodegradability have made them attractive for use as soft tissue scaffolds. However, the network junction points are not covalently cross-linked, and in a highly aqueous environment these hydrogels adsorb more water, transform from gel to sol, and lose the designed mechanical properties. In this article, a hydrogel was formed by the use of a novel two-step approach. In the first step, the end-functionalized PLA-PEO-PLA triblock was self-assembled into a physical hydrogel through hydrophobic micelle network junctions, and in the second step, this self-assembled physical network structure was locked into place by photo-cross-linking the terminal acrylate groups. In contrast with physical hydrogels, the photo-cross-linked gels remained intact in phosphate-buffered solution at body temperature. The swelling, degradation, and mechanical properties were characterized, and they demonstrated an extended degradation time (approximately 65 days), an exponential decrease in modulus with degradation time, and a tunable shear modulus (1.6-133 kPa). We also discuss the various constitutive relationships (Hookean, neo-Hookean, and Mooney-Rivlin) that can be used to describe the stress-strain behavior of these hydrogels. The chosen model and assumptions used for data fitting influenced the obtained modulus values by as much as a factor of 3.5, which demonstrates the importance of clearly stating one's data fitting parameters so that accurate comparisons can be made within the literature.

  16. Off-fault tip splay networks: a genetic and generic property of faults indicative of their long-term propagation, and a major component of off-fault damage

    Science.gov (United States)

    Perrin, C.; Manighetti, I.; Gaudemer, Y.

    2015-12-01

    Faults grow over the long-term by accumulating displacement and lengthening, i.e., propagating laterally. We use fault maps and fault propagation evidences available in literature to examine geometrical relations between parent faults and off-fault splays. The population includes 47 worldwide crustal faults with lengths from millimeters to thousands of kilometers and of different slip modes. We show that fault splays form adjacent to any propagating fault tip, whereas they are absent at non-propagating fault ends. Independent of parent fault length, slip mode, context, etc, tip splay networks have a similar fan shape widening in direction of long-term propagation, a similar relative length and width (~30 and ~10 % of parent fault length, respectively), and a similar range of mean angles to parent fault (10-20°). Tip splays more commonly develop on one side only of the parent fault. We infer that tip splay networks are a genetic and a generic property of faults indicative of their long-term propagation. We suggest that they represent the most recent damage off-the parent fault, formed during the most recent phase of fault lengthening. The scaling relation between parent fault length and width of tip splay network implies that damage zones enlarge as parent fault length increases. Elastic properties of host rocks might thus be modified at large distances away from a fault, up to 10% of its length. During an earthquake, a significant fraction of coseismic slip and stress is dissipated into the permanent damage zone that surrounds the causative fault. We infer that coseismic dissipation might occur away from a rupture zone as far as a distance of 10% of the length of its causative fault. Coseismic deformations and stress transfers might thus be significant in broad regions about principal rupture traces. This work has been published in Comptes Rendus Geoscience under doi:10.1016/j.crte.2015.05.002 (http://www.sciencedirect.com/science/article/pii/S1631071315000528).

  17. Artificial neural networks application for modeling of friction stir welding effects on mechanical properties of 7075-T6 aluminum alloy

    Science.gov (United States)

    Maleki, E.

    2015-12-01

    Friction stir welding (FSW) is a relatively new solid-state joining technique that is widely adopted in manufacturing and industry fields to join different metallic alloys that are hard to weld by conventional fusion welding. Friction stir welding is a very complex process comprising several highly coupled physical phenomena. The complex geometry of some kinds of joints makes it difficult to develop an overall governing equations system for theoretical behavior analyse of the friction stir welded joints. Weld quality is predominantly affected by welding effective parameters, and the experiments are often time consuming and costly. On the other hand, employing artificial intelligence (AI) systems such as artificial neural networks (ANNs) as an efficient approach to solve the science and engineering problems is considerable. In present study modeling of FSW effective parameters by ANNs is investigated. To train the networks, experimental test results on thirty AA-7075-T6 specimens are considered, and the networks are developed based on back propagation (BP) algorithm. ANNs testing are carried out using different experimental data that they are not used during networks training. In this paper, rotational speed of tool, welding speed, axial force, shoulder diameter, pin diameter and tool hardness are regarded as inputs of the ANNs. Yield strength, tensile strength, notch-tensile strength and hardness of welding zone are gathered as outputs of neural networks. According to the obtained results, predicted values for the hardness of welding zone, yield strength, tensile strength and notch-tensile strength have the least mean relative error (MRE), respectively. Comparison of the predicted and the experimental results confirms that the networks are adjusted carefully, and the ANN can be used for modeling of FSW effective parameters.

  18. Artificial neural networks application for modeling of friction stir welding effects on mechanical properties of 7075-T6 aluminum alloy

    International Nuclear Information System (INIS)

    Maleki, E

    2015-01-01

    Friction stir welding (FSW) is a relatively new solid-state joining technique that is widely adopted in manufacturing and industry fields to join different metallic alloys that are hard to weld by conventional fusion welding. Friction stir welding is a very complex process comprising several highly coupled physical phenomena. The complex geometry of some kinds of joints makes it difficult to develop an overall governing equations system for theoretical behavior analyse of the friction stir welded joints. Weld quality is predominantly affected by welding effective parameters, and the experiments are often time consuming and costly. On the other hand, employing artificial intelligence (AI) systems such as artificial neural networks (ANNs) as an efficient approach to solve the science and engineering problems is considerable. In present study modeling of FSW effective parameters by ANNs is investigated. To train the networks, experimental test results on thirty AA-7075-T6 specimens are considered, and the networks are developed based on back propagation (BP) algorithm. ANNs testing are carried out using different experimental data that they are not used during networks training. In this paper, rotational speed of tool, welding speed, axial force, shoulder diameter, pin diameter and tool hardness are regarded as inputs of the ANNs. Yield strength, tensile strength, notch-tensile strength and hardness of welding zone are gathered as outputs of neural networks. According to the obtained results, predicted values for the hardness of welding zone, yield strength, tensile strength and notch-tensile strength have the least mean relative error (MRE), respectively. Comparison of the predicted and the experimental results confirms that the networks are adjusted carefully, and the ANN can be used for modeling of FSW effective parameters. (paper)

  19. Functional architecture and global properties of the Corynebacterium glutamicum regulatory network: Novel insights from a dataset with a high genomic coverage.

    Science.gov (United States)

    Freyre-González, Julio A; Tauch, Andreas

    2017-09-10

    Corynebacterium glutamicum is a Gram-positive, anaerobic, rod-shaped soil bacterium able to grow on a diversity of carbon sources like sugars and organic acids. It is a biotechnological relevant organism because of its highly efficient ability to biosynthesize amino acids, such as l-glutamic acid and l-lysine. Here, we reconstructed the most complete C. glutamicum regulatory network to date and comprehensively analyzed its global organizational properties, systems-level features and functional architecture. Our analyses show the tremendous power of Abasy Atlas to study the functional organization of regulatory networks. We created two models of the C. glutamicum regulatory network: all-evidences (containing both weak and strong supported interactions, genomic coverage=73%) and strongly-supported (only accounting for strongly supported evidences, genomic coverage=71%). Using state-of-the-art methodologies, we prove that power-law behaviors truly govern the connectivity and clustering coefficient distributions. We found a non-previously reported circuit motif that we named complex feed-forward motif. We highlighted the importance of feedback loops for the functional architecture, beyond whether they are statistically over-represented or not in the network. We show that the previously reported top-down approach is inadequate to infer the hierarchy governing a regulatory network because feedback bridges different hierarchical layers, and the top-down approach disregards the presence of intermodular genes shaping the integration layer. Our findings all together further support a diamond-shaped, three-layered hierarchy exhibiting some feedback between processing and coordination layers, which is shaped by four classes of systems-level elements: global regulators, locally autonomous modules, basal machinery and intermodular genes. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Modeling the Effect of Crude Oil Impacted Sand on the Properties of Concrete Using Artificial Neural Networks

    OpenAIRE

    W. O. Ajagbe; A. A. Ganiyu; M. O. Owoyele; J. O. Labiran

    2013-01-01

    A network of the feedforward-type artificial neural networks (ANNs) was used to predict the compressive strength of concrete made from crude oil contaminated soil samples at 3, 7, 14, 28, 56, 84, and 168 days at different degrees of contamination of 2.5%, 5%, 10%, 15%, 20% and 25%. A total of 49 samples were used in the training, testing, and prediction phase of the modeling in the ratio 32 : 11 : 7. The TANH activation function was used and the maximum number of iterations was limited to 20,...

  1. The art of wireless sensor networks

    CERN Document Server

    2014-01-01

    During the last one and a half decades, wireless sensor networks have witnessed significant growth and tremendous development in both academia and industry.   “The Art of Wireless Sensor Networks: Volume 1: Fundamentals” focuses on the fundamentals concepts in the design, analysis, and implementation of wireless sensor networks. It covers the various layers of the lifecycle of this type of network from the physical layer up to the application layer. Its rationale is that the first volume covers contemporary design issues, tools, and protocols for radio-based two-dimensional terrestrial sensor networks. All the book chapters in this volume include up-to-date research work spanning various classic facets of the physical properties and functional behavior of wireless sensor networks, including physical layer, medium access control, data routing, topology management, mobility management, localization, task management, data management, data gathering, security, middleware, sensor technology, standards, and ...

  2. THE EVALUATION SYSTEM OF DESIGN SOLUTIONS FOR RESIDENTIAL PROPERTY ON THE PRE-INVESTMENT STAGE THROUGH NEURAL NETWORK TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    G. D. Kostsikava

    2016-01-01

    Full Text Available Ever since the Soviet Union design solutions were evaluated according to different criteria and indicators. At the present stage of evaluation systems of design solutions stands systemengineering doctrine is allocated. It is complemented by the theory of efficiency and financial sustainability investment project in view of the general market concept. Also great attention is paid to the virtual object modeling. It is urgent to include the behavior prediction of an investment construction project model at each stage of its life cycle. The high cost of all phases of this life cycle makes it necessary to calculate the feasibility of the investment. Very urgent to do it as accurately as possible and before we start of design works on the stage of the investment plan evaluation. Belarus has legislated pre-investment stage of construction project development. To evaluate the design solution at this stage is necessary to develop an investment justification, a project management plan and a business plan. They will evaluate and will compare several options for future objects by the complex. This requires not only time, but considerable financial costs. In order to optimize the process to develop an evaluation system design solutions based on existing projects. It allows the customer (investor choose design solutions to build the object without developing of pre-design documentations for several options. This system it is advisable to try out the example of apartment house building with the assistance of the national fund of project documentation and objects-analogues data bank. The developed evaluation system of design solutions for residential real estate objects in the pre-investment stage is supposed to use the theory of neural networks and neyroprogramming. This system bases on the input parameters projects. The hidden layer neurons are trained to choose suitable projects of apartment houses with their classification. The projects will be classified

  3. New seismograph includes filters

    Energy Technology Data Exchange (ETDEWEB)

    1979-11-02

    The new Nimbus ES-1210 multichannel signal enhancement seismograph from EG and G geometrics has recently been redesigned to include multimode signal fillers on each amplifier. The ES-1210F is a shallow exploration seismograph for near subsurface exploration such as in depth-to-bedrock, geological hazard location, mineral exploration, and landslide investigations.

  4. INTIMIDAD Y PROPIEDAD INTELECTUAL EN LAS REDES SOCIALES: EL CASO COLOMBIANO. PRIVACY AND INTELLECTUAL PROPERTY IN THE SOCIAL NETWORKS: THE COLOMBIAN CASE.

    Directory of Open Access Journals (Sweden)

    Hugo Nelson Castañeda

    2012-12-01

    Full Text Available Los abusos que se hace del derecho a la información en internet y especialmente en las Redes Sociales Virtuales (en adelante RSV son constantes y la posibilidad de restringirlos es mínima. Todo parecería indicar que en el mundo virtual no existirá la censura, pero se evidencia todo lo contrario. Muchos grupos de presión, entre ellos quienes buscan la defensa de intereses económicos, han instado a los gobiernos, como el colombiano, y a las empresas de la web (incluidas las RSV para que constituyan mecanismos de control de todo lo que se difunde por internet y evitar atentados contra el honor, la intimidad y la propiedad intelectual, pero los métodos (legales o de facto que se han implementado se convirtieron en una forma de censura de las expresiones creativas que reduce la disponibilidad de información y paradójicamente la libertad individual. Para demostrar lo anterior, en escrito se utilizó técnicas de estudio documental en los que se pudiera constatar la influencia de las RSV en el Derecho.Abuses of the right to information on the Internet and especially in virtual social networks (VSN from now on are constant and the possibility of restricting them is minimal. Everything would seem to indicate that in the virtual world there is no censorship, but there is evidence of the opposite. Many groups, including those who seek the defense of economic interests, have urged Governments, such as the Colombian one, and the Web companies (including the RSV so that they constitute control mechanisms of everything that is spread via the Internet and prevent the attacks against honor, privacy, and intellectual property, but the (legal or de facto methods that have been implemented have become a form of censorship of creative expressions that reduces the availability of information and paradoxically the individual freedom. In order to prove this, techniques of documentary study were used, in which the influence of the VSN in the Law, could be

  5. Antagonistic Phenomena in Network Dynamics

    Science.gov (United States)

    Motter, Adilson E.; Timme, Marc

    2018-03-01

    Recent research on the network modeling of complex systems has led to a convenient representation of numerous natural, social, and engineered systems that are now recognized as networks of interacting parts. Such systems can exhibit a wealth of phenomena that not only cannot be anticipated from merely examining their parts, as per the textbook definition of complexity, but also challenge intuition even when considered in the context of what is now known in network science. Here, we review the recent literature on two major classes of such phenomena that have far-reaching implications: (a) antagonistic responses to changes of states or parameters and (b) coexistence of seemingly incongruous behaviors or properties - both deriving from the collective and inherently decentralized nature of the dynamics. They include effects as diverse as negative compressibility in engineered materials, rescue interactions in biological networks, negative resistance in fluid networks, and the Braess paradox occurring across transport and supply networks. They also include remote synchronization, chimera states, and the converse of symmetry breaking in brain, power-grid, and oscillator networks as well as remote control in biological and bioinspired systems. By offering a unified view of these various scenarios, we suggest that they are representative of a yet broader class of unprecedented network phenomena that ought to be revealed and explained by future research.

  6. Fabrication of Robust Super hydrophobic Bamboo Based on ZnO Nano sheet Networks with Improved Water-, UV-, and Fire-Resistant Properties

    International Nuclear Information System (INIS)

    Li, J.; Sun, Q.; Yao, Q.; Wang, J.; Han, Sh.; Jin, Ch.

    2014-01-01

    Bamboo with water-resistant, UV-resistant, and fire-resistant properties was desirable in modern society. In this paper, the original bamboo was firstly treated with ZnO sol and then hydrothermally the ZnO nano sheet networks grow onto the bamboo surface and subsequently modified with fluoro alkyl silane (FAS-17). The FAS-17 treated bamboo substrate exhibited not only robust super hydrophobicity with a high contact angle of 161° but also stable repellency towards simulated acid rain (ph = 3) with a contact angle of 152°. Except for its robust super hydrophobicity, such a bamboo also presents superior water-resistant, UV-resistant, and fire-resistant properties.

  7. Fabrication of Robust Superhydrophobic Bamboo Based on ZnO Nanosheet Networks with Improved Water-, UV-, and Fire-Resistant Properties

    Directory of Open Access Journals (Sweden)

    Jingpeng Li

    2015-01-01

    Full Text Available Bamboo with water-resistant, UV-resistant, and fire-resistant properties was desirable in modern society. In this paper, the original bamboo was firstly treated with ZnO sol and then hydrothermally the ZnO nanosheet networks grow onto the bamboo surface and subsequently modified with fluoroalkyl silane (FAS-17. The FAS-17 treated bamboo substrate exhibited not only robust superhydrophobicity with a high contact angle of 161° but also stable repellency towards simulated acid rain (pH = 3 with a contact angle of 152°. Except for its robust superhydrophobicity, such a bamboo also presents superior water-resistant, UV-resistant, and fire-resistant properties.

  8. The Role of Nonlinearity in Computing Graph-Theoretical Properties of Resting-State Functional Magnetic Resonance Imaging Brain Networks

    Czech Academy of Sciences Publication Activity Database

    Hartman, David; Hlinka, Jaroslav; Paluš, Milan; Mantini, D.; Corbetta, M.

    2011-01-01

    Roč. 21, č. 1 (2011), art.no 013119 ISSN 1054-1500 R&D Projects: GA MŠk 7E08027 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex network * fMRI * brain connectivity * nonlinear * mutual information * correlation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.076, year: 2011

  9. Study on the morphology and thermomechanical properties of poly(urethane-siloxane) networks based on hyperbranched polyester

    Czech Academy of Sciences Publication Activity Database

    Pergal, M. V.; Džunuzović, J. V.; Špírková, Milena; Poreba, Rafal; Steinhart, Miloš; Pergal, M. M.; Ostojić, S.

    2013-01-01

    Roč. 67, č. 6 (2013), s. 871-879 ISSN 0367-598X R&D Projects: GA ČR GAP108/10/0195 Institutional support: RVO:61389013 Keywords : polyurethane networks * poly(dimethylsiloxane) * hyperbranched polyester Subject RIV: CD - Macromolecular Chemistry Impact factor: 0.562, year: 2013

  10. Local structural properties and attribute characteristisc in 2-mode networks: p* models to map choices of theater events

    NARCIS (Netherlands)

    Agneessens, F.; Roose, H.

    2008-01-01

    Choices of plays made by theatergoers can be considered as a 2-mode or affiliation network. In this article we illustrate how p* models (an exponential family of distributions for random graphs) can be used to uncover patterns of choices. Based on audience research in three theater institutions in

  11. Influence of Landscape Coverage on Measuring Spatial and Length Properties of Rock Fracture Networks: Insights from Numerical Simulation

    Science.gov (United States)

    Cao, Wenzhuo; Lei, Qinghua

    2018-01-01

    Natural fractures are ubiquitous in the Earth's crust and often deeply buried in the subsurface. Due to the difficulty in accessing to their three-dimensional structures, the study of fracture network geometry is usually achieved by sampling two-dimensional (2D) exposures at the Earth's surface through outcrop mapping or aerial photograph techniques. However, the measurement results can be considerably affected by the coverage of forests and other plant species over the exposed fracture patterns. We quantitatively study such effects using numerical simulation. We consider the scenario of nominally isotropic natural fracture systems and represent them using 2D discrete fracture network models governed by fractal and length scaling parameters. The groundcover is modelled as random patches superimposing onto the 2D fracture patterns. The effects of localisation and total coverage of landscape patches are further investigated. The fractal dimension and length exponent of the covered fracture networks are measured and compared with those of the original non-covered patterns. The results show that the measured length exponent increases with the reduced localisation and increased coverage of landscape patches, which is more evident for networks dominated by very large fractures (i.e. small underlying length exponent). However, the landscape coverage seems to have a minor impact on the fractal dimension measurement. The research findings of this paper have important implications for field survey and statistical analysis of geological systems.

  12. A strategy for prediction of the elastic properties of epoxy-cellulose nanocrystal-reinforced fiber networks

    Science.gov (United States)

    Johnathan E. Goodsell; Robert J. Moon; Alionso Huizar; R. Byron Pipes

    2014-01-01

    The reinforcement potential of cellulose nanocrystal (CNC) additions on an idealized 2-dirmensional (2-D) fiber network structure consisting of micron sized fiber elements was investigated. The reinforcement mechanism considered in this study was through the stiffening of the micron sized fiber elements via a CNC-epoxy coating. A hierarchical analytical modeling...

  13. Analysis of dynamic mechanical, thermal and surface properties of poly(urethane-ester-siloxane) networks based on hyperbranched polyester

    Czech Academy of Sciences Publication Activity Database

    Džunuzović, J. V.; Pergal, M. V.; Poreba, Rafal; Vodnik, V. V.; Simonović, B. R.; Špírková, Milena; Jovanović, S.

    2012-01-01

    Roč. 358, č. 23 (2012), s. 3161-3169 ISSN 0022-3093 R&D Projects: GA ČR GAP108/10/0195 Institutional research plan: CEZ:AV0Z40500505 Institutional support: RVO:61389013 Keywords : polyurethane network * hyperbranched polyester * poly(dimethylsiloxane) Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.597, year: 2012

  14. Semi-Interpenetrating polymer network hydrogels based on aspen hemicellulose and chitosan: Effect of crosslinking sequence on hydrogel properties

    Science.gov (United States)

    Muzaffer Ahmet Karaaslan; Mandla A. Tshabalala; Gisela Buschle-Diller

    2012-01-01

    Semi-interpenetrating network hydrogel films were prepared using hemicellulose and chemically crosslinked chitosan. Hemicellulose was extracted from aspen by using a novel alkaline treatment and characterized by HPSEC, and consisted of a mixture of high and low molecular weight polymeric fractions. HPLC analysis of the acid hydrolysate of the hemicellulose showed that...

  15. Analytic device including nanostructures

    KAUST Repository

    Di Fabrizio, Enzo M.; Fratalocchi, Andrea; Totero Gongora, Juan Sebastian; Coluccio, Maria Laura; Candeloro, Patrizio; Cuda, Gianni

    2015-01-01

    A device for detecting an analyte in a sample comprising: an array including a plurality of pixels, each pixel including a nanochain comprising: a first nanostructure, a second nanostructure, and a third nanostructure, wherein size of the first nanostructure is larger than that of the second nanostructure, and size of the second nanostructure is larger than that of the third nanostructure, and wherein the first nanostructure, the second nanostructure, and the third nanostructure are positioned on a substrate such that when the nanochain is excited by an energy, an optical field between the second nanostructure and the third nanostructure is stronger than an optical field between the first nanostructure and the second nanostructure, wherein the array is configured to receive a sample; and a detector arranged to collect spectral data from a plurality of pixels of the array.

  16. Saskatchewan resources. [including uranium

    Energy Technology Data Exchange (ETDEWEB)

    1979-09-01

    The production of chemicals and minerals for the chemical industry in Saskatchewan are featured, with some discussion of resource taxation. The commodities mentioned include potash, fatty amines, uranium, heavy oil, sodium sulfate, chlorine, sodium hydroxide, sodium chlorate and bentonite. Following the successful outcome of the Cluff Lake inquiry, the uranium industry is booming. Some developments and production figures for Gulf Minerals, Amok, Cenex and Eldorado are mentioned.

  17. Multilevel method for modeling large-scale networks.

    Energy Technology Data Exchange (ETDEWEB)

    Safro, I. M. (Mathematics and Computer Science)

    2012-02-24

    Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

  18. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    Science.gov (United States)

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Accelerating networks

    International Nuclear Information System (INIS)

    Smith, David M D; Onnela, Jukka-Pekka; Johnson, Neil F

    2007-01-01

    Evolving out-of-equilibrium networks have been under intense scrutiny recently. In many real-world settings the number of links added per new node is not constant but depends on the time at which the node is introduced in the system. This simple idea gives rise to the concept of accelerating networks, for which we review an existing definition and-after finding it somewhat constrictive-offer a new definition. The new definition provided here views network acceleration as a time dependent property of a given system as opposed to being a property of the specific algorithm applied to grow the network. The definition also covers both unweighted and weighted networks. As time-stamped network data becomes increasingly available, the proposed measures may be easily applied to such empirical datasets. As a simple case study we apply the concepts to study the evolution of three different instances of Wikipedia, namely, those in English, German, and Japanese, and find that the networks undergo different acceleration regimes in their evolution

  20. Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413 Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

    Directory of Open Access Journals (Sweden)

    R. Soundararajan

    2015-01-01

    Full Text Available Artificial Neural Network (ANN approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. The experiments are carried out with different controlled input variables such as squeeze pressure, die preheating temperature, and melt temperature as per Full Factorial Design (FFD. The accounted absolute process variables produce a casting with pore-free and ideal fine grain dendritic structure resulting in good mechanical properties such as hardness, ultimate tensile strength, and yield strength. As a primary objective, a feed forward back propagation ANN model has been developed with different architectures for ensuring the definiteness of the values. The developed model along with its predicted data was in good agreement with the experimental data, inferring the valuable performance of the optimal model. From the work it was ascertained that, for castings produced by squeeze casting route, the ANN is an alternative method for predicting the mechanical properties and appropriate results can be estimated rather than measured, thereby reducing the testing time and cost. As a secondary objective, quantitative and statistical analysis was performed in order to evaluate the effect of process parameters on the mechanical properties of the castings.

  1. Impact of acid and alkaline pretreatments on the molecular network of wheat gluten and on the mechanical properties of compression-molded glassy wheat gluten bioplastics.

    Science.gov (United States)

    Jansens, Koen J A; Lagrain, Bert; Brijs, Kristof; Goderis, Bart; Smet, Mario; Delcour, Jan A

    2013-10-02

    Wheat gluten can be converted into rigid biobased materials by high-temperature compression molding at low moisture contents. During molding, a cross-linked protein network is formed. This study investigated the effect of mixing gluten with acid/alkali in 70% ethanol at ambient temperature for 16 h followed by ethanol removal, freeze-drying, and compression molding at 130 and 150 °C on network formation and on types of cross-links formed. Alkaline pretreatment (0-100 mmol/L sodium hydroxide or 25 mmol/L potassium hydroxide) strongly affected gluten cross-linking, whereas acid pretreatment (0-25 mmol/L sulfuric acid or 25 mmol/L hydrochloric acid) had limited effect on the gluten network. Molded alkaline-treated gluten showed enhanced cross-linking but also degradation when treated with high alkali concentrations, whereas acid treatment reduced gluten cross-linking. β-Elimination of cystine and lanthionine formation occurred more pronouncedly at higher alkali concentrations. In contrast, formation of disulfide and nondisulfide cross-links during molding was hindered in acid-pretreated gluten. Bioplastic strength was higher for alkali than for acid-pretreated samples, whereas the flexural modulus was only slightly affected by either alkaline or acid pretreatment. Apparently, the ratio of disulfide to nondisulfide cross-links did not affect the mechanical properties of rigid gluten materials.