WorldWideScience

Sample records for network properties including

  1. 78 FR 12359 - Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division Including...

    Science.gov (United States)

    2013-02-22

    ... Employment and Training Administration Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division Including Workers in the Core Network Engineering (Deployment Engineering) Division in... of Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division, including...

  2. 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...

  3. 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.

  4. Connecting network properties of rapidly disseminating epizoonotics.

    Directory of Open Access Journals (Sweden)

    Ariel L Rivas

    Full Text Available 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.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.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.Geo-temporal constructs of Network Theory's nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable

  5. Topological properties of hierarchical networks.

    Science.gov (United States)

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

    2015-06-01

    Hierarchical networks are attracting a renewal interest for modeling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the Dyson hierarchical construction for ferromagnets, neural networks, and spin glasses, recently analyzed from a statistical-mechanics perspective, and we focus on the topological properties of the underlying structures. In particular, we find that such structures are weighted graphs that exhibit a high degree of clustering and of modularity, with a small spectral gap; the robustness of such features with respect to the presence of thermal noise is also studied. These outcomes are then discussed and related to the statistical-mechanics scenario in full consistency. Last, we look at these weighted graphs as Markov chains and we show that in the limit of infinite size, the emergence of ergodicity breakdown for the stochastic process mirrors the emergence of metastabilities in the corresponding statistical mechanical analysis.

  6. Topological properties of hierarchical networks

    Science.gov (United States)

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

    2015-06-01

    Hierarchical networks are attracting a renewal interest for modeling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the Dyson hierarchical construction for ferromagnets, neural networks, and spin glasses, recently analyzed from a statistical-mechanics perspective, and we focus on the topological properties of the underlying structures. In particular, we find that such structures are weighted graphs that exhibit a high degree of clustering and of modularity, with a small spectral gap; the robustness of such features with respect to the presence of thermal noise is also studied. These outcomes are then discussed and related to the statistical-mechanics scenario in full consistency. Last, we look at these weighted graphs as Markov chains and we show that in the limit of infinite size, the emergence of ergodicity breakdown for the stochastic process mirrors the emergence of metastabilities in the corresponding statistical mechanical analysis.

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

    OpenAIRE

    Tufan Turaci; Hüseyin Aksan

    2016-01-01

    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...

  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. An architecture including network QoS in scientific workflows

    NARCIS (Netherlands)

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

    2010-01-01

    The quality of the network services has so far rarely been considered in composing and executing scientific workflows. Currently, scientific applications tune the execution quality of workflows neglecting network resources, and by selecting only optimal software services and computing resources. One

  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. 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.

  12. Dynamical Properties of Discrete Reaction Networks

    OpenAIRE

    Paulevé, Loïc; Craciun, Gheorghe; Koeppl, Heinz

    2013-01-01

    International audience; Reaction networks are commonly used to model the evolution of populations of species subject to transformations following an imposed stoichiometry. This paper focuses on the efficient characterisation of dynamical properties of Discrete Reaction Networks (DRNs). DRNs can be seen as modelling the underlying discrete nondeterministic transitions of stochastic models of reactions networks. In that sense, any proof of non-reachability in DRNs directly applies to any concre...

  13. 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.

  14. 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

  15. Viscoelastic properties of microtubule networks

    NARCIS (Netherlands)

    Lin, Y. C.; Koenderink, G.H.; Mac Kintosh, F.C.; Weitz, D. A.

    2007-01-01

    Microtubules are filamentous protein biopolymers found in eukaryotic cells. They form networks that guide active intracellular transport and support the overall cell structure. Microtubules are very rigid polymers, with persistence lengths as large as a millimeter. As such, they constitute an

  16. 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.

  17. 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.

  18. Elastic properties of nonstoichiometric reacted PDMS networks

    DEFF Research Database (Denmark)

    Skov, Anne Ladegaard; Hansen, Kristoffer Karsten; Sommer-Larsen, Peter

    2003-01-01

    The influence of stoichiometry on the elastic modulus of eight-functional end-linked poly(dimethylsiloxane) (PDMS) networks was investigated by extensional rheometry with extensions up to more than 100%, and the stress-strain relation was found to be almost linear-a characteristic property...

  19. 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.

  20. Electronic Properties of Quantum Wire Networks

    OpenAIRE

    Kuzmenko, Igor

    2005-01-01

    Quantum wire networks (``quantum crossbars'', QCB) represent a 2D grid formed by superimposed crossing arrays of parallel conducting quantum wires, molecular chains or metallic single-wall carbon nanotubes. QCB coupled only by capacitive interaction in the crosses have similar low-energy, long-wave properties characterized as a crossed sliding Luttinger liquid (CSLL) phase. In this Thesis we develop a theory of interacting Bose excitations (plasmons) in QCB. We analyze spectrum of boson field...

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

    CERN Document Server

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

    2014-01-01

    The complexity and heterogeneity of bone tissue require a multiscale modelling to understand its mechanical behaviour and its remodelling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network computation and homogenisation 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 neural network simulation. Finite element (FE) calculation is performed at nanoscopic levels to provide a database to train an in-house neural network program; (iii) in steps 2 to 10 from fibril to continuum cortical bone tissue, homogenisation equations are used to perform the computation at the higher s...

  2. National Materials Property Data Network: standardization for materials-property data bases and networking

    Energy Technology Data Exchange (ETDEWEB)

    Kaufman, J.G.

    1986-02-01

    There are a number of hurdles to developing the National Materials Property Data Network (MPD Network), which will provide ready on-line access to computerized numeric research and engineering data on materials properties. The author reviews several studies carried out by the ASTM Society and others aimed at developing standards for developing sophisticated network software. He describes the need for standards of material designations, test methods, and data presentation, as well as ASTM's role in the process. ASTM intends to reinforce its position of having the highest caliber products in the field by becoming the leader in standards for materials property data base building and management. 29 references, 1 table.

  3. 76 FR 23812 - Reliability and Continuity of Communications Networks, Including Broadband Technologies; Effects...

    Science.gov (United States)

    2011-04-28

    ... they begin to deploy Smart Grid. Hospitals and healthcare providers can leverage broadband technologies... COMMISSION Reliability and Continuity of Communications Networks, Including Broadband Technologies; Effects... broadband technologies. 4. Today's increasingly interconnected world is one in which communications services...

  4. The emergent properties of a dolphin social network.

    Science.gov (United States)

    Lusseau, David

    2003-11-07

    Many complex networks, including human societies, the Internet, the World Wide Web and power grids, have surprising properties that allow vertices (individuals, nodes, Web pages, etc.) to be in close contact and information to be transferred quickly between them. Nothing is known of the emerging properties of animal societies, but it would be expected that similar trends would emerge from the topology of animal social networks. Despite its small size (64 individuals), the Doubtful Sound community of bottlenose dolphins has the same characteristics. The connectivity of individuals follows a complex distribution that has a scale-free power-law distribution for large k. In addition, the ability for two individuals to be in contact is unaffected by the random removal of individuals. The removal of individuals with many links to others does affect the length of the 'information' path between two individuals, but, unlike other scale-free networks, it does not fragment the cohesion of the social network. These self-organizing phenomena allow the network to remain united, even in the case of catastrophic death events.

  5. Conjugated electrical properties of Au nanoparticle–polyaniline network

    Science.gov (United States)

    Usami, Yuki; Otsuka, Yoichi; Naitoh, Yasuhisa; Matsumoto, Takuya

    2017-12-01

    We investigated the electrical properties of a two-dimensional (2D) network consisting of multiple Au nanoparticles (AuNPs) and self-doped polyaniline sulfonate (SPAN). Nonlinear current–voltage (I–V) characteristics with wide variations were observed in the networks. The temperature dependence of the I–V characteristics exhibited a short localization length, suggesting conjugated electronic properties of the AuNP–SPAN network. This result provides a new direction for network-based molecular electronic devices.

  6. 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.

  7. 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.

  8. Gastroduodenal neuroendocrine neoplasms, including gastrinoma - management guidelines (recommended by the Polish Network of Neuroendocrine Tumours).

    Science.gov (United States)

    Lipiński, Michał; Rydzewska, Grażyna; Foltyn, Wanda; Andrysiak-Mamos, Elżbieta; Bałdys-Waligórska, Agata; Bednarczuk, Tomasz; Blicharz-Dorniak, Jolanta; Bolanowski, Marek; Boratyn-Nowicka, Agnieszka; Borowska, Małgorzata; Cichocki, Andrzej; Ćwikła, Jarosław B; Falconi, Massimo; Handkiewicz-Junak, Daria; Hubalewska-Dydejczyk, Alicja; Jarząb, Barbara; Junik, Roman; Kajdaniuk, Dariusz; Kamiński, Grzegorz; Kolasińska-Ćwikła, Agnieszka; Kowalska, Aldona; Król, Robert; Królicki, Leszek; Kunikowska, Jolanta; Kuśnierz, Katarzyna; Lampe, Paweł; Lange, Dariusz; Lewczuk-Myślicka, Anna; Lewiński, Andrzej; Londzin-Olesik, Magdalena; Marek, Bogdan; Nasierowska-Guttmejer, Anna; Nowakowska-Duława, Ewa; Pilch-Kowalczyk, Joanna; Poczkaj, Karolina; Rosiek, Violetta; Ruchała, Marek; Siemińska, Lucyna; Sowa-Staszczak, Anna; Starzyńska, Teresa; Steinhof-Radwańska, Katarzyna; Strzelczyk, Janusz; Sworczak, Krzysztof; Syrenicz, Anhelli; Szawłowski, Andrzej; Szczepkowski, Marek; Wachuła, Ewa; Zajęcki, Wojciech; Zemczak, Anna; Zgliczyński, Wojciech; Kos-Kudła, Beata

    2017-01-01

    This paper presents the updated Polish Neuroendocrine Tumour Network expert panel recommendations on the management of neuroendocrine neoplasms (NENs) of the stomach and duodenum, including gastrinoma. The recommendations discuss the epidemiology, pathogenesis, and clinical presentation of these tumours as well as their diagnosis, including biochemical, histopathological, and localisation diagnoses. The principles of treatment are discussed, including endoscopic, surgical, pharmacological, and radionuclide treatments. Finally, there are also recommendations on patient monitoring.

  9. Netter: re-ranking gene network inference predictions using structural network properties.

    Science.gov (United States)

    Ruyssinck, Joeri; Demeester, Piet; Dhaene, Tom; Saeys, Yvan

    2016-02-09

    Many algorithms have been developed to infer the topology of gene regulatory networks from gene expression data. These methods typically produce a ranking of links between genes with associated confidence scores, after which a certain threshold is chosen to produce the inferred topology. However, the structural properties of the predicted network do not resemble those typical for a gene regulatory network, as most algorithms only take into account connections found in the data and do not include known graph properties in their inference process. This lowers the prediction accuracy of these methods, limiting their usability in practice. We propose a post-processing algorithm which is applicable to any confidence ranking of regulatory interactions obtained from a network inference method which can use, inter alia, graphlets and several graph-invariant properties to re-rank the links into a more accurate prediction. To demonstrate the potential of our approach, we re-rank predictions of six different state-of-the-art algorithms using three simple network properties as optimization criteria and show that Netter can improve the predictions made on both artificially generated data as well as the DREAM4 and DREAM5 benchmarks. Additionally, the DREAM5 E.coli. community prediction inferred from real expression data is further improved. Furthermore, Netter compares favorably to other post-processing algorithms and is not restricted to correlation-like predictions. Lastly, we demonstrate that the performance increase is robust for a wide range of parameter settings. Netter is available at http://bioinformatics.intec.ugent.be. Network inference from high-throughput data is a long-standing challenge. In this work, we present Netter, which can further refine network predictions based on a set of user-defined graph properties. Netter is a flexible system which can be applied in unison with any method producing a ranking from omics data. It can be tailored to specific prior

  10. 78 FR 1252 - CalAmp Wireless Networks Corporation (CWNC), Satellite Products Division, Including On-Site...

    Science.gov (United States)

    2013-01-08

    ... Employment and Training Administration CalAmp Wireless Networks Corporation (CWNC), Satellite Products Division, Including On-Site Leased Workers From Select Staffing, Oxnard, CA; CalAmp Wireless Networks... Networks Corporation (CWNC), and that the manufacturing of wireless networking products was transferred...

  11. Scaling in topological properties of brain networks

    NARCIS (Netherlands)

    Singh, S.S.; Khundrakpam, B.S.; Reid, A.T.; Lewis, J.D.; Evans, A.C.; Ishrat, R.; Sharma, B.I.; Singh, R.K.B.

    2016-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks.

  12. Dynamic properties of cellular neural networks

    Directory of Open Access Journals (Sweden)

    Angela Slavova

    1993-01-01

    Full Text Available Dynamic behavior of a new class of information-processing systems called Cellular Neural Networks is investigated. In this paper we introduce a small parameter in the state equation of a cellular neural network and we seek for periodic phenomena. New approach is used for proving stability of a cellular neural network by constructing Lyapunov's majorizing equations. This algorithm is helpful for finding a map from initial continuous state space of a cellular neural network into discrete output. A comparison between cellular neural networks and cellular automata is made.

  13. Expanding the DOCLINE network to include nonmedical libraries in the state of Nevada.

    OpenAIRE

    Potter, L A; Zenan, J S

    1993-01-01

    Most libraries cannot meet patron demands for biomedical information using only their in-house collections. Consequently, many types of libraries request biomedical information through interlibrary loan, and these include not only academic health sciences libraries, hospital and special libraries, but also general libraries. In Nevada, with its small population spread over a large geographic area, it has become critical to develop a statewide network for sharing biomedical information. As the...

  14. 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...... it was possible to obtain rheological data from the washed network without interference from the sol fraction, and furthermore from the sol fraction without interference from the elastic washed network. When the stoichiometry increased towards perfectly reacted networks and beyond we observed harder networks both...... qualitatively and by rheology and the properties of the two fractions became more and more different. At the gel point, the sol fraction and the washed network have more or less identical properties which our data also shows. The storage and loss moduli, G′ and G′′, were analysed with the gel equation...

  15. Research on Intellectual Property Right Problems of Peer-to-Peer Networks.

    Science.gov (United States)

    Dong, Ying; Li, Mingshu; Chen, Meizhang; Zheng, Shengli

    2002-01-01

    Discusses digital intellectual property rights relating to peer-to-peer networks, using Napster as an example. Suggests anti-piracy solutions to prevent litigation and considers how libraries can develop potential service models using peer-to-peer networks, including the development of personal libraries on the Internet, interlibrary loan,…

  16. How Network Properties Affect One's Ability to Obtain Benefits: A Network Simulation

    Science.gov (United States)

    Trefalt, Špela

    2014-01-01

    Networks and the social capital that they carry enable people to get things done, to prosper in their careers, and to feel supported. To develop an effective network, one needs to know more than how to make connections with strangers at a reception; understanding the consequences of network properties on one's ability to obtain benefits is…

  17. Expanding the DOCLINE network to include nonmedical libraries in the state of Nevada.

    Science.gov (United States)

    Potter, L A; Zenan, J S

    1993-01-01

    Most libraries cannot meet patron demands for biomedical information using only their in-house collections. Consequently, many types of libraries request biomedical information through interlibrary loan, and these include not only academic health sciences libraries, hospital and special libraries, but also general libraries. In Nevada, with its small population spread over a large geographic area, it has become critical to develop a statewide network for sharing biomedical information. As the state resource library, the Savitt Medical Library launched an effort to establish a network, via DOCLINE, of all Nevada libraries that have health-related collections. The process of convincing academic and community college libraries to join DOCLINE and the resulting benefits of improved resource sharing and cooperative collection development are discussed.

  18. 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 ...

  19. 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.

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

    Science.gov (United States)

    Zand, Martin S; Trayhan, Melissa; Farooq, Samir A; Fucile, Christopher; Ghoshal, Gourab; White, Robert J; Quill, Caroline M; Rosenberg, Alexander; Barbosa, Hugo Serrano; Bush, Kristen; Chafi, Hassan; Boudreau, Timothy

    2017-01-01

    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 United States and

  1. Topological properties of four networks in protein structures

    Science.gov (United States)

    Min, Seungsik; Kim, Kyungsik; Chang, Ki-Ho; Ha, Deok-Ho; Lee, Jun-Ho

    2017-11-01

    In this paper, we investigate the complex networks of interacting amino acids in protein structures. The cellular networks and their random controls are treated for the four threshold distances between atoms. The numerical simulation and analysis are relevant to the topological properties of the complex networks in the structural classification of proteins, and we mainly estimate the network's metrics from the resultant network. The cellular network is shown to exhibit a small-world feature regardless of their structural class. The protein structure presents the positive assortative coefficients, when the topological property is described as a tendency for connectivity of high-degree nodes. We particularly show that both the modularity and the small-wordness are significantly followed the increasing function against nodes.

  2. Improved exponential convergence result for generalized neural networks including interval time-varying delayed signals.

    Science.gov (United States)

    Rajchakit, G; Saravanakumar, R; Ahn, Choon Ki; Karimi, Hamid Reza

    2017-02-01

    This article examines the exponential stability analysis problem of generalized neural networks (GNNs) including interval time-varying delayed states. A new improved exponential stability criterion is presented by establishing a proper Lyapunov-Krasovskii functional (LKF) and employing new analysis theory. The improved reciprocally convex combination (RCC) and weighted integral inequality (WII) techniques are utilized to obtain new sufficient conditions to ascertain the exponential stability result of such delayed GNNs. The superiority of the obtained results is clearly demonstrated by numerical examples. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Properties of Fibrillar Protein Assemblies and their Percolating Networks

    NARCIS (Netherlands)

    Veerman, C.

    2004-01-01

    Properties of Fibrillar Protein Assemblies and their Percolating Networks. PhD thesis, Wageningen University, The Netherlands Keywords: bovine serum albumin, complex fluids, excluded volume, fibrils, gels, innovation, b-lactoglobulin, ovalbumin, percolation, proteins, rheology, rheo-optics,

  4. 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.

  5. Generalisation of action sequences in RNNPB networks with mirror properties

    OpenAIRE

    Cuijpers, R.H.; Stuijt, F.H.A.; Sprinkhuizen-Kuyper, I.G.

    2009-01-01

    The human mirror neuron system (MNS) is supposed to be involved in recognition of observed action sequences. However, it remains unclear how such a system could learn to recognise a large variety of action sequences. Here we investigated a neural network with mirror properties, the Recurrent Neural Network with Parametric Bias (RNNPB). We show that the network is capable of recognising noisy action sequences and that it is capable of generalising from a few learnt examples. Such a mechanism m...

  6. Integration of network topological and connectivity properties for neuroimaging classification.

    Science.gov (United States)

    Jie, Biao; Zhang, Daoqiang; Gao, Wei; Wang, Qian; Wee, Chong-Yaw; Shen, Dinggang

    2014-02-01

    Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results.

  7. Imaging spatially varying biomechanical properties with neural networks

    Science.gov (United States)

    Hoerig, Cameron; Reyes, Wendy; Fabre, Léo.; Ghaboussi, Jamshid; Insana, Michael F.

    2017-03-01

    Elastography comprises a set of modalities that image the biomechanical properties of soft tissues for disease detection and diagnosis. Quasi-static ultrasound elastography, in particular, tracks sub-surface displacements resulting from an applied surface force. The local displacement information and measured surface loads may be used to compute a parametric summary of biomechanical properties; however, the inverse problem is under- determined, limiting most techniques to estimating a single linear-elastic parameter. We previously described a new method to develop mechanical models using a combination of computational mechanics and machine learning that circumvents the limitations associated with the inverse problem. The Autoprogressive method weaves together finite element analysis and artificial neural networks (ANNs) to develop empirical models of mechanical behavior using only measured force-displacement data. We are extending that work by incorporating spatial information with the material properties. Previously, the ANNs accepted only a strain vector input and computed the corresponding stress, meaning any spatial information was encoded in the finite element mesh. Now, using a pair of ANNs working in tandem with spatial coordinates included as part of the input, these new Cartesian ANNs are able to learn the spatially varying mechanical behavior of complex media. We show that a single Cartesian ANN is able to describe the same mechanical behavior of an object that previously required at least two ANNs. Furthermore, we show the new ANNs can learn complex material property distributions and reconstruct images of the Young's modulus distribution, not merely classify, filter, or otherwise process an existing image. For the first time, we present results using Cartesian neural networks within the Autoprogressive Method to form elastic modulus images.

  8. Structure and properties of triolein-based polyurethane networks.

    Science.gov (United States)

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

    2002-01-01

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

  9. Implementation of neural network for color properties of polycarbonates

    Science.gov (United States)

    Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

    2014-05-01

    In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

  10. Vehicular networking: from fundamental properties to network solutions

    OpenAIRE

    Fiore, Marco

    2014-01-01

    Vehicular communications are regarded as a key technology within upcoming Intelligent Transportation Systems (ITS), which are expected to improve road safety and traffic management, as well as to enhance the comfort of on-board drivers and passengers. In this manuscript, we will first discuss the need for realistic representations of road traffic dynamics in studies concerning vehicular communications, and show their impact on dedicated (infrastructure-based and spontaneous) network solutions...

  11. Topological properties of random wireless networks

    Indian Academy of Sciences (India)

    indicating that a physical infrastructure needs to be put in place before nodes can communicate. Ad hoc and sensor ... edges, the communication paths of the wireless network can be represented by a graph. The representation of the ..... Pr (Gn ∈ P) → 1. Another definition of a threshold is from Friedgut & Kalal (1996). For a.

  12. Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency.

    Science.gov (United States)

    Baek, K; Morris, L S; Kundu, P; Voon, V

    2017-03-01

    The efficient organization and communication of brain networks underlie cognitive processing and their disruption can lead to pathological behaviours. Few studies have focused on whole-brain networks in obesity and binge eating disorder (BED). Here we used multi-echo resting-state functional magnetic resonance imaging (rsfMRI) along with a data-driven graph theory approach to assess brain network characteristics in obesity and BED. Multi-echo rsfMRI scans were collected from 40 obese subjects (including 20 BED patients) and 40 healthy controls and denoised using multi-echo independent component analysis (ME-ICA). We constructed a whole-brain functional connectivity matrix with normalized correlation coefficients between regional mean blood oxygenation level-dependent (BOLD) signals from 90 brain regions in the Automated Anatomical Labeling atlas. We computed global and regional network properties in the binarized connectivity matrices with an edge density of 5%-25%. We also verified our findings using a separate parcellation, the Harvard-Oxford atlas parcellated into 470 regions. Obese subjects exhibited significantly reduced global and local network efficiency as well as decreased modularity compared with healthy controls, showing disruption in small-world and modular network structures. In regional metrics, the putamen, pallidum and thalamus exhibited significantly decreased nodal degree and efficiency in obese subjects. Obese subjects also showed decreased connectivity of cortico-striatal/cortico-thalamic networks associated with putaminal and cortical motor regions. These findings were significant with ME-ICA with limited group differences observed with conventional denoising or single-echo analysis. Using this data-driven analysis of multi-echo rsfMRI data, we found disruption in global network properties and motor cortico-striatal networks in obesity consistent with habit formation theories. Our findings highlight the role of network properties in

  13. The intellectual property management for data sharing in a German liver cancer research network.

    Science.gov (United States)

    He, Shan; Ganzinger, Matthias; Knaup, Petra

    2012-01-01

    Sharing data in biomedical research networks has great potential benefits including efficient use of resources, avoiding duplicate experiments and promoting collaboration. However, concerns from data producers about difficulties of getting proper acknowledgement for their contributions are becoming obstacles for efficient and network wide data sharing in reality. Effective and convenient ways of intellectual property management and acknowledging contributions to the data producers are required. This paper analyzed the system requirements for intellectual property management in a German liver cancer research network and proposed solutions for facilitating acknowledgement of data contributors using informatics tools instead of pure policy level strategies.

  14. Spectral properties of attractive bosons in a ring lattice including a single-site potential

    Science.gov (United States)

    Cavaletto, S. M.; Penna, V.

    2011-06-01

    The ground-state properties of attractive bosons trapped in a ring lattice including a single attractive potential well with an adjustable depth are investigated. The energy spectrum is reconstructed both in the strong-interaction limit and in the superfluid regime within the Bogoliubov picture. The analytical results thus obtained are compared with those found numerically from the exact Hamiltonian, in order to identify the regions in the parameter space where this picture is effective. The single potential introduced is the simplest way to break the translational symmetry and to observe, through a completely analytical approach, how the absence of symmetry affects the properties of the low-excited eigenstates of the system. This model gives a first insight into the properties of systems including more complex potentials.

  15. Structural properties of the Caenorhabditis elegans neuronal network.

    Directory of Open Access Journals (Sweden)

    Lav R Varshney

    2011-02-01

    Full Text Available Despite recent interest in reconstructing neuronal networks, complete wiring diagrams on the level of individual synapses remain scarce and the insights into function they can provide remain unclear. Even for Caenorhabditis elegans, whose neuronal network is relatively small and stereotypical from animal to animal, published wiring diagrams are neither accurate nor complete and self-consistent. Using materials from White et al. and new electron micrographs we assemble whole, self-consistent gap junction and chemical synapse networks of hermaphrodite C. elegans. We propose a method to visualize the wiring diagram, which reflects network signal flow. We calculate statistical and topological properties of the network, such as degree distributions, synaptic multiplicities, and small-world properties, that help in understanding network signal propagation. We identify neurons that may play central roles in information processing, and network motifs that could serve as functional modules of the network. We explore propagation of neuronal activity in response to sensory or artificial stimulation using linear systems theory and find several activity patterns that could serve as substrates of previously described behaviors. Finally, we analyze the interaction between the gap junction and the chemical synapse networks. Since several statistical properties of the C. elegans network, such as multiplicity and motif distributions are similar to those found in mammalian neocortex, they likely point to general principles of neuronal networks. The wiring diagram reported here can help in understanding the mechanistic basis of behavior by generating predictions about future experiments involving genetic perturbations, laser ablations, or monitoring propagation of neuronal activity in response to stimulation.

  16. A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

    Science.gov (United States)

    Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

    2017-04-01

    Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

  17. A speech recognition system based on hybrid wavelet network including a fuzzy decision support system

    Science.gov (United States)

    Jemai, Olfa; Ejbali, Ridha; Zaied, Mourad; Ben Amar, Chokri

    2015-02-01

    This paper aims at developing a novel approach for speech recognition based on wavelet network learnt by fast wavelet transform (FWN) including a fuzzy decision support system (FDSS). Our contributions reside in, first, proposing a novel learning algorithm for speech recognition based on the fast wavelet transform (FWT) which has many advantages compared to other algorithms and in which major problems of the previous works to compute connection weights were solved. They were determined by a direct solution which requires computing matrix inversion, which may be intensive. However, the new algorithm was realized by the iterative application of FWT to compute connection weights. Second, proposing a new classification way for this speech recognition system. It operated a human reasoning mode employing a FDSS to compute similarity degrees between test and training signals. Extensive empirical experiments were conducted to compare the proposed approach with other approaches. Obtained results show that the new speech recognition system has a better performance than previously established ones.

  18. Prediction of macroscopic properties of elastomeric networks

    Energy Technology Data Exchange (ETDEWEB)

    Al-ghamdi, A.M.S.; Rayes, T.B.; Galiatsatos, V. [Univ. of Akron, OH (United States)

    1993-12-31

    Monte Carlo simulations of amorphous elastomeric networks of polyisoprene and polybutadiene cured with sulfur have been prepared. The effect of molecular weight of the prepolymer, and the concentration and type of cross-links is studied. The affine modulus as a function of the extent of reaction is reported. Comparisons between the two polymers and reasons for their differing behavior are being attributed to their molecular characteristics.

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

    Science.gov (United States)

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

    2014-06-01

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

  20. Synchronization properties of heterogeneous neuronal networks with mixed excitability type.

    Science.gov (United States)

    Leone, Michael J; Schurter, Brandon N; Letson, Benjamin; Booth, Victoria; Zochowski, Michal; Fink, Christian G

    2015-03-01

    We study the synchronization of neuronal networks with dynamical heterogeneity, showing that network structures with the same propensity for synchronization (as quantified by master stability function analysis) may develop dramatically different synchronization properties when heterogeneity is introduced with respect to neuronal excitability type. Specifically, we investigate networks composed of neurons with different types of phase response curves (PRCs), which characterize how oscillating neurons respond to excitatory perturbations. Neurons exhibiting type 1 PRC respond exclusively with phase advances, while neurons exhibiting type 2 PRC respond with either phase delays or phase advances, depending on when the perturbation occurs. We find that Watts-Strogatz small world networks transition to synchronization gradually as the proportion of type 2 neurons increases, whereas scale-free networks may transition gradually or rapidly, depending upon local correlations between node degree and excitability type. Random placement of type 2 neurons results in gradual transition to synchronization, whereas placement of type 2 neurons as hubs leads to a much more rapid transition, showing that type 2 hub cells easily "hijack" neuronal networks to synchronization. These results underscore the fact that the degree of synchronization observed in neuronal networks is determined by a complex interplay between network structure and the dynamical properties of individual neurons, indicating that efforts to recover structural connectivity from dynamical correlations must in general take both factors into account.

  1. Digital 3D reconstructions using histological serial sections of lung tissue including the alveolar capillary network.

    Science.gov (United States)

    Grothausmann, Roman; Knudsen, Lars; Ochs, Matthias; Mühlfeld, Christian

    2017-02-01

    Grothausmann R, Knudsen L, Ochs M, Mühlfeld C. Digital 3D reconstructions using histological serial sections of lung tissue including the alveolar capillary network. Am J Physiol Lung Cell Mol Physiol 312: L243-L257, 2017. First published December 2, 2016; doi:10.1152/ajplung.00326.2016-The alveolar capillary network (ACN) provides an enormously large surface area that is necessary for pulmonary gas exchange. Changes of the ACN during normal or pathological development or in pulmonary diseases are of great functional impact and warrant further analysis. Due to the complexity of the three-dimensional (3D) architecture of the ACN, 2D approaches are limited in providing a comprehensive impression of the characteristics of the normal ACN or the nature of its alterations. Stereological methods offer a quantitative way to assess the ACN in 3D in terms of capillary volume, surface area, or number but lack a 3D visualization to interpret the data. Hence, the necessity to visualize the ACN in 3D and to correlate this with data from the same set of data arises. Such an approach requires a large sample volume combined with a high resolution. Here, we present a technically simple and cost-efficient approach to create 3D representations of lung tissue ranging from bronchioles over alveolar ducts and alveoli up to the ACN from more than 1 mm sample extent to a resolution of less than 1 μm. The method is based on automated image acquisition of serially sectioned epoxy resin-embedded lung tissue fixed by vascular perfusion and subsequent automated digital reconstruction and analysis of the 3D data. This efficient method may help to better understand mechanisms of vascular development and pathology of the lung. Copyright © 2017 the American Physiological Society.

  2. Calcium Phosphate Bone Cements Including Sugar Surfactants: Part Two—Injectability, Adhesive Properties and Biocompatibility

    Directory of Open Access Journals (Sweden)

    Fabienne Briand-Mesange

    2010-12-01

    Full Text Available Addition of sugar surfactants, sucrose fatty acid esters and alkylpolyglucosides to a calcium phosphate cement, designed for bone reconstruction, is described. Thanks to their adsorption at the surface of the calcium phosphate particles, the sugar surfactants allowed a full injectability and brought a very good workability. Injectability was measured by monitoring force-distance curves. With some of the selected sugar surfactants adhesive properties of the cement pastes were also observed, which were measured by tack tests. Finally, some properties related to biological applications are described, including gentamicine release and osteoblast viability experiments. The whole study demonstrates that addition of these mild surfactants improved several properties of the calcium phosphate cement, without impairing function.

  3. Calcium Phosphate Bone Cements Including Sugar Surfactants: Part Two-Injectability, Adhesive Properties and Biocompatibility.

    Science.gov (United States)

    Bercier, Ariane; Gonçalves, Stéphane; Autefage, Helène; Briand-Mesange, Fabienne; Lignon, Olivier; Fitremann, Juliette

    2010-12-02

    Addition of sugar surfactants, sucrose fatty acid esters and alkylpolyglucosides to a calcium phosphate cement, designed for bone reconstruction, is described. Thanks to their adsorption at the surface of the calcium phosphate particles, the sugar surfactants allowed a full injectability and brought a very good workability. Injectability was measured by monitoring force-distance curves. With some of the selected sugar surfactants adhesive properties of the cement pastes were also observed, which were measured by tack tests. Finally, some properties related to biological applications are described, including gentamicine release and osteoblast viability experiments. The whole study demonstrates that addition of these mild surfactants improved several properties of the calcium phosphate cement, without impairing function.

  4. A finite element technique for non-deterministic thermal deformation analyses including temperature dependent material properties

    Science.gov (United States)

    Case, W. R., Jr.; Walston, W. H., Jr.

    1977-01-01

    A technique utilizing the finite element displacement method is developed for the static analysis of structures subjected to non-deterministic thermal loading in which the material properties, assumed isotropic, are temperature dependent. Matrix equations are developed for the first two statistical moments of the displacements using a third order series expansion for the displacements in terms of the random temperatures. Sample problems are included to demonstrate the range of applicability of the third order series solutions. These solutions are compared with results from Monte Carlo analyses and also, for some problems, with solutions obtained by numerically integrating equations for the statistical properties of the displacements. In general, it is shown that the effect of temperature dependent material properties can have a significant effect on the covariances of the displacements.

  5. Proposing an Integrative Approach for Efficiency Evaluation of Network Structures Including Tour and Allocation Link

    Directory of Open Access Journals (Sweden)

    reza hejazi

    2012-02-01

    Full Text Available Data envelopment analysis (DEA is known as one of the most common approaches for efficiency evaluation. Network models are new subjects in which, a DMU with all its subunits and links is considered as a network structure. One of the most widely used DEA methods for network data is the suggested approach of Lewis and Sexton. In this approach, performance of each DMU is measured compared to a similar DMU by moving on the effective paths and then computing the final outputs and classic primary inputs . In reality, many cases can be found that an original input or an intermediate product allocates to several subunits or forms a tour in a network. In such networks, the approach of Lewis and Sexton is not able to calculate efficiency. Therefore, in this paper, an approach has been proposed for solving such problems and computing the efficiency of such networks.

  6. The Italian Interbank Network: statistical properties and a simple model

    Science.gov (United States)

    De Masi, G.; Iori, G.; Caldarelli, G.

    2007-06-01

    We use the theory of complex networks in order to quantitatively characterize the structure of reciprocal expositions of Italian banks in the interbank money market market. We observe two main different strategies of banks: small banks tend to be the lender of the system, while large banks are borrowers. We propose a model to reproduce the main statistical features of this market. Moreover the network analysis allows us to investigate properties of robustness of this system.

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

    Science.gov (United States)

    Trayhan, Melissa; Farooq, Samir A.; Fucile, Christopher; Ghoshal, Gourab; White, Robert J.; Quill, Caroline M.; Rosenberg, Alexander; Barbosa, Hugo Serrano; Bush, Kristen; Chafi, Hassan; Boudreau, Timothy

    2017-01-01

    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 United States and

  8. Community structure from spectral properties in complex networks

    Science.gov (United States)

    Servedio, V. D. P.; Colaiori, F.; Capocci, A.; Caldarelli, G.

    2005-06-01

    We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.

  9. Acoustical properties of nonwoven fiber network structures

    Science.gov (United States)

    Tascan, Mevlut

    Sound insulation is one of the most important issues for the automotive and building industries. Because they are porous fibrous structures, textile materials can be used as sound insulating and sound absorbing materials. Very high-density materials such as steel can insulate sound very effectively but these rigid materials reflect most of the sound back to the environment, causing sound pollution. Additionally, because high-density, rigid materials are also heavy and high cost, they cannot be used for sound insulation for the automotive and building industries. Nonwoven materials are more suitable for these industries, and they can also absorb sound in order to decrease sound pollution in the environment. Therefore, nonwoven materials are one of the most important materials for sound insulation and absorption applications materials. Insulation and absorption properties of nonwoven fabrics depend on fiber geometry and fiber arrangement within the fabric structure. Because of their complex structure, it is very difficult to define the microstructure of nonwovens. The structure of nonwovens only has fibers and voids that are filled by air. Because of the complexity of fiber-void geometry, there is still not a very accurate theory or model that defines the structural arrangement. A considerable amount of modeling has been reported in literature [1--19], but most models are not accurate due to the assumptions made. Voids that are covered by fibers are called pores in nonwoven structures and their geometry is very important, especially for the absorption properties of nonwovens. In order to define the sound absorption properties of nonwoven fabrics, individual pore structure and the number of pores per unit thickness of the fabric should be determined. In this research, instead of trying to define pores, the properties of the fibers are investigated and the number of fibers per volume of fabric is taken as a parameter in the theory. Then the effect of the nonwoven

  10. Refrigerant Performance Evaluation Including Effects of Transport Properties and Optimized Heat Exchangers.

    Science.gov (United States)

    Brignoli, Riccardo; Brown, J Steven; Skye, H; Domanski, Piotr A

    2017-08-01

    Preliminary refrigerant screenings typically rely on using cycle simulation models involving thermodynamic properties alone. This approach has two shortcomings. First, it neglects transport properties, whose influence on system performance is particularly strong through their impact on the performance of the heat exchangers. Second, the refrigerant temperatures in the evaporator and condenser are specified as input, while real-life equipment operates at imposed heat sink and heat source temperatures; the temperatures in the evaporator and condensers are established based on overall heat transfer resistances of these heat exchangers and the balance of the system. The paper discusses a simulation methodology and model that addresses the above shortcomings. This model simulates the thermodynamic cycle operating at specified heat sink and heat source temperature profiles, and includes the ability to account for the effects of thermophysical properties and refrigerant mass flux on refrigerant heat transfer and pressure drop in the air-to-refrigerant evaporator and condenser. Additionally, the model can optimize the refrigerant mass flux in the heat exchangers to maximize the Coefficient of Performance. The new model is validated with experimental data and its predictions are contrasted to those of a model based on thermodynamic properties alone.

  11. 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

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

    Science.gov (United States)

    Criscuoli, Serena; Norton, Aimee; Whitney, Taylor

    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.

  13. 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.

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

    African Journals Online (AJOL)

    The prediction of multiphase transport properties of reservoir rocks has been undertaken. This was done by numerical flow simulation of relative permeability and capillary pressure curves from pore network models extracted from Pore Architecture Models (PAMs). These PAMs are three-dimensional images obtained from ...

  15. Generalisation of action sequences in RNNPB networks with mirror properties

    NARCIS (Netherlands)

    Cuijpers, R.H.; Stuijt, F.H.A.; Sprinkhuizen-Kuyper, I.G.

    2009-01-01

    The human mirror neuron system (MNS) is supposed to be involved in recognition of observed action sequences. However, it remains unclear how such a system could learn to recognise a large variety of action sequences. Here we investigated a neural network with mirror properties, the Recurrent Neural

  16. The predictive power of local properties of financial networks

    Science.gov (United States)

    Caraiani, Petre

    2017-01-01

    The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

  17. Task-related changes in functional properties of the human brain network underlying attentional control.

    Directory of Open Access Journals (Sweden)

    Tetsuo Kida

    Full Text Available Previous studies have demonstrated task-related changes in brain activation and inter-regional connectivity but the temporal dynamics of functional properties of the brain during task execution is still unclear. In the present study, we investigated task-related changes in functional properties of the human brain network by applying graph-theoretical analysis to magnetoencephalography (MEG. Subjects performed a cue-target attention task in which a visual cue informed them of the direction of focus for incoming auditory or tactile target stimuli, but not the sensory modality. We analyzed the MEG signal in the cue-target interval to examine network properties during attentional control. Cluster-based non-parametric permutation tests with the Monte-Carlo method showed that in the cue-target interval, beta activity was desynchronized in the sensori-motor region including premotor and posterior parietal regions in the hemisphere contralateral to the attended side. Graph-theoretical analysis revealed that, in beta frequency, global hubs were found around the sensori-motor and prefrontal regions, and functional segregation over the entire network was decreased during attentional control compared to the baseline. Thus, network measures revealed task-related temporal changes in functional properties of the human brain network, leading to the understanding of how the brain dynamically responds to task execution as a network.

  18. 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.

  19. 41 CFR 102-38.140 - What must we include in the public notice on sale of personal property?

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What must we include in the public notice on sale of personal property? 102-38.140 Section 102-38.140 Public Contracts and Property Management Federal Property Management Regulations System (Continued) FEDERAL MANAGEMENT...

  20. 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.

  1. Estimating topological properties of weighted networks from limited information

    Science.gov (United States)

    Gabrielli, Andrea; Cimini, Giulio; Garlaschelli, Diego; Squartini, Angelo

    A typical problem met when studying complex systems is the limited information available on their topology, which hinders our understanding of their structural and dynamical properties. A paramount example is provided by financial networks, whose data are privacy protected. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here we develop a reconstruction method, based on statistical mechanics concepts, that exploits the empirical link density in a highly non-trivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems. Acknoweledgement to ``Growthcom'' ICT - EC project (Grant No: 611272) and ``Crisislab'' Italian Project.

  2. 78 FR 21879 - Improving 9-1-1 Reliability; Reliability and Continuity of Communications Networks, Including...

    Science.gov (United States)

    2013-04-12

    ... outages during the ``derecho'' windstorm that affected large portions of the United States in June 2012... (PSHSB or Bureau) January 10, 2013, report titled Impact of the June 2012 Derecho on Communications Networks and Services: Report and Recommendations (Derecho Report), which is available at http://www.fcc...

  3. Anisotropic properties of superconducting niobium wire-networks

    Science.gov (United States)

    Hua, J.; Xiao, Z. L.; Imre, A.; Patel, U.; Ocola, L. E.; Novosad, V.; Welp, U.; Kwok, W. K.

    2008-03-01

    By utilizing focused ion beam (FIB) patterning technique we were able to fabricate hole-arrays with interhole spacing down to 150 nm into superconducting niobium (Nb) films. This enabled us to have a large temperature range to explore the properties of Nb wire networks in which the superconducting strips between neighboring holes are comparable to the superconducting coherence length. We studied the anisotropy of these superconducting networks by measuring the critical temperatures and magnetoresistances at various magnetic field directions respect to the film surface. The effect of film thickness, hole diameter, interhole-spacing and the symmetry of the hole lattice on the anisotropy will be reported.

  4. 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.

  5. Thermodynamic and transport properties of plasmas including silicon-based compounds

    Science.gov (United States)

    Colonna, G.; D’Angola, A.; Pietanza, L. D.; Capitelli, M.; Pirani, F.; Stevanato, E.; Laricchiuta, A.

    2018-01-01

    The characterization of the thermodynamic and transport properties of plasmas including silicon species could be of great interest for the investigation of many different systems containing the product of the ablation of silicon-based materials. Different plasma systems (pure silicon, silicon–argon, silicon dioxide and silicon carbide) have been investigated in a wide temperature range (103–4 104 K) and for different pressures (1, 10, 30 and 100 atm), relying on the construction of accurate and extended databases of internal energy levels and binary-interaction transport cross sections for the silicon compounds. The results have been compared with the available results in the literature also studying the dependence on the ratio of components.

  6. 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.

  7. A Poroelastic Approach for Quantifying Gel Network Properties

    Science.gov (United States)

    Chan, Edwin; Nadermann, Nichole; Feldman, Katie; Davis, Eric

    The unique chemical and structural properties of polymer gels has led to the application of these materials in various membrane-based technologies where selective transport is critical to device performance. Characterizing the chemical and structural properties of a gel is critical to understanding its transport behavior. yet quantifying these properties is nontrivial as it typically requires multiple measurement techniques. In this talk, we demonstrate poroelastic relaxation indentation (PRI) as a single measurement tool to characterize the swelling, mechanical and transport properties of model poly(ethylene glycol)-based hydrogel systems. By applying the appropriate thermodynamic polymer network model and the linear theory of poroelasticity, we are able to use the results from PRI to extract the thermodynamic parameters, elastic modulus, water permeability and mesh size of these gels. We validate these results with small angle neutron scattering to illustrate the applicability of the PRI measurement technique for studying these membrane-like materials.

  8. 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.

  9. 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.

  10. Synthesis and properties of methacrylic-functionalized tween monomer networks.

    Science.gov (United States)

    Muzzalupo, Rita; Tavano, Lorena; Rossi, Cesare Oliviero; Cassano, Roberta; Trombino, Sonia; Picci, Nevio

    2009-02-03

    Tween surfactants possess very interesting properties such as biodegradability, biocompatibility, and low toxicity. The synthesis of acrylate monomers by means of the chemical modification of polysorbate surfactants Tween 20, 40, and 60 with unsaturated groups is described. Monomers were obtained as a result of the reaction of methacrylic anhydride with different grades of Tween surfactants. Further polymerization was carried out in tetrahydrofuran, dimethylformamide, and a mixture of water-tetrahydrofuran. Physicochemistry properties of the polymer networks were investigated, and the obtained results reveal that they strongly depend on the type of solvent used during the polymerization, as well as on the concentration of the casting solution. In particular, our study demonstrated that, depending on the solvent boiling point, i.e., the facility to remove the solvent from the polymer matrix, it is possible to predict properties of the network morphology. Moreover, in vitro studies on controlled release were accomplished to demonstrate the possibility of utilizing these new materials as drug delivery systems. All resulting networks represent a novel class of cross-linked polymeric materials useful both in pharmaceutical and chemical applications.

  11. Estimating topological properties of weighted networks from limited information.

    Science.gov (United States)

    Cimini, Giulio; Squartini, Tiziano; Gabrielli, Andrea; Garlaschelli, Diego

    2015-10-01

    A problem typically encountered when studying complex systems is the limitedness of the information available on their topology, which hinders our understanding of their structure and of the dynamical processes taking place on them. A paramount example is provided by financial networks, whose data are privacy protected: Banks publicly disclose only their aggregate exposure towards other banks, keeping individual exposures towards each single bank secret. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here, we develop a reconstruction method, based on statistical mechanics concepts, that makes use of the empirical link density in a highly nontrivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems.

  12. 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.

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

    NARCIS (Netherlands)

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

    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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

    networks and the number of cortical regions included in the scale. Results revealed that schemes comprising 540–599 regions (surface areas spanning between 250 and 275mm2) at sparsities below 10% showed a superior balance between small-world organization and the size of the cortical scale employed...

  19. The Anatomy of the Global Football Player Transfer Network: Club Functionalities versus Network Properties.

    Directory of Open Access Journals (Sweden)

    Xiao Fan Liu

    Full Text Available Professional association football is a game of talent. The success of a professional club hinges largely on its ability of assembling the best team. Building on a dataset of player transfer records among more than 400 clubs in 24 world-wide top class leagues from 2011 to 2015, this study aims to relate a club's success to its activities in the player transfer market from a network perspective. We confirm that modern professional football is indeed a money game, in which larger investment spent on the acquisition of talented players generally yields better team performance. However, further investigation shows that professional football clubs can actually play different strategies in surviving or even excelling this game, and the success of strategies is strongly associated to their network properties in the football player transfer network.

  20. Intellectual Property Rights Protection in Peer to Peer Networks

    Science.gov (United States)

    Stylios, Georgios; Tsolis, Dimitrios

    Peer to Peer Networks are oftenly used by internet users to share and distribute digital content (images, audio and video) which is in most of cases protected by the Intellectual Property Rights (IPR) legislation. This fact threatens e-inclusion and Internet democracy as a whole as it forces organizations to block access to valuable content. This paper claims that IPR protection and P2P can be complementary. Specifically, a P2P infrastructure is presented which allows broad digital content exchange while on the same time supports data and copyright protection through watermarking technologies.

  1. The scaling properties of dynamical fluctuations in temporal networks

    CERN Document Server

    Chi, Liping

    2015-01-01

    The factorial moments analyses are performed to study the scaling properties of the dynamical fluctuations of contacts and nodes in temporal networks based on empirical data sets. The intermittent behaviors are observed in the fluctuations for all orders of the moments. It indicates that the interaction has self-similarity structure in time interval and the fluctuations are not purely random but dynamical and correlated. The scaling exponents for contacts in Prostitution data and nodes in Conference data are very close to that for 2D Ising model undergoing a second-order phase transition.

  2. From network models to network responses: integration of thermodynamic and kinetic properties of yeast genome-scale metabolic networks.

    Science.gov (United States)

    Soh, Keng Cher; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2012-03-01

    Many important problems in cell biology arise from the dense nonlinear interactions between functional modules. The importance of mathematical modelling and computer simulation in understanding cellular processes is now indisputable and widely appreciated. Genome-scale metabolic models have gained much popularity and utility in helping us to understand and test hypotheses about these complex networks. However, there are some caveats that come with the use and interpretation of different types of metabolic models, which we aim to highlight here. We discuss and illustrate how the integration of thermodynamic and kinetic properties of the yeast metabolic networks in network analyses can help in understanding and utilizing this organism more successfully in the areas of metabolic engineering, synthetic biology and disease treatment. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  3. A Computational Estimation of Cyclic Material Properties Using Artificial Neural Networks

    OpenAIRE

    Tomasella, A.; Dsoki, C. el; H. Hanselka; Kaufmann, H.

    2011-01-01

    The structural durability design of components requires the knowledge of cyclic material properties. These parameters are strongly dependent on environmental conditions and manufacturing processes, and require many experimental tests to be correctly determined. Considering time and costs, it is not possible to include in the tests all the variables that influence the material behaviour. For this reason, the computational method of the Artificial Neural Network (ANN) can be implemented to supp...

  4. Characterizing disease states from topological properties of transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Kluger Harriet M

    2006-05-01

    Full Text Available Abstract Background High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. Here we present new paradigms of data Separation based on construction of transcriptional regulatory networks for normal and abnormal cells using sequence predictions, literature based data and gene expression studies. We analyzed expression datasets from a number of diseased and normal cells, including different types of acute leukemia, and breast cancer with variable clinical outcome. Results We constructed sample-specific regulatory networks to identify links between transcription factors (TFs and regulated genes that differentiate between healthy and diseased states. This approach carries the advantage of identifying key transcription factor-gene pairs with differential activity between healthy and diseased states rather than merely using gene expression profiles, thus alluding to processes that may be involved in gene deregulation. We then generalized this approach by studying simultaneous changes in functionality of multiple regulatory links pointing to a regulated gene or emanating from one TF (or changes in gene centrality defined by its in-degree or out-degree measures, respectively. We found that samples can often be separated based on these measures of gene centrality more robustly than using individual links. We examined distributions of distances (the number of links needed to traverse the path between each pair of genes in the transcriptional networks for gene subsets whose collective expression profiles could best separate each dataset into predefined groups. We found that genes that optimally classify samples are concentrated in neighborhoods in the gene regulatory networks. This suggests that genes that are deregulated in diseased states exhibit a remarkable degree of connectivity. Conclusion Transcription factor-regulated gene links and

  5. 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.

  6. Calcium Phosphate Bone Cements Including Sugar Surfactants: Part Two—Injectability, Adhesive Properties and Biocompatibility

    OpenAIRE

    Fabienne Briand-Mesange; Stéphane Gonçalves; Helène Autefage; Ariane Bercier; Olivier Lignon; Juliette Fitremann

    2010-01-01

    Addition of sugar surfactants, sucrose fatty acid esters and alkylpolyglucosides to a calcium phosphate cement, designed for bone reconstruction, is described. Thanks to their adsorption at the surface of the calcium phosphate particles, the sugar surfactants allowed a full injectability and brought a very good workability. Injectability was measured by monitoring force-distance curves. With some of the selected sugar surfactants adhesive properties of the cement pastes were also observed, wh...

  7. Application of the similarity theory including variable property effects to a complex benchmark problem

    Science.gov (United States)

    Jin, Y.; Herwig, H.

    2010-06-01

    An asymptotic method to account for variable property effects, recently described in this journal, is now applied to a complex benchmark geometry. It is a room which is ventilated by forced convection through inlet and outlet slit nozzles at the top and bottom of the side walls. Four heating elements standing on the ground floor add heat with constant heat flux density of varying strength. CFD solutions with the full coverage of all property temperature dependencies of air and SF6 are compared with asymptotic results (ACFD), applied for these fluids. ACFD results are given as systematic expansions with respect to a heat transfer parameter {\\varepsilon} which serves as perturbation parameter. First and second order asymptotic results of the Nußelt number at the surface of the heating elements are shown as well as temperature distributions along the adiabatic walls of the room. Special attention is given to the reference Nußelt numbers of zero order {(\\varepsilon=0)} which are those for constant properties only for pure forced convection.

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

    DEFF Research Database (Denmark)

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

    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...... 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...... the effect of iron on the measured properties by doping these glasses with ~1 mol% of iron oxide....

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

    Science.gov (United States)

    Romero-Garcia, Rafael; Clemmensen, Line H.

    2014-03-01

    Estimation of morphometric relationships between cortical regions is a widely used approach to identify and characterize structural connectivity. The elevated number of regions that can be considered in a whole-brain correlation analysis might lead to overfitted models. However, the overfitting can be avoided by using regularization methods. We found that, as expected, non-regularized correlations had low variability when a scarce number of variables were considered. However, a slight increase of variables led to an increase of variance of several magnitude orders. On the other hand, the regularized 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. Discovering cancer genes by integrating network and functional properties

    Directory of Open Access Journals (Sweden)

    Davis David P

    2009-09-01

    Full Text Available Abstract Background Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO annotations, to facilitate the identification of cancer genes. Methods Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1. Results Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1. Conclusion Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.

  12. 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.

  13. Fundamental Properties of Wireless Mobile Ad-hoc Networks

    NARCIS (Netherlands)

    Hekmat, R.

    2005-01-01

    Wireless mobile ad-hoc networks are formed by mobile devices that set up a possibly short-lived network for communication needs of the moment. Ad-hoc networks are decentralized, self-organizing networks capable of forming a communication network without relying on any fixed infrastructure. Each node

  14. Ab initio calculations on nuclear matter properties including the effects of three-nucleons interaction

    Science.gov (United States)

    Lovato, Alessandro

    2012-10-01

    In this thesis, the ground state properties of nuclear matter, namely the energy per particle and the response to weak probes, are computed, studying the effects of three nucleon interactions. Both the variational approach, based on the formalism of correlated basis function, and the auxiliary field diffusion Monte Carlo method have been used. A scheme suitable to construct a density-dependent two-nucleon potential in correlated basis approach is discussed. The density dependent potential resulting from UIX three-nucleon force has been employed in auxiliary field diffusion Monte Carlo calculations that turned out to be in very good agreement with correlated basis variational results. Hence, the underbinding of symmetric nuclear matter has to be ascribed to deficiencies of the UXI potential. A comparative analysis of the equations of state of both pure neutron matter and symmetric nuclear matter obtained using a new generation of "chiral inspired" local three-body potentials has been performed. These potentials provide an excellent description of the properties of light nuclei, as well as of the neutron-deuteron doublet scattering length. The weak response of symmetric nuclear matter has been computed at three-body cluster level. Two-body effective interactions and one-body effective operators have been derived within the formalism of correlated basis functions. The inclusion of the three-body cluster term in the effective interaction allowed for a direct inclusion of the UIX three-nucleon potential. Moreover, the sizable unphysical dependence of the effective weak operator is removed once the three-body cluster term is taken into account.

  15. 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.

  16. 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

    Estimation of morphometric relationships between cortical regions is a widely used approach to identify and characterize structural connectivity. The elevated number of regions that can be considered in a whole-brain correlation analysis might lead to overfitted models. However, the overfitting can...... 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...

  17. 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.

  18. 75 FR 47631 - Douglas Battery Manufacturing Co., Currently Known as Lexington Road Properties, Inc., Including...

    Science.gov (United States)

    2010-08-06

    ... Employment and Training Administration Douglas Battery Manufacturing Co., Currently Known as Lexington Road... January 6, 2010, applicable to workers of Douglas Battery Manufacturing Co., including on-site leased... engaged in the production of automotive and industrial batteries. New information shows that in January...

  19. Mathematical Properties of the Hyperbolicity of Circulant Networks

    Directory of Open Access Journals (Sweden)

    Juan C. Hernández

    2015-01-01

    Full Text Available If X is a geodesic metric space and x1,x2,x3∈X, a geodesic triangle   T={x1,x2,x3} is the union of the three geodesics [x1x2], [x2x3], and [x3x1] in X. The space X is δ-hyperbolic (in the Gromov sense if any side of T is contained in a δ-neighborhood of the union of the two other sides, for every geodesic triangle T in X. The study of the hyperbolicity constant in networks is usually a very difficult task; therefore, it is interesting to find bounds for particular classes of graphs. A network is circulant if it has a cyclic group of automorphisms that includes an automorphism taking any vertex to any other vertex. In this paper we obtain several sharp inequalities for the hyperbolicity constant of circulant networks; in some cases we characterize the graphs for which the equality is attained.

  20. Pharmacological treatment of oro-facial pain - health technology assessment including a systematic review with network meta-analysis.

    Science.gov (United States)

    Häggman-Henrikson, B; Alstergren, P; Davidson, T; Högestätt, E D; Östlund, P; Tranaeus, S; Vitols, S; List, T

    2017-10-01

    This health technology assessment evaluated the efficacy of pharmacological treatment in patients with oro-facial pain. Randomised controlled trials were included if they reported pharmacological treatment in patients ≥18 years with chronic (≥3 months) oro-facial pain. Patients were divided into subgroups: TMD-muscle [temporomandibular disorders (TMD) mainly associated with myalgia]; TMD-joint (TMD mainly associated with temporomandibular joint pain); and burning mouth syndrome (BMS). The primary outcome was pain intensity reduction after pharmacological treatment. The scientific quality of the evidence was rated according to GRADE. An electronic search in PubMed, Cochrane Library, and EMBASE from database inception to 1 March 2017 combined with a handsearch identified 1552 articles. After screening of abstracts, 178 articles were reviewed in full text and 57 studies met the inclusion criteria. After risk of bias assessment, 41 articles remained: 15 studies on 790 patients classified as TMD-joint, nine on 375 patients classified as TMD-muscle and 17 on 868 patients with BMS. Of these, eight studies on TMD-muscle, and five on BMS were included in separate network meta-analysis. The narrative synthesis suggests that NSAIDs as well as corticosteroid and hyaluronate injections are effective treatments for TMD-joint pain. The network meta-analysis showed that clonazepam and capsaicin reduced pain intensity in BMS, and the muscle relaxant cyclobenzaprine, for the TMD-muscle group. In conclusion, based on a limited number of studies, evidence provided with network meta-analysis showed that clonazepam and capsaicin are effective in treatment of BMS and that the muscle relaxant cyclobenzaprine has a positive treatment effect for TMD-muscle pain. © 2017 John Wiley & Sons Ltd.

  1. Pharmacological treatment of orofacial pain - Health Technology Assessment including a systematic review with network meta-analysis.

    Science.gov (United States)

    Häggman-Henrikson, B; Alstergren, P; Davidson, T; Högestätt, Ed; Östlund, P; Tranaeus, S; Vitols, S; List, T

    2017-06-27

    This health technology assessment evaluated the efficacy of pharmacological treatment in patients with orofacial pain. Randomised controlled trials were included if they reported pharmacological treatment in patients ≥18 years with chronic (≥3 months) orofacial pain. Patients were divided into subgroups: TMD-muscle [Temporomandibular disorders (TMD) mainly associated with myalgia]; TMD-joint (TMD mainly associated with temporomandibular joint pain); and Burning mouth syndrome (BMS). The primary outcome was pain intensity reduction after pharmacological treatment. The scientific quality of the evidence was rated according to GRADE. An electronic search in PubMed, Cochrane Library, and Embase from database inception to 1 March 2017 combined with a handsearch identified 1,556 articles. After screening of abstracts, 182 articles were reviewed in full text and 57 studies met the inclusion criteria. After risk of bias assessment, 41 articles remained: 15 studies on 790 patients classified as TMD-joint, 9 on 375 patients classified as TMD-muscle, and 17 on 868 patients with BMS. Of these, 8 studies on TMD-muscle and 5 on BMS were included in separate network meta-analysis. The narrative synthesis suggests that NSAIDs as well as corticosteroid and hyaluronate injections are effective treatments for TMD-joint pain. The network meta-analysis showed that clonazepam and capsaicin reduced pain intensity in BMS, and the muscle relaxant cyclobenzaprine, for the TMD-muscle group. In conclusion, based on a limited number of studies, evidence provided with network meta-analysis showed that clonazepam and capsaicin are effective in treatment of BMS and that the muscle relaxant cyclobenzaprine have a positive treatment effect for TMD-muscle pain. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  2. Photocatalytic Properties of TiO2 Porous Network Film.

    Science.gov (United States)

    Yu, Lianqing; Zhi, Qianqian; Huang, Chengxing; Zhang, Yaping; Dong, Kaituo; Neppolian, B

    2015-09-01

    Three-dimensional porous network TiO2 film (PW-film) and nanoparticles film were synthesized on surface of the Ti foil by a facile method to investigate both the photoelectrochemical and photocatalytic properties. The prepared samples were characterized by scanning electron microscopy (SEM), transmission electron microscope (TEM) and X-ray diffraction spectroscopy (XRD) techniques. Methylene blue was used as a target molecule to estimate the photocatalytic activity of the films. Results revealed that the hydrothermal temperature and time have great influence on the crystal type and film morphology of TiO2 catalysts. A higher hydrothermal temperature is benefit for the formation of anatase phase of TiO2 nanotubes with PW-film, which had a large number of nodes. After investigation of the photoelectrochemical properties, a maximum photoconversion efficiency of 4.79% is observed for nanoparticles film with rutile phase of TiO2 under UV light illumination, which was incredible 2 times higher than that of the PW-film with anatase phase. It was shown that the morphology of TiO2 film contributes more significant effect on photocatalytic and photoelectric performance than its crystal type.

  3. 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.

  4. Comparison of three intraocular pressure measurement methods including biomechanical properties of the cornea.

    Science.gov (United States)

    Smedowski, Adrian; Weglarz, Beata; Tarnawska, Dorota; Kaarniranta, Kai; Wylegala, Edward

    2014-02-04

    The aim of this study was to show the usefulness of three methods for measuring IOP: Goldmann applanation tonometry, rebound tonometry, and Ultra-High-Speed Scheimpflug technology. The examined group consisted of 96 patients (192 eyes), including 63 women and 33 men with a mean age of 59.3 ± 19.9 years. Together, 152 healthy eyes and 40 eyes with different pathologies were examined. Intraocular pressure was measured using the Goldmann applanation tonometer (GAT), the Icare Pro rebound tonometer (RT), and Ultra-High-Speed Scheimpflug technology (UHS ST; Corvis ST with pachymetry). Additionally, corneal pachymetry was conducted with a Scheimpflug camera (Pentacam) and an Ultrasound Pachymeter (A-scan Plus) as a comparison for Corvis ST pachymetry. The mean IOPs were 15.6 ± 3.75 mm Hg, 15.6 ± 3.5 mm Hg, and 16.1 ± 4.0 mm Hg when measured with the GAT, the RT, and the UHS ST, respectively. The mean central corneal thickness (CCT) was 543.7 ± 52.7 μm, 547.9 ± 54.0 μm, and 556.25 ± 38.8 μm as measured with the UHS ST, the Pentacam, and the Ultrasound Pachymeter, respectively. In comparison between devices, there was a significant difference between IOP values measured with the GAT and the RT versus the UHS ST (P < 0.001), and there was no significant difference between GAT and RT (P = 0.5). No significant differences were observed in CCT measured with the UHS ST, Pentacam, and Ultrasound Pachymeter. We showed that the RT Icare Pro ensures IOP measurements that are more comparable with the measurements obtained with the GAT than the measurements that are provided by UHS ST.

  5. 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.

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

    Science.gov (United States)

    Muelas, Raquel; Monllor, Paula; Romero, Gema; Sayas-Barberá, Estrella; Navarro, Casilda; Díaz, José Ramón; Sendra, Esther

    2017-12-18

    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.

  7. Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space.

    Science.gov (United States)

    Ahnert, S E; Fink, T M A

    2016-07-01

    Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the 'function' of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature. © 2016 The Authors.

  8. Altered network properties of the fronto-parietal network and the thalamus in impaired consciousness

    Directory of Open Access Journals (Sweden)

    Julia Sophia Crone

    2014-01-01

    In chronic disorders of consciousness, modularity at the global level was reduced suggesting a disturbance in the optimal balance between segregation and integration. Moreover, network properties were altered in several regions which are associated with conscious processing (particularly, in medial parietal, and frontal regions, as well as in the thalamus. Between minimally conscious and unconscious patients the local efficiency of medial parietal regions differed. Alterations in the thalamus were particularly evident in non-conscious patients. Most of the regions affected in patients with impaired consciousness belong to the so-called ‘rich club’ of highly interconnected central nodes. Disturbances in their topological characteristics have severe impact on information integration and are reflected in deficits in cognitive functioning probably leading to a total breakdown of consciousness.

  9. Traffic properties for stochastic routings on scale-free networks

    CERN Document Server

    Hayashi, Yukio

    2011-01-01

    For realistic scale-free networks, we investigate the traffic properties of stochastic routing inspired by a zero-range process known in statistical physics. By parameters $\\alpha$ and $\\delta$, this model controls degree-dependent hopping of packets and forwarding of packets with higher performance at more busy nodes. Through a theoretical analysis and numerical simulations, we derive the condition for the concentration of packets at a few hubs. In particular, we show that the optimal $\\alpha$ and $\\delta$ are involved in the trade-off between a detour path for $\\alpha 0$; In the low-performance regime at a small $\\delta$, the wandering path for $\\alpha 0$ and $\\alpha < 0$ is small, neither the wandering long path with short wait trapped at nodes ($\\alpha = -1$), nor the short hopping path with long wait trapped at hubs ($\\alpha = 1$) is advisable. A uniformly random walk ($\\alpha = 0$) yields slightly better performance. We also discuss the congestion phenomena in a more complicated situation with pack...

  10. 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.

  11. 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.

  12. INVESTIGATION OF FOSSIL FUEL AND LIQUID BIOFUEL BLEND PROPERTIES USING ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    G. Najafi

    2012-06-01

    Full Text Available Gasoline fuel is the baseline fuel in this research, to which bioethanol, biodiesel and diesel are additives. The fuel blends were prepared based on different volumes and following which, ASTM (American Society for Testing and Materials test methods analysed some of the important properties of the blends, such as: density, dynamic viscosity, kinematic viscosity and water and sediment. Experimental data were analysed by means of Matlab software. The results obtained from artificial neural network analysis of the data showed that the network with feed forward back propagation of the Levenberg-Marquardt train LM function with 10 neurons in the hidden layer was the best for predicting the parameters, including: Water and sediment (W, dynamic viscosity (DV, kinematic viscosity (KV and density (De. The experimental data had a good correlation with ANN-predicted values according to 0.96448 for regression.

  13. 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

  14. In-vivo characterization of optical properties of pigmented skin lesions including melanoma using oblique incidence diffuse reflectance spectrometry

    Science.gov (United States)

    Garcia-Uribe, Alejandro; Smith, Elizabeth B.; Zou, Jun; Duvic, Madeleine; Prieto, Victor; Wang, Lihong V.

    2011-02-01

    In this letter, we report the first use of oblique incidence diffuse reflectance spectrometry to conduct in-vivo measurements of optical properties of three different types of pigmented skin lesions, including melanoma, dysplastic, and common nevi. Both absorption and reduced scattering coefficient spectra were estimated from the spatially resolved diffuse reflectance within the wavelength range of 455-765 nm for 144 pigmented skin lesions including 16 melanomas. The absorption and reduced scattering spectra were found to change with the malignancy of the skin lesions, which were generally higher for the malignant cases than the benign ones. Based on the measurement results, the physiological origin leading to the change of the absorption and scattering properties is also discussed.

  15. 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.

  16. The Landscape of Evolution: Reconciling Structural and Dynamic Properties of Metabolic Networks in Adaptive Diversifications.

    Science.gov (United States)

    Morrison, Erin S; Badyaev, Alexander V

    2016-08-01

    The network of the interactions among genes, proteins, and metabolites delineates a range of potential phenotypic diversifications in a lineage, and realized phenotypic changes are the result of differences in the dynamics of the expression of the elements and interactions in this deterministic network. Regulatory mechanisms, such as hormones, mediate the relationship between the structural and dynamic properties of networks by determining how and when the elements are expressed and form a functional unit or state. Changes in regulatory mechanisms lead to variable expression of functional states of a network within and among generations. Functional properties of network elements, and the magnitude and direction of evolutionary change they determine, depend on their location within a network. Here, we examine the relationship between network structure and the dynamic mechanisms that regulate flux through a metabolic network. We review the mechanisms that control metabolic flux in enzymatic reactions and examine structural properties of the network locations that are targets of flux control. We aim to establish a predictive framework to test the contributions of structural and dynamic properties of deterministic networks to evolutionary diversifications. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

  17. 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.

  18. Structural properties of the Caenorhabditis elegans neuronal network

    National Research Council Canada - National Science Library

    Varshney, Lav R; Chen, Beth L; Paniagua, Eric; Hall, David H; Chklovskii, Dmitri B

    2011-01-01

    .... Even for Caenorhabditis elegans, whose neuronal network is relatively small and stereotypical from animal to animal, published wiring diagrams are neither accurate nor complete and self-consistent...

  19. Structural properties of the Caenorhabditis elegans neuronal network

    National Research Council Canada - National Science Library

    Varshney, Lav R; Chen, Beth L; Paniagua, Eric; Hall, David H; Chklovskii, Dmitri B

    2011-01-01

    Despite recent interest in reconstructing neuronal networks, complete wiring diagrams on the level of individual synapses remain scarce and the insights into function they can provide remain unclear...

  20. 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.

  1. Weighted Association Rule Mining for Item Groups with Different Properties and Risk Assessment for Networked Systems

    Science.gov (United States)

    Kim, Jungja; Ceong, Heetaek; Won, Yonggwan

    In market-basket analysis, weighted association rule (WAR) discovery can mine the rules that include more beneficial information by reflecting item importance for special products. In the point-of-sale database, each transaction is composed of items with similar properties, and item weights are pre-defined and fixed by a factor such as the profit. However, when items are divided into more than one group and the item importance must be measured independently for each group, traditional weighted association rule discovery cannot be used. To solve this problem, we propose a new weighted association rule mining methodology. The items should be first divided into subgroups according to their properties, and the item importance, i.e. item weight, is defined or calculated only with the items included in the subgroup. Then, transaction weight is measured by appropriately summing the item weights from each subgroup, and the weighted support is computed as the fraction of the transaction weights that contains the candidate items relative to the weight of all transactions. As an example, our proposed methodology is applied to assess the vulnerability to threats of computer systems that provide networked services. Our algorithm provides both quantitative risk-level values and qualitative risk rules for the security assessment of networked computer systems using WAR discovery. Also, it can be widely used for new applications with many data sets in which the data items are distinctly separated.

  2. A density-functional theory-based neural network potential for water clusters including van der Waals corrections.

    Science.gov (United States)

    Morawietz, Tobias; Behler, Jörg

    2013-08-15

    The fundamental importance of water for many chemical processes has motivated the development of countless efficient but approximate water potentials for large-scale molecular dynamics simulations, from simple empirical force fields to very sophisticated flexible water models. Accurate and generally applicable water potentials should fulfill a number of requirements. They should have a quality close to quantum chemical methods, they should explicitly depend on all degrees of freedom including all relevant many-body interactions, and they should be able to describe molecular dissociation and recombination. In this work, we present a high-dimensional neural network (NN) potential for water clusters based on density-functional theory (DFT) calculations, which is constructed using clusters containing up to 10 monomers and is in principle able to meet all these requirements. We investigate the reliability of specific parametrizations employing two frequently used generalized gradient approximation (GGA) exchange-correlation functionals, PBE and RPBE, as reference methods. We find that the binding energy errors of the NN potentials with respect to DFT are significantly lower than the typical uncertainties of DFT calculations arising from the choice of the exchange-correlation functional. Further, we examine the role of van der Waals interactions, which are not properly described by GGA functionals. Specifically, we incorporate the D3 scheme suggested by Grimme (J. Chem. Phys. 2010, 132, 154104) in our potentials and demonstrate that it can be applied to GGA-based NN potentials in the same way as to DFT calculations without modification. Our results show that the description of small water clusters provided by the RPBE functional is significantly improved if van der Waals interactions are included, while in case of the PBE functional, which is well-known to yield stronger binding than RPBE, van der Waals corrections lead to overestimated binding energies.

  3. 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.

  4. 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.

  5. Genetic network properties of the human cortex based on regional thickness and surface area measures

    Directory of Open Access Journals (Sweden)

    Anna R. Docherty

    2015-08-01

    Full Text Available We examined network properties of genetic covariance between average cortical thickness (CT and surface area (SA within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques—biometrical genetic modeling, cluster analysis, and graph theory—to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.

  6. Engineering reaction-diffusion networks with properties of neural tissue.

    Science.gov (United States)

    Litschel, Thomas; Norton, Michael M; Tserunyan, Vardges; Fraden, Seth

    2018-01-03

    We present an experimental system of networks of coupled non-linear chemical reactors, which we theoretically model within a reaction-diffusion framework. The networks consist of patterned arrays of diffusively coupled nanoliter-scale reactors containing the Belousov-Zhabotinsky (BZ) reaction. Microfluidic fabrication techniques are developed that provide the ability to vary the network topology and the reactor coupling strength and offer the freedom to choose whether an arbitrary reactor is inhibitory or excitatory coupled to its neighbor. This versatile experimental and theoretical framework can be used to create a wide variety of chemical networks. Here we design, construct and characterize chemical networks that achieve the complexity of central pattern generators (CPGs), which are found in the autonomic nervous system of a variety of organisms.

  7. 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...

  8. 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

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

    OpenAIRE

    Pablo Gonzalez Rodriguez; A. Petra Dral; Karin J. H. van den Nieuwenhuijzen; Walter Lette; Dik J. Schipper; Johan E. ten Elshof

    2018-01-01

    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...

  10. Metabolic pathway of non-alcoholic fatty liver disease: Network properties and robustness

    OpenAIRE

    WenJun Zhang

    2017-01-01

    Nonalcoholic fatty liver disease (NAFLD) is a systematic and complex disease involving various cytokines/metabolites. In present article, we use methodology of network biology to analyze network properties of NAFLD metabolic pathway. It is found that the metabolic pathway of NAFLD is not a typical complex network with power-law degree distribution, p(x)=x^(-4.4275), x>=5. There is only one connected component in the metabolic pathway. The calculated cut cytokines/metabolites of the metabolic ...

  11. 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.

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

    Science.gov (United States)

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

    2015-08-07

    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.

  13. Properties of centralized cooperative sensing in cognitive radio networks

    Science.gov (United States)

    Skokowski, Paweł; Malon, Krzysztof; Łopatka, Jerzy

    2017-04-01

    Spectrum sensing is a functionality that enables network creation in the cognitive radio technology. Spectrum sensing is use for building the situation awareness knowledge for better use of radio resources and to adjust network parameters in case of jamming, interferences from legacy systems, decreasing link quality caused e.g. by nodes positions changes. This paper presents results from performed tests to compare cooperative centralized sensing versus local sensing. All tests were performed in created simulator developed in Matlab/Simulink environment.

  14. Thermochemical stability and friction properties of soft organosilica networks for solid lubrication

    NARCIS (Netherlands)

    Gonzalez Rodriguez, P.; Dral, A. Petra; van den Nieuwenhuijzen, Karin J.H.; Lette, Walter; Schipper, Dik J.; ten Elshof, Johan E.

    2018-01-01

    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

  15. Analysis and applications of spectral properties of grounded Laplacian matrices for directed networks

    NARCIS (Netherlands)

    Xia, Weiguo; Cao, Ming

    In-depth understanding of the spectral properties of grounded Laplacian matrices is critical for the analysis of convergence speeds of dynamical processes over complex networks, such as opinion dynamics in social networks with stubborn agents. We focus on grounded Laplacian matrices for directed

  16. 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.

  17. Native SDS-PAGE: high resolution electrophoretic separation of proteins with retention of native properties including bound metal ions.

    Science.gov (United States)

    Nowakowski, Andrew B; Wobig, William J; Petering, David H

    2014-05-01

    Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) is commonly used to obtain high resolution separation of complex mixtures of proteins. The method initially denatures the proteins that will undergo electrophoresis. Although covalent structural features of resolved proteins can be determined with SDS-PAGE, functional properties are destroyed, including the presence of non-covalently bound metal ions. To address this shortcoming, blue-native (BN)-PAGE has been introduced. This method retains functional properties but at the cost of protein resolving power. To address the need for a high resolution PAGE method that results in the separation of native proteins, experiments tested the impact of changing the conditions of SDS-PAGE on the quality of protein separation and retention of functional properties. Removal of SDS and EDTA from the sample buffer together with omission of a heating step had no effect on the results of PAGE. Reduction of SDS in the running buffer from 0.1% to 0.0375% together with deletion of EDTA also made little impact on the quality of the electrophoretograms of fractions of pig kidney (LLC-PK1) cell proteome in comparison with that achieved with the SDS-PAGE method. The modified conditions were called native (N)SDS-PAGE. Retention of Zn(2+) bound in proteomic samples increased from 26 to 98% upon shifting from standard to modified conditions. Moreover, seven of nine model enzymes, including four Zn(2+) proteins that were subjected to NSDS-PAGE retained activity. All nine were active in BN-PAGE, whereas all underwent denaturation during SDS-PAGE. Metal retention after electrophoresis was additionally confirmed using laser ablation-inductively coupled plasma-mass spectrometry and in-gel Zn-protein staining using the fluorophore TSQ.

  18. Multifractal analysis and topological properties of a new family of weighted Koch networks

    Science.gov (United States)

    Huang, Da-Wen; Yu, Zu-Guo; Anh, Vo

    2017-03-01

    Weighted complex networks, especially scale-free networks, which characterize real-life systems better than non-weighted networks, have attracted considerable interest in recent years. Studies on the multifractality of weighted complex networks are still to be undertaken. In this paper, inspired by the concepts of Koch networks and Koch island, we propose a new family of weighted Koch networks, and investigate their multifractal behavior and topological properties. We find some key topological properties of the new networks: their vertex cumulative strength has a power-law distribution; there is a power-law relationship between their topological degree and weight strength; the networks have a high weighted clustering coefficient of 0.41004 (which is independent of the scaling factor c) in the limit of large generation t; the second smallest eigenvalue μ2 and the maximum eigenvalue μn are approximated by quartic polynomials of the scaling factor c for the general Laplacian operator, while μ2 is approximately a quartic polynomial of c and μn= 1.5 for the normalized Laplacian operator. Then, we find that weighted koch networks are both fractal and multifractal, their fractal dimension is influenced by the scaling factor c. We also apply these analyses to six real-world networks, and find that the multifractality in three of them are strong.

  19. A Logic for Checking the Probabilistic Steady-State Properties of Reaction Networks.

    Science.gov (United States)

    Picard, Vincent; Siegel, Anne; Bourdon, Jérémie

    2017-08-01

    Designing probabilistic reaction models and determining their stochastic kinetic parameters are major issues in systems biology. To assist in the construction of reaction network models, we introduce a logic that allows one to express asymptotic properties about the steady-state stochastic dynamics of a reaction network. Basically, the formulas can express properties on expectancies, variances, and covariances. If a formula encoding for experimental observations on the system is not satisfiable, then the reaction network model can be rejected. We demonstrate that deciding the satisfiability of a formula is NP-hard, but we provide a decision method based on solving systems of polynomial constraints. We illustrate our method on a toy example.

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

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2015-01-01

    Full Text Available 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

  1. Predicting the connectivity of primate cortical networks from topological and spatial node properties

    Directory of Open Access Journals (Sweden)

    Kaiser Marcus

    2007-03-01

    Full Text Available Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.

  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 Nanoma...

  3. Enhanced Mechanical Properties of Nanoparticle Networks Cross-Linked by Biomimetic Catch Bonds

    Science.gov (United States)

    Mbanga, Badel L.; Iyer, Balaji V. S.; Yashin, Victor V.; Balazs, Anna C.

    2015-03-01

    The tunable behavior of cross-linked networks of Polymer-Grafted Nanoparticles (PGNs) makes them excellent candidates for designing novel materials with enhanced mechanical properties. The building block of a PGN network is a nanoparticle with grafted polymer chains whose free ends' reactive groups can form bonds with the end chains on the nearby particles. We use computer modeling to study the tensile behavior of 3D samples, in which some fraction of cross-links is formed through the biomimetic ``catch'' bonds. In contrast to conventional ``slip'' bonds, the catch bonds might become stronger under an applied force due to transitions between two conformational states. The mechanical properties of the PGN networks are shown to exhibit a drastic improvement upon introduction of the catch bonds into the network. We discuss how ductility, toughness, and rate of strain recovery of the network depend on the catch bond content.

  4. 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,

  5. 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.

  6. Stability and dynamical properties of material flow systems on random networks

    Science.gov (United States)

    Anand, K.; Galla, T.

    2009-04-01

    The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

  7. Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions.

    Science.gov (United States)

    Porth, Ilga; Klápště, Jaroslav; Skyba, Oleksandr; Friedmann, Michael C; Hannemann, Jan; Ehlting, Juergen; El-Kassaby, Yousry A; Mansfield, Shawn D; Douglas, Carl J

    2013-11-01

    High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P. trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28,831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Transcripts were pre-selected at a much lower logarithm of Bayes factor (logBF) threshold than SNPs and were not accommodated in the networks. Using persistent variables, we constructed cross-validated networks for variability in wood attributes, which contained four to six variables with 94-100% predictive accuracy. Accommodated gene variants revealed the hierarchy in the genetic architecture that underpins substantial phenotypic variability, and represent new tools to support the maximization of response to selection. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  8. Computing properties of stable configurations of thermodynamic binding networks

    OpenAIRE

    Breik, Keenan; Prakash, Lakshmi; Thachuk, Chris; Heule, Marijn; Soloveichik, David

    2017-01-01

    Models of molecular computing generally embed computation in kinetics--the specific time evolution of a chemical system. However, if the desired output is not thermodynamically stable, basic physical chemistry dictates that thermodynamic forces will drive the system toward error throughout the computation. The Thermodynamic Binding Network (TBN) model was introduced to formally study how the thermodynamic equilibrium can be made consistent with the desired computation, and it idealizes bindin...

  9. Spam email filtering using network-level properties

    OpenAIRE

    Cortez, Paulo; Correia, André; Sousa, Pedro; Rocha, Miguel; Rio, Miguel

    2010-01-01

    Spam is serious problem that affects email users (e.g. phishing attacks, viruses and time spent reading unwanted messages). We propose a novel spam email filtering approach based on network-level attributes (e.g. the IP sender geographic coordinates) that are more persistent in time when compared to message content. This approach was tested using two classifiers, Naive Bayes (NB) and Support Vector Machines (SVM), and compared against bag-of-words models and eight blacklists. Several experime...

  10. Benchmark Calculations of Energetic Properties of Groups 4 and 6 Transition Metal Oxide Nanoclusters Including Comparison to Density Functional Theory

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Zongtang; Both, Johan; Li, Shenggang; Yue, Shuwen; Aprà, Edoardo; Keçeli, Murat; Wagner, Albert F.; Dixon, David A.

    2016-08-09

    The heats of formation and the normalized clustering energies (NCEs) for the group 4 and group 6 transition metal oxide (TMO) trimers and tetramers have been calculated by the Feller-Peterson-Dixon (FPD) method. The heats of formation predicted by the FPD method do not differ much from those previously derived from the NCEs at the CCSD(T)/aT level except for the CrO3 nanoclusters. New and improved heats of formation for Cr3O9 and Cr4O12 were obtained using PW91 orbitals instead of Hartree-Fock (HF) orbitals. Diffuse functions are necessary to predict accurate heats of formation. The fluoride affinities (FAs) are calculated with the CCSD(T) method. The relative energies (REs) of different isomers, NCEs, electron affinities (EAs), and FAs of (MO2)n ( M = Ti, Zr, Hf, n = 1 – 4 ) and (MO3)n ( M = Cr, Mo, W, n = 1 – 3) clusters have been benchmarked with 55 exchange-correlation DFT functionals including both pure and hybrid types. The absolute errors of the DFT results are mostly less than ±10 kcal/mol for the NCEs and the EAs, and less than ±15 kcal/mol for the FAs. Hybrid functionals usually perform better than the pure functionals for the REs and NCEs. The performance of the two types of functionals in predicting EAs and FAs is comparable. The B1B95 and PBE1PBE functionals provide reliable energetic properties for most isomers. Long range corrected pure functionals usually give poor FAs. The standard deviation of the absolute error is always close to the mean errors and the probability distributions of the DFT errors are often not Gaussian (normal). The breadth of the distribution of errors and the maximum probability are dependent on the energy property and the isomer.

  11. Low Modulus Silicone Elastomer Networks with Desirable Viscoelastic Properties for Cell Mobility Studies

    Science.gov (United States)

    Albert, Julie N. L.; Genzer, Jan

    2013-03-01

    Biocompatible silicone elastomer networks provide a versatile platform for studying the effect of compliance on cell movement. In conventional network formation schemes, poly(dimethylsiloxane) (PDMS) is cross-linked via reactive end groups, and the modulus of the material is controlled by the ratio of polymer to cross-linker. However, low modulus networks fabricated in this manner are imperfect and insufficiently cross-linked with high soluble fractions and reduced elasticity, especially as the network modulus approaches that of soft tissues (on the order of 10 kPa). In order to overcome these limitations, we synthesized PDMS chains in which vinylmethylsiloxane units were incorporated every ~15-20 kDa along the polymer backbone. We then cross-linked the polymer through the vinyl groups using hydrosilylation chemistry. The resultant networks exhibited lower soluble fractions and lower viscous dissipation/greater elasticity as compared to equivalent-modulus networks fabricated by the conventional end-group cross-linking scheme. We attribute the mechanical properties of our networks to the presence of network-bound free chain ends that effectively plasticize the network to lower the modulus without compromising network elasticity.

  12. 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.

  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...... these improved properties are achieved without consequently increased Young’s moduli and decreased breakdown strength compared, for example, with other silicone elastomers containing fillers. In particular, the interpenetrating systems show dielectric permittivity ε’ from 6,7 to 2 x 103 at low frequencies (0...

  14. 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.

  15. Connecting macroscopic dynamics with microscopic properties in active microtubule network contraction

    Science.gov (United States)

    Foster, Peter J.; Yan, Wen; Fürthauer, Sebastian; Shelley, Michael J.; Needleman, Daniel J.

    2017-12-01

    The cellular cytoskeleton is an active material, driven out of equilibrium by molecular motor proteins. It is not understood how the collective behaviors of cytoskeletal networks emerge from the properties of the network’s constituent motor proteins and filaments. Here we present experimental results on networks of stabilized microtubules in Xenopus oocyte extracts, which undergo spontaneous bulk contraction driven by the motor protein dynein, and investigate the effects of varying the initial microtubule density and length distribution. We find that networks contract to a similar final density, irrespective of the length of microtubules or their initial density, but that the contraction timescale varies with the average microtubule length. To gain insight into why this microscopic property influences the macroscopic network contraction time, we developed simulations where microtubules and motors are explicitly represented. The simulations qualitatively recapitulate the variation of contraction timescale with microtubule length, and allowed stress contributions from different sources to be estimated and decoupled.

  16. A New Method for Identifying Essential Proteins Based on Network Topology Properties and Protein Complexes.

    Directory of Open Access Journals (Sweden)

    Chao Qin

    Full Text Available Essential proteins are indispensable to the viability and reproduction of an organism. The identification of essential proteins is necessary not only for understanding the molecular mechanisms of cellular life but also for disease diagnosis, medical treatments and drug design. Many computational methods have been proposed for discovering essential proteins, but the precision of the prediction of essential proteins remains to be improved. In this paper, we propose a new method, LBCC, which is based on the combination of local density, betweenness centrality (BC and in-degree centrality of complex (IDC. First, we introduce the common centrality measures; second, we propose the densities Den1(v and Den2(v of a node v to describe its local properties in the network; and finally, the combined strategy of Den1, Den2, BC and IDC is developed to improve the prediction precision. The experimental results demonstrate that LBCC outperforms traditional topological measures for predicting essential proteins, including degree centrality (DC, BC, subgraph centrality (SC, eigenvector centrality (EC, network centrality (NC, and the local average connectivity-based method (LAC. LBCC also improves the prediction precision by approximately 10 percent on the YMIPS and YMBD datasets compared to the most recently developed method, LIDC.

  17. A New Method for Identifying Essential Proteins Based on Network Topology Properties and Protein Complexes.

    Science.gov (United States)

    Qin, Chao; Sun, Yongqi; Dong, Yadong

    2016-01-01

    Essential proteins are indispensable to the viability and reproduction of an organism. The identification of essential proteins is necessary not only for understanding the molecular mechanisms of cellular life but also for disease diagnosis, medical treatments and drug design. Many computational methods have been proposed for discovering essential proteins, but the precision of the prediction of essential proteins remains to be improved. In this paper, we propose a new method, LBCC, which is based on the combination of local density, betweenness centrality (BC) and in-degree centrality of complex (IDC). First, we introduce the common centrality measures; second, we propose the densities Den1(v) and Den2(v) of a node v to describe its local properties in the network; and finally, the combined strategy of Den1, Den2, BC and IDC is developed to improve the prediction precision. The experimental results demonstrate that LBCC outperforms traditional topological measures for predicting essential proteins, including degree centrality (DC), BC, subgraph centrality (SC), eigenvector centrality (EC), network centrality (NC), and the local average connectivity-based method (LAC). LBCC also improves the prediction precision by approximately 10 percent on the YMIPS and YMBD datasets compared to the most recently developed method, LIDC.

  18. A LOCATION-INVENTORY MODEL INCLUDING DELIVERY DELAY COST AND CAPACITY CONSTRAINTS IN A STOCHASTIC DISTRIBUTION NETWORK

    Directory of Open Access Journals (Sweden)

    A. Ahmadi Javid

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: In this paper, we present a distribution network design problem in a supply chain system that minimises the total cost of location, inventory, and delivery delay. Customers’ demands are random, and multiple capacity levels are available for the distribution centers. The problem is first formulated as a mixed integer convex programming model to optimally solve medium-sized instances, and then a heuristic is developed for solving large-sized instances.

    AFRIKAANSE OPSOMMING: In hierdie artikel word ‘n distribusienetwerkprobleem in ‘n voorsieningsketting voorgehou waar die totale koste van die ligging, voorraad en afleweringsvertragings geminimiseer word. Die vraag is lukraak en verskeie kapasiteitsvlakke is beskikbaar in die verspreidingsentra. Die problem word eers geformuleer as ‘n gemengde-heeltal-konvekse model sodat mediumgrootte gevalle geoptimiseer kan word, waarna ‘n heuristieke benadering ontwikkel word vir die oplos van grootskaalse aktiwiteite.

  19. Topological properties and community detection of venture capital network: Evidence from China

    Science.gov (United States)

    Jin, Yonghong; Zhang, Qi; Li, Sai-Ping

    2016-01-01

    Financial networks have been extensively studied as examples of real world complex networks. Based on the data from Chinese GEM and SME board, we establish a venture capital (VC) network to study the statistical properties, topological properties and community structure of the Chinese venture capital network. The result shows that there are no dominant venture capital firms in China which act as hubs in the VC network, and multi-company syndication is not popular in China, meaning that the relationships among venture capital companies are weak. The network is robust under either random or intentional attack, and possesses small world property. We also find from its community structure that, venture capital companies are more concentrated in developed districts but the links within the same district are scarce as compared to the links between different developed districts, indicating that venture capital companies are more willing to syndicate with companies in other developed districts. Furthermore, venture capital companies which invest in the same industry have closer relations within their communities than those which do not invest in the same industry.

  20. Dependence of River Network Scaling and Geomorphic Properties on Initial Conditions in Landscape Evolution Models

    Science.gov (United States)

    Poore, G. M.; Kieffer, S. W.

    2008-12-01

    Initial conditions affect river network scaling and geomorphic properties, but the effect has not been systematically studied. Previous numerical and experimental studies have found that initial conditions affect river network drainage patterns, determining whether patterns are more parallel or more dendritic. They have also found that some network properties depend on initial conditions. We investigated the effect of initial conditions in the context of numerical models, using simulations of a stream power law. A common initial condition consists of a flat or sloping surface combined with random fluctuations in elevation. We used these initial conditions and focused on the effect of the magnitude of initial slope and the magnitude of initial randomness on standard network scaling and geomorphic properties, such as the Hack exponent, sinuosity, and hypsometry. Preliminary results indicate that some of the scaling and geomorphic properties show a strong dependence on initial conditions, while others exhibit little or no dependence. The strength of dependence can be sensitive to the statistical methods employed. Our results are relevant to numerical and analog modeling methodologies. The results suggest that initial conditions deserve greater consideration in attempts to understand the emergence of scaling in river networks.

  1. 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.

  2. Can one identify karst conduit networks geometry and properties from hydraulic and tracer test data?

    Science.gov (United States)

    Borghi, Andrea; Renard, Philippe; Cornaton, Fabien

    2016-04-01

    Karst aquifers are characterized by extreme heterogeneity due to the presence of karst conduits embedded in a fractured matrix having a much lower hydraulic conductivity. The resulting contrast in the physical properties of the system implies that the system reacts very rapidly to some changes in the boundary conditions and that numerical models are extremely sensitive to small modifications in properties or positions of the conduits. Furthermore, one major issue in all those models is that the location and size of the conduits is generally unknown. For all those reasons, estimating karst network geometry and their properties by solving an inverse problem is a particularly difficult problem. In this paper, two numerical experiments are described. In the first one, 18,000 flow and transport simulations have been computed and used in a systematic manner to assess statistically if one can retrieve the parameters of a model (geometry and radius of the conduits, hydraulic conductivity of the conduits) from head and tracer data. When two tracer test data sets are available, the solution of the inverse problems indicate with high certainty that there are indeed two conduits and not more. The radius of the conduits are usually well identified but not the properties of the matrix. If more conduits are present in the system, but only two tracer test data sets are available, the inverse problem is still able to identify the true solution as the most probable but it also indicates that the data are insufficient to conclude with high certainty. In the second experiment, a more complex model (including non linear flow equations in conduits) is considered. In this example, gradient-based optimization techniques are proved to be efficient for estimating the radius of the conduits and the hydraulic conductivity of the matrix in a promising and efficient manner. These results suggest that, despite the numerical difficulties, inverse methods should be used to constrain numerical

  3. The network and properties of the NR/SBR vulcanizate modified by electron beam irradiation

    Science.gov (United States)

    Shen, Jing; Wen, Shipeng; Du, Yishi; Li, Ning; Zhang, Liqun; Yang, Yusheng; Liu, Li

    2013-11-01

    A natural rubber/styrene butadiene rubber (NR/SBR) vulcanizate filled with carbon black was modified by high-energy electron beam (EB) irradiation in this work. The crosslinked structure was studied by a special chemical probe method. The influence of EB irradiation on mechanical properties, filler network, and dynamic properties including abrasion resistance, rolling resistance, and wet skid resistance was also investigated. The results revealed that the crosslink structure significantly changed after EB treatment, indicating that the amount of poly- and di-sulfide crosslinked bonds decreased and that of mono-sulfide bonds increased. The polymer-filler interaction was enhanced after EB irradiation. An EB dose of 600 kGy reduced the abrasion loss of the NR/SBR vulcanizate, and one of 300 kGy reduced the rolling resistance by 11.4%. Meanwhile, EB doses below 200 kGy had no obvious effect on the wet skid resistance. This EB-modified NR/SBR vulcanizate can be used to prepare high-performance tires with good abrasion resistance and low rolling resistance.

  4. Altered Topological Properties of Brain Networks in Social Anxiety Disorder: A Resting-state Functional MRI Study

    Science.gov (United States)

    Zhu, Hongru; Qiu, Changjian; Meng, Yajing; Yuan, Minlan; Zhang, Yan; Ren, Zhengjia; Li, Yuchen; Huang, Xiaoqi; Gong, Qiyong; Lui, Su; Zhang, Wei

    2017-01-01

    Recent studies involving connectome analysis including graph theory have yielded potential biomarkers for mental disorders. In this study, we aimed to investigate the differences of resting-state network between patients with social anxiety disorder (SAD) and healthy controls (HCs), as well as to distinguish between individual subjects using topological properties. In total, 42 SAD patients and the same number of HCs underwent resting functional MRI, and the topological organization of the whole-brain functional network was calculated using graph theory. Compared with the controls, the patients showed a decrease in 49 positive connections. In the topological analysis, the patients showed an increase in the area under the curve (AUC) of the global shortest path length of the network (Lp) and a decrease in the AUC of the global clustering coefficient of the network (Cp). Furthermore, the AUCs of Lp and Cp were used to effectively discriminate the individual SAD patients from the HCs with high accuracy. This study revealed that the neural networks of the SAD patients showed changes in topological characteristics, and these changes were prominent not only in both groups but also at the individual level. This study provides a new perspective for the identification of patients with SAD. PMID:28266518

  5. 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.

  6. Comparison of nanomechanical properties of in vivo and in vitro keratin 8/18 networks

    CERN Document Server

    Paust, Tobias; Nolte, Ulla; Beil, Michael; Herrmann, Harald; Marti, Othmar

    2015-01-01

    In our work we compare the mechanical properties of the extracted keratin cytoskeleton of pancreatic carcinoma cells with the mechanical properties of in vitro assembled keratin 8/18 networks. For this purpose we use microrheology measurements with embedded tracer beads. This method is a suitable tool, because the size of the beads compared to the meshsize of the network allows us to treat the network as a continuum. Observing the beads motion with a CCD-High-Speed-Camera then leads to the dynamic shear modulus. Our measurements show lower storage moduli with increasing distance between the rim of the nucleus and the bead, but no clear tendency for the loss modulus. The same measurement method applied to in vitro assembled keratin 8/18 networks shows different characteristics of storage and loss moduli. The storage modulus is one order of magnitude lower than that of the extracted cytoskeleton and the loss modulus is higher. We draw conclusions on the network topology of both keratin network types based on th...

  7. Analysis of wideband radio channel properties for planning of next-generation wireless networks

    NARCIS (Netherlands)

    Zhang, H.; Mantel, O.C.; Kwakkernaat, M.R.J.A.E.; Herben, M.

    2009-01-01

    This paper analyzes the application of wideband channel properties in the radio planning of wideband wireless networks. The definition and prediction of delay spread (DS) and angular spread (AS) are first discussed. A wideband high-resolution measurement campaign is then described which was

  8. Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks.

    Science.gov (United States)

    Szedlak, Anthony; Smith, Nicholas; Liu, Li; Paternostro, Giovanni; Piermarocchi, Carlo

    2016-06-01

    The diverse, specialized genes present in today's lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins' binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes' evolutionary properties. Slowly evolving ("cold"), old genes tend to interact with each other, as do rapidly evolving ("hot"), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN's community structures and its genes' evolutionary properties provide new perspectives for understanding evolutionary genetics.

  9. Structure-Property Relationships in Polycyanurate / Graphene Networks

    Science.gov (United States)

    2015-12-12

    AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NO. Air Force Research Laboratory (AFMC) AFRL/RQRP 10 E. Saturn Blvd. Edwards AFB, CA 93524-7680...ABSTRACT Unclassified c. THIS PAGE Unclassified SAR 18 19b. TELEPHONE NO (include area code ) N/A Standard Form 298 (Rev. 8-98) Prescribed by

  10. 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.

  11. Metabolic pathway of non-alcoholic fatty liver disease: Network properties and robustness

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2017-03-01

    Full Text Available Nonalcoholic fatty liver disease (NAFLD is a systematic and complex disease involving various cytokines/metabolites. In present article, we use methodology of network biology to analyze network properties of NAFLD metabolic pathway. It is found that the metabolic pathway of NAFLD is not a typical complex network with power-law degree distribution, p(x=x^(-4.4275, x>=5. There is only one connected component in the metabolic pathway. The calculated cut cytokines/metabolites of the metabolic pathway are SREBP-1c, ChREBP, ObR, AMPK, IRE1alpha, ROS, PERK, elF2alpha, ATF4, CHOP, Bim, CASP8, Bid, CxII, Lipogenic enzymes, XBP1, and FFAs. The most important cytokine/metabolite for possible network robustness is FFAs, seconded by TNF-alpha. It is concluded that FFAs is the most important cytokine/metabolite in the metabolic pathway, seconded by ROS. FFAs, LEP, ACDC, CYP2E1, and Glucose are the only cytokines/metabolites that affect others without influences from other cytokines/metabolites. Finally, the IDs matrix for identifying possible sub-networks/modules is given. However, jointly combining the results of connectedness analysis and sub-networks/modules identification, we hold that there are not significant sub-networks/modules in the pathway.

  12. Reversible Control of Network Properties in Azobenzene-Containing Hyaluronic Acid-Based Hydrogels.

    Science.gov (United States)

    Rosales, Adrianne M; Rodell, Christopher Blake; Chen, Minna H; Morrow, Matthew G; Anseth, Kristi S; Burdick, Jason A

    2018-02-06

    Biomimetic hydrogels fabricated from biologically-derived polymers, such as hyaluronic acid (HA), are useful for numerous biomedical applications. Due to the dynamic nature of biological processes, it is of great interest to synthesize hydrogels with dynamically tunable network properties where various functions (e.g., cargo delivery, mechanical signaling) can be changed over time. Among the various stimuli developed to control hydrogel properties, light stands out for its exquisite spatiotemporal control; however, most light-based chemistries are unidirectional in their ability to manipulate network changes. Here, we report a strategy to reversibly modulate HA hydrogel properties with light, using supramolecular crosslinks formed via azobenzene bound to β-cyclodextrin. Upon isomerization with 365 nm or 400-500 nm light, the binding affinity between azobenzene and β-cyclodextrin changed and altered the network connectivity. The hydrogel mechanical properties depended on both the azobenzene modification and isomeric state (lower for cis state), with up to a 60% change in storage modulus with light exposure. Furthermore, the release of a fluorescently-labeled protein was accelerated with light exposure under conditions that were cytocompatible to encapsulated cells. These results indicate that the developed hydrogels may be suitable for applications in which temporal regulation of material properties is important, such as drug delivery or mechanobiology studies.

  13. Molecular network and chemical fragment-based characteristics of medicinal herbs with cold and hot properties from Chinese medicine.

    Science.gov (United States)

    Liang, Fei; Li, Li; Wang, Maolin; Niu, Xuyan; Zhan, Junping; He, Xiaojuan; Yu, Changyuan; Jiang, Miao; Lu, Aiping

    2013-07-30

    Chinese herbal medicines (HMs) is one of the great herbal systems of the world, which play an important role in current health care system in many countries. In the view of tradition Chinese medicine (TCM) theory, Yin-yang and five-elements theory is the central theory, which is used to explain how the world and body work. Under the guidance of such philosophy, TCM considers that HMs have different properties, which are the important factors for prescribing herbal formulae; such prescriptions are based on TCM pattern classification in clinical practice. The cold and hot property are commonly defined for HM property identification; however, the biological activities that are related to the HM property remain a mystery because of a lack of appropriate methods. A bioinformatics approach was applied to identify the distinguishing biological activities of HMs that have these cold and hot properties. Twenty HMs with typical cold and hot properties (10 cold and 10 hot) were selected based on TCM clinical application records and Chinese pharmacopeia. The active target proteins of each HM were searched in the PubChem database and were analyzed in Ingenuity Pathway Analysis (IPA) platform to find out the HM property-related biological activities. In addition, the main compounds of the HMs were fragmented using a fragment-based approach and were analyzed for the purpose of deciphering the properties. The main biological networks of HMs with cold and hot properties include cell cycle, cellular growth, proliferation and development, cancer, cytokine signaling, and intracellular and second messenger signaling; 11 specific pathways are presented to be perturbed only by HMs with the hot property, and the 27 specific target protein molecules include PRKACA, PRKCA, PRKCB, PRKCD, PRKCE, PRKCG, PRKD1, TLR4, TLR7, TLR8, TLR9, HTR4, HTR6, HTR7, HTR2A, HTR1B, HTR2B, GNAO1, GNAI1, TNF, IL8, ROCK2, AKT1, MAPK1, RPS6KA1, RPS6KA3 and JAK2, which are involved in the biological network. One

  14. 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.

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

    NARCIS (Netherlands)

    Nguyen, Q.D.; Elwenspoek, Michael Curt

    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

  16. Properties of kinetic transition networks for atomic clusters and glassy solids.

    Science.gov (United States)

    Morgan, John W R; Mehta, Dhagash; Wales, David J

    2017-09-27

    A database of minima and transition states corresponds to a network where the minima represent nodes and the transition states correspond to edges between the pairs of minima they connect via steepest-descent paths. Here we construct networks for small clusters bound by the Morse potential for a selection of physically relevant parameters, in two and three dimensions. The properties of these unweighted and undirected networks are analysed to examine two features: whether they are small-world, where the shortest path between nodes involves only a small number or edges; and whether they are scale-free, having a degree distribution that follows a power law. Small-world character is present, but statistical tests show that a power law is not a good fit, so the networks are not scale-free. These results for clusters are compared with the corresponding properties for the molecular and atomic structural glass formers ortho-terphenyl and binary Lennard-Jones. These glassy systems do not show small-world properties, suggesting that such behaviour is linked to the structure-seeking landscapes of the Morse clusters.

  17. Engineering interpenetrating network hydrogels as biomimetic cell niche with independently tunable biochemical and mechanical properties.

    Science.gov (United States)

    Tong, Xinming; Yang, Fan

    2014-02-01

    Hydrogels have been widely used as artificial cell niche to mimic extracellular matrix with tunable properties. However, changing biochemical cues in hydrogels developed-to-date would often induce simultaneous changes in mechanical properties, which do not support mechanistic studies on stem cell-niche interactions. Here we report the development of a PEG-based interpenetrating network (IPN), which is composed of two polymer networks that can independently and simultaneously crosslink to form hydrogels in a cell-friendly manner. The resulting IPN hydrogel allows independently tunable biochemical and mechanical properties, as well as stable and more homogeneous presentation of biochemical ligands in 3D than currently available methods. We demonstrate the potential of our IPN platform for elucidating stem cell-niche interactions by modulating osteogenic differentiation of human adipose-derived stem cells. The versatility of such IPN hydrogels is further demonstrated using three distinct and widely used polymers to form the mechanical network while keeping the biochemical network constant. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. 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.

  19. Prediction of Genetic Interactions Using Machine Learning and Network Properties.

    Science.gov (United States)

    Madhukar, Neel S; Elemento, Olivier; Pandey, Gaurav

    2015-01-01

    A genetic interaction (GI) is a type of interaction where the effect of one gene is modified by the effect of one or several other genes. These interactions are important for delineating functional relationships among genes and their corresponding proteins, as well as elucidating complex biological processes and diseases. An important type of GI - synthetic sickness or synthetic lethality - involves two or more genes, where the loss of either gene alone has little impact on cell viability, but the combined loss of all genes leads to a severe decrease in fitness (sickness) or cell death (lethality). The identification of GIs is an important problem for it can help delineate pathways, protein complexes, and regulatory dependencies. Synthetic lethal interactions have important clinical and biological significance, such as providing therapeutically exploitable weaknesses in tumors. While near systematic high-content screening for GIs is possible in single cell organisms such as yeast, the systematic discovery of GIs is extremely difficult in mammalian cells. Therefore, there is a great need for computational approaches to reliably predict GIs, including synthetic lethal interactions, in these organisms. Here, we review the state-of-the-art approaches, strategies, and rigorous evaluation methods for learning and predicting GIs, both under general (healthy/standard laboratory) conditions and under specific contexts, such as diseases.

  20. 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.

  1. Envelope periodic solutions for a discrete network with the Jacobi elliptic functions and the alternative (G'/G)-expansion method including the generalized Riccati equation

    Science.gov (United States)

    Tala-Tebue, E.; Tsobgni-Fozap, D. C.; Kenfack-Jiotsa, A.; Kofane, T. C.

    2014-06-01

    Using the Jacobi elliptic functions and the alternative ( G'/ G-expansion method including the generalized Riccati equation, we derive exact soliton solutions for a discrete nonlinear electrical transmission line in (2+1) dimension. More precisely, these methods are general as they lead us to diverse solutions that have not been previously obtained for the nonlinear electrical transmission lines. This study seeks to show that it is not often necessary to transform the equation of the network into a well-known differential equation before finding its solutions. The solutions obtained by the current methods are generalized periodic solutions of nonlinear equations. The shape of solutions can be well controlled by adjusting the parameters of the network. These exact solutions may have significant applications in telecommunication systems where solitons are used to codify or for the transmission of data.

  2. Properties of a new small-world network with spatially biased random shortcuts

    Science.gov (United States)

    Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

    2017-11-01

    This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

  3. Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials.

    Science.gov (United States)

    Asteris, Panagiotis G; Roussis, Panayiotis C; Douvika, Maria G

    2017-06-09

    This work presents a soft-sensor approach for estimating critical mechanical properties of sandcrete materials. Feed-forward (FF) artificial neural network (ANN) models are employed for building soft-sensors able to predict the 28-day compressive strength and the modulus of elasticity of sandcrete materials. To this end, a new normalization technique for the pre-processing of data is proposed. The comparison of the derived results with the available experimental data demonstrates the capability of FF ANNs to predict with pinpoint accuracy the mechanical properties of sandcrete materials. Furthermore, the proposed normalization technique has been proven effective and robust compared to other normalization techniques available in the literature.

  4. Physical Properties and Hydrogen-Bonding Network of Water-Ethanol Mixtures from Molecular Dynamics Simulations.

    Science.gov (United States)

    Ghoufi, A; Artzner, F; Malfreyt, P

    2016-02-04

    While many numerical and experimental works were focused on water-ethanol mixtures at low ethanol concentration, this work reports predictions of a few physical properties (thermodynamical, interfacial, dynamical, and dielectrical properties) of water-ethanol mixture at high alcohol concentrations by means of molecular dynamics simulations. By using a standard force field a good agreement was found between experiment and molecular simulation. This was allowed us to explore the dynamics, structure, and interplay between both hydrogen-bonding networks of water and ethanol.

  5. Structures and electrical properties of pure and vacancy-included ZnO NWs of different sizes

    Science.gov (United States)

    Yu, Xiao-Xia; Zhou, Yan; Liu, Jia; Jin, Hai-Bo; Fang, Xiao-Yong; Cao, Mao-Sheng

    2015-12-01

    The structures and electronic properties of ZnO nanowires (NWs) of different diameters are investigated by employing the first-principles density functional theory. The results indicate that the oxygen vacancy (VO) exerts a more evident influence on the band gap of the ZnO NWs. However, the effect will be weakened with the increase of the diameter. In addition, the energy band shifts downward due to the existence of VO and the offset decreases with the reduction of the VO concentration. As the concentration of surface Zn atoms decreases, the conduction band shifts downward, while 2p electrons are lost in the oxygen vacancy, resulting in the split of valence band and the formation of an impurity level. Our findings agree well with the previous observations and will be of great importance for theoretical research based on ZnO NWs. Project supported by the National Natural Science Foundation of China (Grant Nos. 51132002 and 11574261) and the Natural Science Foundation of Hebei Province, China (Grant No. A2015203261).

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Gonzalez Rodriguez, Pablo; Dral, A Petra; van den Nieuwenhuijzen, Karin J H; Lette, Walter; Schipper, Dik J; Ten Elshof, Johan E

    2018-01-24

    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(triethoxysilyl)benzene 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.

  9. Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate

    Energy Technology Data Exchange (ETDEWEB)

    Fazlali, Alireza; Koranian, Parvaneh [Arak University, Arak (Iran, Islamic Republic of); Beigzadeh, Reza [Islamic Azad University, Kermanshah (Iran, Islamic Republic of); Rahimi, Masoud [Razi University, Kermanshah (Iran, Islamic Republic of)

    2013-09-15

    A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-random-two- liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.

  10. Comparisons of topological properties in autism for the brain network construction methods

    Science.gov (United States)

    Lee, Min-Hee; Kim, Dong Youn; Lee, Sang Hyeon; Kim, Jin Uk; Chung, Moo K.

    2015-03-01

    Structural brain networks can be constructed from the white matter fiber tractography of diffusion tensor imaging (DTI), and the structural characteristics of the brain can be analyzed from its networks. When brain networks are constructed by the parcellation method, their network structures change according to the parcellation scale selection and arbitrary thresholding. To overcome these issues, we modified the Ɛ -neighbor construction method proposed by Chung et al. (2011). The purpose of this study was to construct brain networks for 14 control subjects and 16 subjects with autism using both the parcellation and the Ɛ-neighbor construction method and to compare their topological properties between two methods. As the number of nodes increased, connectedness decreased in the parcellation method. However in the Ɛ-neighbor construction method, connectedness remained at a high level even with the rising number of nodes. In addition, statistical analysis for the parcellation method showed significant difference only in the path length. However, statistical analysis for the Ɛ-neighbor construction method showed significant difference with the path length, the degree and the density.

  11. Spatiotemporal memory is an intrinsic property of networks of dissociated cortical neurons.

    Science.gov (United States)

    Ju, Han; Dranias, Mark R; Banumurthy, Gokulakrishna; VanDongen, Antonius M J

    2015-03-04

    The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining optogenetics with microelectrode array recording, we show that these randomly organized cortical microcircuits are able to process complex spatiotemporal information, allowing the identification of a large number of temporal sequences and classification of musical styles. These experiments uncovered spatiotemporal memory processes lasting several seconds. Neural network simulations indicated that both short-term synaptic plasticity and recurrent connections are required for the emergence of this capability. Interestingly, NMDA receptor function is not a requisite for these short-term spatiotemporal memory processes. Indeed, blocking the NMDA receptor with the antagonist APV significantly improved the temporal processing ability of the networks, by reducing spontaneously occurring network bursts. These highly synchronized events have disastrous effects on spatiotemporal information processing, by transiently erasing short-term memory. These results show that the ability to process and integrate complex spatiotemporal information is an intrinsic property of generic cortical networks that does not require specifically designed circuits. Copyright © 2015 the authors 0270-6474/15/354040-12$15.00/0.

  12. Lack of "obesity paradox" in patients presenting with ST-segment elevation myocardial infarction including cardiogenic shock: a multicenter German network registry analysis.

    Science.gov (United States)

    Akin, Ibrahim; Schneider, Henrik; Nienaber, Christoph A; Jung, Werner; Lübke, Mike; Rillig, Andreas; Ansari, Uzair; Wunderlich, Nina; Birkemeyer, Ralf

    2015-07-11

    Studies have associated obesity with better outcomes in comparison to non-obese patients after elective and emergency coronary revascularization. However, these findings might have been influenced by patient selection. Therefore we thought to look into the obesity paradox in a consecutive network STEMI population. The database of two German myocardial infarction network registries were combined and data from a total of 890 consecutive patients admitted and treated for acute STEMI including cardiogenic shock and cardiopulmonary resuscitation according to standardized protocols were analyzed. Patients were categorized in normal weight (≤24.9 kg/m(2)), overweight (25-30 kg/m(2)) and obese (>30 kg/m(2)) according to BMI. Baseline clinical parameters revealed a higher comorbidity index for overweight and obese patients; 1-year follow-up comparison between varying groups revealed similar rates of all-cause death (9.1 % vs. 8.3 % vs. 6.2 %; p = 0.50), major adverse cardiac and cerebrovascular [MACCE (15.1 % vs. 13.4 % vs. 10.2 %; p = 0.53)] and target vessel revascularization in survivors [TVR (7.0 % vs. 5.0 % vs. 4.0 %; p = 0.47)] with normal weight when compared to overweight or obese patients. These results persisted after risk-adjustment for heterogeneous baseline characteristics of groups. An analysis of patients suffering from cardiogenic shock showed no impact of BMI on clinical endpoints. Our data from two network systems in Germany revealed no evidence of an "obesity paradox"in an all-comer STEMI population including patients with cardiogenic shock.

  13. 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.

  14. Effect of Network Structure/Topology on Mechanical Properties of Crosslinked Polymers

    Science.gov (United States)

    Sharifi, Majid

    The interest in epoxy thermosetting polymers is widespread (e.g. Boeing 787 Dreamliner, windmill blades, automobiles, coatings, adhesives, etc.), and a demand still exists for improving toughness of these materials without degrading advantageous properties such as strength, modulus, and Tg. This study introduces novel approaches for improving the intrinsic mechanical characteristics of these polymers. The designed synthetic techniques focus on developing polymer materials with the same overall compositions but varying in network topologies, with distinct topological features in the size range of 5-50 nm, measured by SAXS and SEM. It was found that without altering chemical structure, the network topology of a dense thermoset can be engineered such that, under mechanical deformation, nano-cavities open and dissipate energy before rupturing covalent bonds, producing a tougher material without sacrificing strength, modulus, and even glass transition temperature. Modified structures also revealed higher resistance to fracture than the corresponding control structures. The major fracture mechanism responsible for the increased energy dissipation was found to be nano-cavitation. SEM images from the fracture surfaces showed clear cavities on the modified samples whereas none were seen on the fracture surface of the control samples. Overall, it was demonstrated that network topology can be used to tailor thermal and mechanical properties of thermosetting polymers. The experimental methodologies in this dissertation can directly and economically be applied to design polymeric materials with improved properties for desired applications. Although topology-based toughening was investigated on epoxy-amine polymers, the concept can be extended to most thermoset chemistries and perhaps to other brittle network forming materials.

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

    National Research Council Canada - National Science Library

    J. Jakubski; St. M. Dobosz; K. Major-Gabryś

    2013-01-01

    .... 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...

  16. Changes induced by sea level rise on network properties of restoration areas

    Science.gov (United States)

    Jiménez, Mirian; Castanedo, Sonia; Zhou, Zeng; Coco, Giovanni; Medina, Raúl

    2015-04-01

    Human actions have been reducing the natural domain of estuarine systems for centuries. In the past, estuaries were perceived as unhealthy areas, source of diseases, which were adapted to human use by drainage and heavy engineering. Our current understanding shows that estuaries are not sources of disease, but rich ecosystems that cover important ecosystem functions. They need to be restored to their natural state. However, restoration actions may induce morphological changes that may change the estuary current behavior. It is thus of the utmost importance to understand the morphodynamic changes induced by restoration actions, more so when the final aim is to predict these changes. Dikes have been the most used mean to enclose and drain areas of estuaries. In this work, we focus our attention on dike removal as a means to restore the areas enclosed by these dikes. Dikes may be removed completely, or only partially (opening one or several breaches), to allow the tidal flow to enter into the area to be restored. Morphodynamic effects of dike removal are simulated numerically using Delft3d. Different dike removal configurations are studied and their effect on the recovery of the estuary quantified. Estuarine tidal networks are characterized by means of a new approach that links network connectivity to the spatial hydrodynamic fields developed in the estuary. The impact of different restorations strategies in the drainage properties of the network has been studied in the short term (5 -10 years) and in the long term (100 years) allowing the connectivity to evolve with time. Results show, for different scenarios, differences not only in the spatial distribution of the tidal network but also in statistical characteristics after different dike removal actions. The new distribution of channels will have implications for the location of the tidal flats, flood patterns and thus biological environments within the tidal networks. These changes in the morphological properties

  17. 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.

  18. Probing the Topological Properties of Complex Networks Modeling Short Written Texts

    Science.gov (United States)

    Amancio, Diego R.

    2015-01-01

    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. PMID:25719799

  19. 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.

  20. 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.

  1. Prediction of Henry's law constants by a quantitative structure property relationship and neural networks.

    Science.gov (United States)

    English, N J; Carroll, D G

    2001-01-01

    Multiple linear regression analysis and neural networks were employed to develop predictive models for Henry's law constants (HLCs) for organic compounds of environmental concern in pure water at 25 degrees C, using a set of quantitative structure property relationship (QSPR)-based descriptors to encode various molecular structural features. Two estimation models were developed from a set of 303 compounds using 10 and 12 descriptors, one of these models using two descriptors to account for hydrogen-bonding characteristics explicitly; these were validated subsequently on an external set of 54 compounds. For each model, a linear regression and neural network version was prepared. The standard errors of the linear regression models for the training data set were 0.262 and 0.488 log(H(cc)) units, while those of the neural network analogues were lower at 0.202 and 0.224, respectively; the linear regression models explained 98.3% and 94.3% of the variance in the development data, respectively, the neural network models giving similar quality results of 99% and 98.3%, respectively. The various descriptors used describe connectivity, charge distribution, charged surface area, hydrogen-bonding characteristics, and group influences on HLC values.

  2. Electrical properties of carbon-nanotube-network transistors in air after gamma irradiation

    Science.gov (United States)

    Ishii, Satoshi; Yabe, Daisuke; Enomoto, Shotaro; Koshio, Shigeru; Konishi, Teruaki; Hamano, Tsuyoshi; Hirao, Toshio

    2017-02-01

    We experimentally evaluate the electrical properties of carbon nanotube (CNT)-network transistors before and after 60Co gamma-ray irradiation up to 50 kGy in an air environment. When the total dose is increased, the degree of the threshold voltage (Vth) shift towards positive gate voltages in the drain current-gate voltage (ID-VGS) characteristics decreases for total irradiation doses above 30 kGy, although it is constant below 30 kGy. From our analysis of the ID-VGS characteristics along with micro-Raman spectroscopy, the gamma-ray irradiation does not change the structure of the CNT network channel for total doses up to 50 kGy; it instead generates charge traps near the CNT/SiO2 gate insulator interfaces. These traps are located within the SiO2 layer and/or the adsorbate on the device surface. The positively charged traps near the CNT/SiO2 interface contribute less to the Vth shift than the interface dipoles at the CNT/metal electrode interfaces and the segment of the CNT network channel below doses of 30 kGy, while the contribution of the charge traps increases for total doses above 30 kGy. Our findings indicate the possibility of the application of CNT-network transistors as radiation detectors suitable for use in air for radiation doses above 30 kGy.

  3. Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks.

    Science.gov (United States)

    Bernazzani, Luca; Duce, Celia; Micheli, Alessio; Mollica, Vincenzo; Sperduti, Alessandro; Starita, Antonina; Tiné, Maria Rosaria

    2006-01-01

    In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the

  4. Closed-loop neuro-robotic experiments to test computational properties of neuronal networks.

    Science.gov (United States)

    Tessadori, Jacopo; Chiappalone, Michela

    2015-03-02

    Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed. Here an experimental system is introduced and described in which the activity of a neuronal element (i.e., a network of neurons extracted from embryonic mammalian hippocampi) is given context and used to control the movement of an artificial agent, while environmental information is fed back to the culture as a sequence of electrical stimuli. This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

  5. 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.

  6. 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.

  7. A Study of Multitype Library Cooperatives: Including Developments in the Southwest Michigan Library Network, Michigan, California and Texas, with References to New York State and Illinois.

    Science.gov (United States)

    Faibisoff, Sylvia G.

    This report reviews the activities, structure, and organization of the Southwest Michigan Library Network (SMLN) and provides a review of multitype networking in several other states, sources of funding, and issues in national networking. The SMLN is a cooperative group of 56 libraries located within the five counties of Allegan, Berrien, Cass,…

  8. Influence of Halide Solutions on Collagen Networks: Measurements of Physical Properties by Atomic Force Microscopy

    Directory of Open Access Journals (Sweden)

    Birgit Spitzer-Sonnleitner

    2016-01-01

    Full Text Available The influence of aqueous halide solutions on collagen coatings was tested. The effects on resistance against indentation/penetration on adhesion forces were measured by atomic force microscopy (AFM and the change of Young’s modulus of the coating was derived. Comparative measurements over time were conducted with halide solutions of various concentrations. Physical properties of the mesh-like coating generally showed large variability. Starting with a compact set of physical properties, data disperse after minutes. A trend of increase in elasticity and permeability was found for all halide solutions. These changes were largest in NaI, displaying a logical trend with ion size. However a correlation with concentration was not measured. Adhesion properties were found to be independent of mechanical properties. The paper also presents practical experience for AFM measurements of soft tissue under liquids, particularly related to data evaluation. The weakening in physical strength found after exposure to halide solutions may be interpreted as widening of the network structure or change in the chemical properties in part of the collagen fibres (swelling. In order to design customized surface coatings at optimized conditions also for medical applications, halide solutions might be used as agents with little impact on the safety of patients.

  9. Influence of Halide Solutions on Collagen Networks: Measurements of Physical Properties by Atomic Force Microscopy.

    Science.gov (United States)

    Spitzer-Sonnleitner, Birgit; Kempe, André; Lackner, Maximilian

    2016-01-01

    The influence of aqueous halide solutions on collagen coatings was tested. The effects on resistance against indentation/penetration on adhesion forces were measured by atomic force microscopy (AFM) and the change of Young's modulus of the coating was derived. Comparative measurements over time were conducted with halide solutions of various concentrations. Physical properties of the mesh-like coating generally showed large variability. Starting with a compact set of physical properties, data disperse after minutes. A trend of increase in elasticity and permeability was found for all halide solutions. These changes were largest in NaI, displaying a logical trend with ion size. However a correlation with concentration was not measured. Adhesion properties were found to be independent of mechanical properties. The paper also presents practical experience for AFM measurements of soft tissue under liquids, particularly related to data evaluation. The weakening in physical strength found after exposure to halide solutions may be interpreted as widening of the network structure or change in the chemical properties in part of the collagen fibres (swelling). In order to design customized surface coatings at optimized conditions also for medical applications, halide solutions might be used as agents with little impact on the safety of patients.

  10. Optical properties of mineral dust aerosol including analysis of particle size, composition, and shape effects, and the impact of physical and chemical processing

    Science.gov (United States)

    Alexander, Jennifer Mary

    Atmospheric mineral dust has a large impact on the earth's radiation balance and climate. The radiative effects of mineral dust depend on factors including, particle size, shape, and composition which can all be extremely complex. Mineral dust particles are typically irregular in shape and can include sharp edges, voids, and fine scale surface roughness. Particle shape can also depend on the type of mineral and can vary as a function of particle size. In addition, atmospheric mineral dust is a complex mixture of different minerals as well as other, possibly organic, components that have been mixed in while these particles are suspended in the atmosphere. Aerosol optical properties are investigated in this work, including studies of the effect of particle size, shape, and composition on the infrared (IR) extinction and visible scattering properties in order to achieve more accurate modeling methods. Studies of particle shape effects on dust optical properties for single component mineral samples of silicate clay and diatomaceous earth are carried out here first. Experimental measurements are modeled using T-matrix theory in a uniform spheroid approximation. Previous efforts to simulate the measured optical properties of silicate clay, using models that assumed particle shape was independent of particle size, have achieved only limited success. However, a model which accounts for a correlation between particle size and shape for the silicate clays offers a large improvement over earlier modeling approaches. Diatomaceous earth is also studied as an example of a single component mineral dust aerosol with extreme particle shapes. A particle shape distribution, determined by fitting the experimental IR extinction data, used as a basis for modeling the visible light scattering properties. While the visible simulations show only modestly good agreement with the scattering data, the fits are generally better than those obtained using more commonly invoked particle shape

  11. 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.

  12. 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.

  13. Modification of Polymer Network Properties through the Addition of Functional Nanogel Particles

    Science.gov (United States)

    Liu, JianCheng

    Multifunctional acrylic and methacrylic monomers have been widely applied in many photopolymerization applications to produce crosslinked polymers with advantages such as rapid curing, broad choices of commercially available monomers and desirable physical and mechanical properties. However, there still remain critical challenges for these materials during polymerization including limited conversion and early onset of gelation as well as the generation of significant polymerization shrinkage and stress. This thesis explores the effects of network property modification through the addition of polymeric nanoparticles or nanogels. In order to understand the relationship between nanogel structure and composite material properties, nanogels with different architectures and functionalities were studied during polymerization in terms of kinetics, shrinkage and stress reduction, mechanical performance and reaction mechanisms. Nanogel composite formulations were evaluated to understand the interaction between nanogel structure with the resin matrix during polymerization through adjustment of nanogel branching densities and reactivity of polymer chain ends. It was found that both the chemical crosslinking from reactive chain ends and physical entanglements of high branching density nanogels with the resin matrix dramatically could improve final material mechanical strength. The reductions in overall volumetric shrinkage and shrinkage stress were found to follow at least proportional behavior with respect to nanogel loading concentration while maintaining similar final conversion and modulus results compared with the control resin. Nanogels containing unique functionalities were designed in order to modify reaction mechanism during secondary polymerization. A nanogel containing an integrated photoinitiator and active chain-end RAFT groups was able to initiate secondary polymerization from the nanogel phase so that localized polymerization was achieved from the beginning of

  14. Properties of water and steam: Network, open, and interactive IT-resources

    Science.gov (United States)

    Ochkov, V. F.; Orlov, K. A.; Aleksandrov, A. A.; Ochkov, A. V.

    2015-05-01

    New tendencies in publishing data on the thermophysical properties of substances are considered taking as an example water and steam, substances used as the main working fluid in thermal and nuclear power engineering. The advantages and shortcomings of both the traditional approach to publishing data on the properties of substances in hard printed form and the modern one, according to which the data are published in electronic form on Internet websites, are pointed out. The important requirements for publishing data in electronic form are described: the data must be presented in the form of network open and interactive calculations with examples of using them. A critical analysis of the relevant Internet resources is given. Some aspects of the work conducted by the International Association on the Properties of Water and Steam (IAPWS) are described. Particular examples of possible ways in which modern IT-resources on calculating the properties of substances can be set up are given: a hard printed handbook, a calculation program for being installed on a computer, calculation documents for downloading from a website, and using server calculations based on the technologies Mathcad Calculation Server on the website of the Moscow Power Engineering Institute National Research University and SMath on the website of the Elsevier electronic publishing house.

  15. 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.

  16. 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

    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...... 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....

  17. 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.

  18. Spatiotemporal properties of sensory responses in vivo are strongly dependent on network context

    Directory of Open Access Journals (Sweden)

    Eugene F. Civillico

    2012-04-01

    Full Text Available Sensory responses in neocortex are strongly modulated by changes in brain state, such as those observed between sleep stages or attentional levels. However, the specific effects of network state changes on the spatiotemporal properties of sensory responses are poorly understood. The slow oscillation, which is observed in neocortex under ketamine-xylazine anesthesia and is characterized by alternating depolarization (up-states and hyperpolarizing (down-states phases, provides an opportunity to study the state-dependence of primary sensory responses in large networks. Here we show using voltage-sensitive dye imaging that multiple properties of whisker-evoked responses are highly dependent on their timing with regard to the ongoing oscillation. In both the up- and down-states, responses spread across large portions of the barrel field, although the up-state responses were reduced in total area due to their sparseness. The depolarizing response in the up-state showed a tendency to propagate along the rows, with an amplitude and slope favoring the higher-numbered arcs. In the up-state, but not in the down-state, the depolarizing response was followed by a hyperpolarizing wave with a consistent spatial structure. We measured the suppression of whisker-evoked responses by a preceding response at 100 ms, and found that suppression showed the same spatial asymmetry as the depolarization. Because the resting level of cells in the up-state is likely to be closer to that in the awake animal, we suggest that the polarities in signal propagation which we observed in the up-state could be used as computational mechanisms in the behaving animal. These results demonstrate the critical importance of ongoing network activity on the dynamics of sensory responses and their integration.

  19. Distinct kinetic pathways generate organogel networks with contrasting fractality and thixotropic properties.

    Science.gov (United States)

    Huang, Xiao; Raghavan, Srinivasa R; Terech, Pierre; Weiss, Richard G

    2006-11-29

    The kinetics of the isothermal transformation of sols, comprised of a low molecular-mass organogelator (LMOG) and an organic liquid, to their organogel phases have been followed by circular dichroism (CD), fluorescence, small angle neutron scattering (SANS), and rheological methods. The thixotropic properties (in the sense that severe shearing followed by rest lead to reestablishment of viscoelasticity) of the gels have been examined as well by rheological measurements. The compositions of the samples were either 5alpha-cholestan-3beta-yl N-(2-naphthyl) carbamate (CNC) in an n-alkane (n-octane or n-dodecane) or 3beta-cholesteryl N-(2-naphthyl) carbamate (CeNC) in ethyl acetate. Values of Df, the mass fractal dimension of the microcrystalline self-assembled fibrillar networks (SAFINs) in the gels, have been extracted from the kinetic data using a model developed by Dickinson (J. Chem. Soc., Faraday Trans. 1997, 93, 111). The Df values, 1.1-1.3 for the CeNC gels and 1.3-1.4 or 1.6-1.8 (depending on the temperature of incubation of the sol phase) for CNC gels, are consistent with the gel network structures observed by optical microscopy. In addition, comparison of the temperature dependence of both n (the Avrami component) and K (the Avrami "rate constant") for CeNC/ethyl acetate gelation with those reported previously for gelation of CNC/n-alkane sols demonstrate that the very small change of a single bond in CNC to a double bond in CeNC causes significant differences in their gelation abilities and gel properties. The rheological measurements on CNC/n-alkane gels with spherulitic SAFIN units, formed by incubation of their sols at or =30 degrees C, leading to fiberlike SAFIN units, remain liquidlike after shearing regardless of the periods they are at rest. The time-dependent viscoelastic properties of the gel networks are treated according to a stretched exponential model. The observations from these studies provide detailed insights into the mechanisms of formation

  20. 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.

  1. 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

  2. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Diaconescu, Rodica-Mariana, E-mail: rodicamdiaconescu@yahoo.com [“Gheorghe Asachi” Technical University of Iasi, Faculty of Chemical Engineering and Environmental Protection, B-dul Prof.dr.doc. D. Mangeron 73, Iasi 700050 (Romania); Barbuta, Marinela, E-mail: barbuta31bmc@yahoo.com [“Gheorghe Asachi” Technical University of Iasi, Faculty of Civil Engineering and Services, B-dul Prof.dr.doc. D. Mangeron 1, Iasi 700050 (Romania); Harja, Maria, E-mail: maria_harja06@yahoo.com [“Gheorghe Asachi” Technical University of Iasi, Faculty of Chemical Engineering and Environmental Protection, B-dul Prof.dr.doc. D. Mangeron 73, Iasi 700050 (Romania)

    2013-11-20

    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.

  4. A note on some properties of an efficient network resource allocation mechanism

    Directory of Open Access Journals (Sweden)

    Fernando Beltrán

    2004-11-01

    Full Text Available Presentamos algunas propiedades límite de un mecanismo de asignación de recursos en redes conocido como la Subasta Progresiva de Segundo Precio (PSP. Este mecanismo busca asignar eficientemente recursos de red tales como ancho de banda y capacidad de buffer, en un ambiente caracterizado por usuarios que compiten; la subasta PSP busca resolver, o al menos aliviar, la congestión en una red exigiendo un intercambio de información entre el subastador y los usuarios sin mucha carga de señalización, y resolviendo el problema de la asignación de un recurso (teóricamente infinitamente divisible. La regla de asignación está inspirada en la subasta de segundo precio (Vickrey. Nuestro análisis de la subasta PSP explora sus propiedades límite, por ejemplo, cómo cambia la asignación en la presencia de un conjunto polarizado de usuarios. Esto último se refiere a una situación en la que los usuarios se dividen en dos grupos: unos con alta demanda y baja valoración por el recurso y otros con baja demanda y alta valoración. Mecanismos tales como las subastas se han vuelto muy populares para la asignación de recursos en redes que presentan congestión, tales como el acceso a servicios Internet. / We present some limiting properties of a network resource allocation mechanism known as the Progressive Second Price (PSP auction. This mechanism aims at efficiently allocate network resources, such as bandwidth or buffer capacity, in an environment characterized by competing users; the PSP auction seeks to solve or at least to ameliorate congestion in a network demanding a low signalling burden between the auctioneer and the users, and solving the allocation problem of an (theoretically infinitely divisible resource. The allocation rule is inspired in the second price (Vickrey auction. Our analysis of the PSP auction explores its limiting properties, namely, how the allocation changes in the presence of a polarized set of users. A polarized set of

  5. Structural and electronic properties of lead sulfide quantum dots from screened hybrid density functional calculations including spin-orbit coupling effects

    OpenAIRE

    Márquez Cruz, Antonio Marcial; Pacheco, Laura C.; Fernández Sanz, Javier

    2017-01-01

    We present in this work density functional theory calculations of the structural and electronic properties of (PbS)n nanoparticles with n=4-32. Particular care has been taken on the correct description of their electronic structure by using a hybrid functional including the spin-orbit coupling effects. We demonstrate that the bonding in PbS nanoparticles is quite different from bulk PbS as the six Pb-S bonds around a single Pb atom are found to have a different character while in bulk PbS all...

  6. 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...

  7. 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...

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

    Science.gov (United States)

    Trentin, Edmondo; Lusnig, Luca; Cavalli, Fabio

    2017-10-18

    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.

  9. Inclusion mechanical property estimation using tactile images, finite element method, and artificial neural network.

    Science.gov (United States)

    Lee, Jong-Ha; Won, Chang-Hee

    2011-01-01

    In this paper, we developed a methodology for estimating three parameters of tissue inclusion: size, depth, and Young's modulus from the tactile data obtained at the tissue surface with the tactile sensation imaging system. The estimation method consists of the forward algorithm using finite element method, and inversion algorithm using artificial neural network. The forward algorithm is designed to comprehensively predict the tactile data based on the mechanical properties of the tissue inclusion. This forward information is used to develop an inversion algorithm that will be used to extract the size, depth, and Young's modulus of a tissue inclusion from the tactile image. The proposed method is then validated with custom made tissue phantoms with matching elasticities of typical human breast tissues. The experimental results showed that the proposed estimation method estimates the size, depth, and Young's modulus of tissue inclusions with root mean squared errors of 1.25 mm, 2.09 mm, and 28.65 kPa, respectively.

  10. 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

    ) 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...... a need for specific hydraulic functions for peat soil. The 2RAL model for Dg agreed well with measured data, and performed better than existing unimodal models. To facilitate use of the 2RAL for Dg, we developed a simple predictive expression for Dg at the reference point. The pore-network tortuosity......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...

  11. Neural Network (NN) retrievals of Stratocumulus cloud properties using multi-angle polarimetric observations during ORACLES

    Science.gov (United States)

    Segal-Rosenhaimer, M.; Knobelspiesse, K. D.; Redemann, J.; Cairns, B.; Alexandrov, M. D.

    2016-12-01

    The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the South-East Atlantic during the Austral Spring for three consecutive years from 2016-2018. The study area encompasses one of the Earth's three semi-permanent subtropical Stratocumulus (Sc) cloud decks, and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), but still challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe a new algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER-2 and P-3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrieval scheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a more realistic representation of the signals. Before introducing the input variables to the network, the signals are projected

  12. Thermoelectric Properties and Band Structure Calculations of Novel Boron Network Compounds

    Science.gov (United States)

    Mori, Takao; Nishimura, Toshiyuki; Grin, Yuri; Shishido, Toetsu; Nakajima, Kazuo

    2009-03-01

    Boron is an interesting element, tending to form atomic networks such as 2D atomic nets and clusters, with some analogy to carbon systems which have been more extensively studied. Boron has one less electron than carbon and thus is electron deficient when forming atomic networks, but this causes it to have a special affinity with the rare earth elements and as a result, many new compounds have recently been discovered [1]. Their potential as viable thermoelectric materials is attracting interest since they are high-temperature materials and possess intrinsic low thermal conductivity, with some compounds exhibiting Seebeck coefficients in excess of 200 μV/K above 1000 K. The thermoelectric properties and band structure calculations of novel borides such as RB44Si2, RB17CN, RB22C2N, RB28.5C4 will be presented. Features in the band structure near the Fermi level indicate large doping effects in these compounds. Various doping experiments were carried out resulting in large increases to the figure of merit. [1] T. Mori, ``Higher Borides,'' in: Handbook on the Physics and Chemistry of Rare Earths, Vol. 38, (North-Holland, Amsterdam, 2008) p. 105-173.

  13. Emergent properties of extracellular vesicles: a holistic approach to decode the complexity of intercellular communication networks.

    Science.gov (United States)

    Gho, Yong Song; Lee, Changjin

    2017-06-27

    Shedding of nano-sized bilayered extracellular vesicles and extracellular vesicle-mediated intercellular communication are evolutionarily conserved biological processes. Communication between cells and the environment is an essential process in living organisms and dysregulation of intercellular communication leads to various diseases. Thus, systematic studies on extracellular vesicles, also known as exosomes, microvesicles, and outer membrane vesicles, are critical for a deeper understanding of intercellular communication networks that are crucial for decoding the exact causes of various difficult-to-cure diseases. Recent progress in this emerging field reveals that extracellular vesicles are endogenous carriers of specific subsets of proteins, mRNAs, miRNAs, and other bioactive materials, as well as play diverse pathophysiological roles. However, certain issues regarding diverse subtypes and the complex pathophysiological roles of extracellular vesicles are not yet clearly elucidated. In this review, we first briefly introduce the complexity of extracellular vesicles in terms of their vesicular cargos and protein-protein interaction networks, their diverse subtypes, and multifaceted pathophysiological functions. Then, we introduce the limitation of reductionist approaches in understanding the complexity of extracellular vesicles. We finally suggest that molecular systems biology approaches based on the concept of emergent properties are essential for a comprehensive understanding of the complex pathophysiological functions of heterogeneous extracellular vesicles, either at the single vesicle level or at a systems level as a whole.

  14. 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.

  15. 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

    2011-09-29

    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.

  16. A new computational strategy for identifying essential proteins based on network topological properties and biological information.

    Science.gov (United States)

    Qin, Chao; Sun, Yongqi; Dong, Yadong

    2017-01-01

    Essential proteins are the proteins that are indispensable to the survival and development of an organism. Deleting a single essential protein will cause lethality or infertility. Identifying and analysing essential proteins are key to understanding the molecular mechanisms of living cells. There are two types of methods for predicting essential proteins: experimental methods, which require considerable time and resources, and computational methods, which overcome the shortcomings of experimental methods. However, the prediction accuracy of computational methods for essential proteins requires further improvement. In this paper, we propose a new computational strategy named CoTB for identifying essential proteins based on a combination of topological properties, subcellular localization information and orthologous protein information. First, we introduce several topological properties of the protein-protein interaction (PPI) network. Second, we propose new methods for measuring orthologous information and subcellular localization and a new computational strategy that uses a random forest prediction model to obtain a probability score for the proteins being essential. Finally, we conduct experiments on four different Saccharomyces cerevisiae datasets. The experimental results demonstrate that our strategy for identifying essential proteins outperforms traditional computational methods and the most recently developed method, SON. In particular, our strategy improves the prediction accuracy to 89, 78, 79, and 85 percent on the YDIP, YMIPS, YMBD and YHQ datasets at the top 100 level, respectively.

  17. 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.

  18. A new approach for estimation of PVT properties of pure gases based on artificial neural network model

    OpenAIRE

    A. R. Moghadassi; Parvizian,F.; Hosseini, S.M.; Fazlali,A. R.

    2009-01-01

    Equations of state are useful for description of fluid properties such as pressure-volume-temperature (PVT). However, the success estimation of such correlations depends mainly on the range of data which have originated. Therefore new models are highly required. In this work a new method is proposed based on Artificial Neural Network (ANN) for estimation of PVT properties of compounds. The data sets were collected from Perry's Chemical Engineers' Handbook. Different training schemes for the b...

  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. A network including PU.1, Vav1 and miR-142-3p sustains ATRA-induced differentiation of acute promyelocytic leukemia cells - a short report.

    Science.gov (United States)

    Grassilli, Silvia; Nika, Ervin; Lambertini, Elisabetta; Brugnoli, Federica; Piva, Roberta; Capitani, Silvano; Bertagnolo, Valeria

    2016-10-01

    Reduced expression of miR-142-3p has been found to be associated with the development of various subtypes of myeloid leukemia, including acute promyelocytic leukemia (APL). In APL-derived cells, miR-142-3p expression can be restored by all-trans retinoic acid (ATRA), which induces the completion of their maturation program. Here, we aimed to assess whether PU.1, essential for ATRA-induced gene transcription, regulates the expression of miR-142-3p in APL-derived cells and, based on the established cooperation between PU.1 and Vav1 in modulating gene expression, to evaluate the role of Vav1 in restoring the expression of miR-142-3p. ATRA-induced increases in PU.1 and Vav1 expression in APL-derived NB4 cells were counteracted with specific siRNAs, and the expression of miR-142-3p was measured by quantitative real-time PCR (qRT-PCR). The recruitment of PU.1 and/or Vav1 to the regulatory region of miR-142 was assessed by quantitative chromatin immunoprecipitation (Q-ChIP). Synthetic inhibitors or mimics for miR-142-3p were used to assess whether this miRNA plays a role in regulating the expression of PU.1 and/or Vav1. We found that the expression of miR-142-3p in differentiating APL-derived NB4 cells is dependent on PU.1, and that Vav1 is essential for the recruitment of this transcription factor to its cis-binding element on the miR-142 promoter. In addition, we found that in ATRA-treated NB4 cells miR-142-3p sustains agonist-induced increases in both PU.1 and Vav1. Our results suggest the existence of a Vav1/PU.1/miR-142-3p network that supports ATRA-induced differentiation in APL-derived cells. Since selective regulation of miRNAs may play a role in the future treatment of hematopoietic malignancies, our results may provide a basis for the development of new therapeutic strategies to restore the expression of miR-142-3p.

  1. Epidemiological modeling of Phytophthora ramorum: network properties of susceptible plant genera movements in the nursery sector of England and Wales

    Science.gov (United States)

    Marco Pautasso; Tom Harwood; Mike Shaw; Xiangming Xu; Mike Jeger

    2008-01-01

    Since the first finding of Phytophthora ramorum in the U.K. (on Viburnum tinus, 2002), the pathogen has been reported throughout the country on a variety of susceptible species both in the horticultural sector and in woodlands and historic gardens. The nursery network may have properties which affect the epidemic threshold for...

  2. 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…

  3. 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.

  4. A new approach for estimation of PVT properties of pure gases based on artificial neural network model

    Directory of Open Access Journals (Sweden)

    A. R. Moghadassi

    2009-03-01

    Full Text Available Equations of state are useful for description of fluid properties such as pressure-volume-temperature (PVT. However, the success estimation of such correlations depends mainly on the range of data which have originated. Therefore new models are highly required. In this work a new method is proposed based on Artificial Neural Network (ANN for estimation of PVT properties of compounds. The data sets were collected from Perry's Chemical Engineers' Handbook. Different training schemes for the back-propagation learning algorithm, such as; Scaled Conjugate Gradient (SCG, Levenberg-Marquardt (LM and Resilient back Propagation (RP methods were used. The accuracy and trend stability of the trained networks were tested against unseen data. The LM algorithm with sixty neurons in the hidden layer has proved to be the best suitable algorithm with the minimum Mean Square Error (MSE of 0.000606. The ANN's capability to estimate the PVT properties is one of the best estimating method with high performance.

  5. 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.

  6. 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.

  7. Ranking the quality of protein structure models using sidechain based network properties.

    Science.gov (United States)

    Ghosh, Soma; Vishveshwara, Saraswathi

    2014-01-01

    Determining the correct structure of a protein given its sequence still remains an arduous task with many researchers working towards this goal. Most structure prediction methodologies result in the generation of a large number of probable candidates with the final challenge being to select the best amongst these. In this work, we have used Protein Structure Networks of native and modeled proteins in combination with Support Vector Machines to estimate the quality of a protein structure model and finally to provide ranks for these models. Model ranking is performed using regression analysis and helps in model selection from a group of many similar and good quality structures. Our results show that structures with a rank greater than 16 exhibit native protein-like properties while those below 10 are non-native like. The tool is also made available as a web-server ( http://vishgraph.mbu.iisc.ernet.in/GraProStr/native_non_native_ranking.html), where, 5 modelled structures can be evaluated at a given time.

  8. Structures and properties of PAX linked regulatory networks architecting and pacing the emergence of neuronal diversity.

    Science.gov (United States)

    Curto, Gloria G; Gard, Chris; Ribes, Vanessa

    2015-08-01

    Over the past two decades, Pax proteins have received a lot of attention from researchers working on the generation and assembly of neural circuits during vertebrate development. Through tissue or cell based phenotypic analyses, or more recently using genome-wide approaches, they have highlighted the pleiotropic functions of Pax proteins during neurogenesis. This review discusses the wide range of molecular and cellular mechanisms by which these transcription factors control in time and space the number and identity of neurons produced during development. We first focus on the position of Pax proteins within gene regulatory networks that generate patterns of cellular differentiation within the central nervous system. Next, the architecture of Pax-linked regulatory loops that provide a tempo of differentiation to progenitor cells is presented. Finally, we examine the molecular foundations providing a "multitasking" property to Pax proteins. Amongst the Pax factors that are expressed within the developing nervous system, Pax6 is the most extensively studied and thus holds a dominant position in this article. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Radio to microwave dielectric characterisation of constitutive electromagnetic soil properties using vector network analyses

    Science.gov (United States)

    Schwing, M.; Wagner, N.; Karlovsek, J.; Chen, Z.; Williams, D. J.; Scheuermann, A.

    2016-04-01

    The knowledge of constitutive broadband electromagnetic (EM) properties of porous media such as soils and rocks is essential in the theoretical and numerical modeling of EM wave propagation in the subsurface. This paper presents an experimental and numerical study on the performance EM measuring instruments for broadband EM wave in the radio-microwave frequency range. 3-D numerical calculations of a specific sensor were carried out using the Ansys HFSS (high frequency structural simulator) to further evaluate the probe performance. In addition, six different sensors of varying design, application purpose, and operational frequency range, were tested on different calibration liquids and a sample of fine-grained soil over a frequency range of 1 MHz-40 GHz using four vector network analysers. The resulting dielectric spectrum of the soil was analysed and interpreted using a 3-term Cole-Cole model under consideration of a direct current conductivity contribution. Comparison of sensor performances on calibration materials and fine-grained soils showed consistency in the measured dielectric spectra at a frequency range from 100 MHz-2 GHz. By combining open-ended coaxial line and coaxial transmission line measurements, the observable frequency window could be extended to a truly broad frequency range of 1 MHz-40 GHz.

  10. Geometric properties of a class of piecewise affine biological network models.

    Science.gov (United States)

    Farcot, Etienne

    2006-03-01

    The purpose of this report is to investigate some dynamical properties common to several biological systems. A model is chosen, which consists of a system of piecewise affine differential equations. Such a model has been previously studied in the context of gene regulation and neural networks, as well as biochemical kinetics. Unlike most of these studies, nonuniform decay rates and several thresholds per variable are assumed, thus considering a more realistic model. This model is investigated with the aid of a geometric formalism. We first provide an analysis of a continuous-space, discrete-time dynamical system equivalent to the initial one, by the way of a transition map. This is similar to former studies. Especially, the analysis of periodic trajectories is carried out in the case of multiple thresholds, thus extending previous results, which all concerned the restricted case of binary systems. The piecewise affine structure of such models is then used to provide a partition of the phase space, in terms of explicit cells. Allowed transitions between these cells define a language on a finite alphabet. Some words are proved to be forbidden in this language, thus improving the knowledge on such systems in terms of symbolic dynamics. More precisely, we show that taking these forbidden words into account leads to a dynamical system with strictly lower topological entropy. This holds for a class of systems, characterized by the presence of a splitting box, with additional conditions. We conclude after an illustrative three-dimensional example.

  11. Properties of Teacher Networks in Twitter: Are They Related to Community-Based Peer Production?

    Science.gov (United States)

    Macià, Maria; Garcia, Iolanda

    2017-01-01

    Teachers participate in social networking sites to share knowledge and collaborate with other teachers to create education-related content. In this study we selected several communities in order to better understand the networks that these participants establish in Twitter and the role that the social network plays in their activity within the…

  12. 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.

  13. Omega-3 fatty acid concentrate from Dunaliella salina possesses anti-inflammatory properties including blockade of NF-κB nuclear translocation.

    Science.gov (United States)

    Chitranjali, T; Anoop Chandran, P; Muraleedhara Kurup, G

    2015-02-01

    The health benefits of omega-3 polyunsaturated fatty acids (ω-3 PUFA), mainly eicosapentaenoic acid (EPA 20:5) and docosahexaenoic acid (DHA, 22:6), have been long known. Although various studies have demonstrated the health benefits of ω-3 PUFA, the mechanisms of action of ω-3 PUFAs are still not completely understood. While the major commercial source is marine fish oil, in this study we suggest the marine micro algae, Dunaliella salina as an alternate source of omega-3 fatty acids. Treatment with this algal omega-3 fatty acid concentrate (Ds-ω-3 FA) resulted in significant down-regulation of LPS-induced production of TNF-α and IL-6 by peripheral blood mononuclear cells (PBMCs). The concentrate was also found to be a potent blocker of cyclooxygenase (COX-2) and matrix metalloproteinase (MMP-2 and MMP-9) expression. The present study reveals the anti-inflammatory properties of Ds-ω-3 FA concentrate including the inhibition of NF-κB translocation.

  14. Properties of a pair of fracture networks produced by triaxial deformation experiments: insights on fluid flow using discrete fracture network models

    Science.gov (United States)

    Trullenque, Ghislain; Parashar, Rishi; Delcourt, Clément; Collet, Lucille; Villard, Pauline; Potel, Sébastien

    2017-05-01

    Results of a series of deformation experiments conducted on gabbro samples and numerical models for computation of flow are presented. Rocks were subjected to triaxial tests (σ1 > σ2 = σ3) under σ3 = 150 MPa confining pressure at room temperature, to generate fracture network patterns. These patterns were either produced by keeping a constant confining pressure and loading the sample up to failure (conventional test: CT), or by building up a high differential stress and suddenly releasing the confining pressure (confining pressure release test: CPR). The networks are similar in overall density but differ primarily in the orientation of smaller fractures. In the case of CT tests, a conjugate fracture set is observed with one dominant fracture zone running at about 20° from σ1. CPR tests do not show such a conjugate pattern and the mean fracture orientation is at around 35° from σ1. Discrete fracture network (DFN) methodology was used to determine the distribution of flow and hydraulic head for both fracture sets under simple boundary conditions and uniform transmissivity values. The fracture network generated by CT and CPR tests exhibit different patterns of flow field and hydraulic head configurations, but convey approximately the same amount of flow at all scales for which DFN models were simulated. The numerical modelling results help to develop understanding of qualitative differences in flow distribution that may arise in rocks of the same mineralogical composition and mechanical properties, but under the influence of different stress conditions, albeit at similar overall stress magnitude.

  15. Hybrid metal-coordinate transient networks: using bio-inspired building blocks to engineer the mechanical properties of physical hydrogels

    Science.gov (United States)

    Grindy, Scott; Barrett, Devin; Messersmith, Phillip; Holten-Andersen, Niels

    2014-03-01

    Recently, metal-coordinate complex crosslinks have been suggested to contribute to the self-healing properties of mussel byssi. Two specific amino acid derivatives - 3,4 dihydroxy-L-phenylalanine (dopa) and histidine (his) - are known to form coordinate complexes with trivalent and divalent ions (respectively) in aqueous solutions. We show here that, by functionalizing poly(ethylene glycol) polymers with dopa and his we are (1) able to characterize the fundamental kinetics and energetics of each specific metal-ligand pair using small amplitude oscillatory shear rheology and (2) create hybrid networks using various mixtures of metals and ligands. From this information, we can design gels with specific target mechanical properties by tailoring the amounts and types of metal-ligand crosslinks present in the gel network, resulting in the ability to engineer the mechanical relaxation spectrum. This work provides basic understanding necessary to intelligently design materials which incorporate metal-ligand crosslinks in more complex architectures.

  16. 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

  17. A reversible monoamine oxidase inhibitor, toloxatone: comparison of its physicochemical properties with those of other inhibitors including brofaromine, harmine, R40519 and moclobemide

    Energy Technology Data Exchange (ETDEWEB)

    Moureau, F.; Wouters, J.; Depas, M.; Vercauteren, D.P.; Durant, F. [Facultes Universitaires Notre-Dame de la Paix, Namur (Belgium); Ducrey, F.; Koenig, J.J.; Jarreau, F.X. [Synthelabo Recherche, 92 - Rueil-Malmaison (France)

    1995-12-31

    Reversible, competitive and selective monoamine oxidase A inhibitors (MAO{sub A}Is) are an exciting new type of anti-depressants with a safe profile. The mechanism for reversible inhibition of MAO{sub A} at the molecular level is still unknown. The planar structure of most reversible MAO{sub A}Is and the well-defined acceptor power of flavin adenine dinucleotide (FAD), the cofactor of the enzyme, suggest that MAO{sub A}Is exert their inhibitory effect through charge-transfer interactions with the FAD. This hypothesis has been evaluated for Toloxatone 1, the first reversible MAO-AI marketed in France. In this work, we give evidence for the ability of other reversible MAO{sub A}Is, including Brofaromine 2, Harmine 3 and R40519 4 to interact with the flavin cofactor in comparison with Moclobemide 5, and we underline the physicochemical properties required for these interactions. First, the formation of a complex between each of the MAO{sub A}Is and riboflavin, a model of the flavin cofactor, is shown by electronic absorption spectroscopy. Essential electronic describers of MAO{sub A}Is, such as the molecular electrostatic potential and the topology of the frontier orbitals, are then calculated by the ab initio Hartree-Fock method and compared with those of previously studied Toloxatone. This confirms the electronic absorption spectroscopy results. Finally, the similarities between the different MAO{sub A}Is are underlined and an interaction model is discussed on the basis of a detailed analysis of the electronic describers of all the considered MAO{sub A}Is and the flavin nucleus. (authors). 49 refs., 14 figs., 3 tabs.

  18. 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.

  19. Can Properties of Labor-Exchange Networks Explain the Resilience of Swidden Agriculture?

    Directory of Open Access Journals (Sweden)

    Sean S. Downey

    2010-12-01

    Full Text Available Despite the fact that swidden agriculture has been the subject of decades of research, questions remain about the extent to which it is constrained by demographic growth and if it can adapt to environmental limits. Here, social network analysis is used to analyze farmer labor-exchange networks within a chronosequence of five Q'eqchi' Maya villages where swidden agriculture is used. Results suggest that changes in land-use patterns, network structure, reciprocity rates, and levels of network hierarchy may increase the resilience of these villages to changes in the forest's agricultural productivity caused by ongoing agricultural activity. I analyze the suitability of subsistence- versus market-oriented agricultural labor for reciprocal labor exchange and develop a novel interpretation of labor reciprocity that highlights how unreciprocated exchanges, when they occur within the context of a network, may limit overexploitation of the forest. The variability observed in labor-exchange network structure across villages suggests that Q'eqchi' swidden can maintain its identity under changing conditions. This important characteristic of resilient systems is explored by analyzing a village case study where a serious demographic exodus dramatically impacted their labor network. The resulting picture of Q'eqchi' swidden agriculture is one of resilience rather than homeostasis. Reorganization of labor-exchange networks helps to maintain a village's cohesion, and ultimately this limits pioneer settlements and may slow overall rates of deforestation.

  20. Proteolytic degradation of the collagen network results in cartilage with inferior biomechanical properties

    NARCIS (Netherlands)

    Bank, R.A.; Koppele, J.M. te

    1999-01-01

    Swelling of cartilage, one of the early signs of osteoarthritis (OA), is considered to be the result of a collagen network that has lost its integrity. So far, no quantitative data directly support this assertion: combined measurements of the state of the collagen network per se and the degree of

  1. Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

    NARCIS (Netherlands)

    Maksimenko, V.A.; Lüttjohann, A.; Makarov, V.V.; Goremyko, M.V.; Koronovskii, A.A.; Nedaivozov, V.; Runnova, A.E.; Luijtelaar, E.L.J.M. van; Hramov, A.E.; Boccaletti, S.

    2017-01-01

    We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators which evolve

  2. 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 new...... industrial system based on biomass, an inexpensive, abundant and renewable raw material, is being established with sustainability as the main driving force [1]. The processing facilities for the production of multiple products (including biofuels and chemicals) from biomass are referred as biorefineries [2......]. 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...

  3. Three-dimensional xylem networks and phyllode properties of co-occurring Acacia.

    Science.gov (United States)

    Page, Gerald F M; Liu, Jie; Grierson, Pauline F

    2011-12-01

    Reduced leaf size is often correlated to increased aridity, where smaller leaves demand less water via xylem conduits. However, it is unknown if differences in three-dimensional (3D) xylem connectivity reflect leaf-level adaptations. We used X-ray microtomography (micro-CT) to quantify 3D xylem connectivity in ∼5 mm diameter branch sections of co-occurring semi-arid Acacia species of varied phyllode size. We compared 3D connectivity to minimum branch water potential and two-dimensional (2D) vessel attributes derived from sections produced by micro-CT. 2D attributes included vessel area, density, vessel size to number ratio (S) and vessel lumen fraction (F). Trees with terete phyllodes had less negative water potentials than broad phyllode variants. 3D xylem connectivity was conserved across all trees regardless of phyllode type or minimum water potential. We also found that xylem connectivity was sensitive to vessel lumen fraction (F) and not the size to number ratio (S) even though F was consistent among species and phyllode variants. Our results demonstrate that differences in phyllode anatomy, and not xylem connectivity, likely explain diversity of drought tolerance among closely related Acacia species. Further analysis using our approach across a broader range of species will improve understanding of adaptations in the xylem networks of arid zone species. © 2011 Blackwell Publishing Ltd.

  4. 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.

  5. Polyampholyte Ionomer Networks

    Science.gov (United States)

    Cavicchi, Kevin; Deng, Guodong

    Novel materials that can reversibly adapt to their environment are important as functional materials. In polymer networks, dynamic bonding of the crosslinks, which can break and reform under an external stimuli (e.g. heat or mechanical stress) are of interest for functional material properties (e.g. self-healing or shape memory) and enhanced mechanical properties (e.g. toughness, strength). One general route to introduce dynamic bonds is through non-covalent interactions. In this work, poly(butyl acrylate) networks crosslinked by vinyl benzyl tri-n-octyl ammonium/phosphonium styrene sulfonate ion pairs were prepared as model system to study the thermo-mechanical properties of polyampholyte networks as a function of the network parameters, including ion-pair chemistry and crosslink density. Results of rheological behavior, mechanical and thermal properties of these materials will be presented and compared to other ionic systems, such as ionomers with pendant counter ions.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. The effect of proline on the network structure of major ampullate silks as inferred from their mechanical and optical properties.

    Science.gov (United States)

    Savage, Ken N; Gosline, John M

    2008-06-01

    The silk that orb-weaving spiders produce for use as dragline and for the frame of the web is spun from the major ampullate (MA) glands, and it is renowned for its exceptional toughness. The fibroins that make up MA silk have previously been organized into two major groupings, spidroin-1 and spidroin-2, based largely on differences in amino acid sequence. The most apparent difference between spidroin-1 and spidroin-2 fibroins is the lack of proline in spidroin-1. The MA silk of Araneus diadematus comprises two spidroin-2 fibroins, and is therefore proline-rich, whereas spidroin-1 is preferentially expressed in Nephila clavipes MA silk, and so this silk is proline deficient. Together, these two silks provide a system for testing the consequences of proline-rich and proline-deficient fibroin networks. This study measures the mechanical and optical properties of dry and hydrated Araneus and Nephila MA silks. Since proline acts to disrupt secondary structure, it is hypothesized that the fibroin network of Araneus MA silk will contain less secondary structure than the network of Nephila MA silk. Mechanical and optical studies clearly support this hypothesis. Although the dry properties of these two silks are indistinguishable, there are large differences between the hydrated silks. Nephila silk does not swell upon hydration to the same degree as Araneus silk. In addition, upon hydration, Nephila MA silk retains more of its initial dry stiffness, and retains more molecular order, as indicated by birefringence measurements.

  12. Some properties of asymmetric Hopfield neural networks with finite time of transition between states

    Science.gov (United States)

    Suleimenov, Ibragim; Mun, Grigoriy; Panchenko, Sergey; Pak, Ivan

    2016-11-01

    There were implemented samples of asymmetric Hopfield neural networks which have finite time of transition from one state to another. It was shown that in such systems, various oscillation modes could occur. It was revealed that the oscillation of the output signal of certain neuron could be treated as extra logical variable, which describes the state of the neuron. Asymmetric Hopfield neural networks are described in terms of ternary logic. Such logic may be employed in image recognition procedure.

  13. Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily

    OpenAIRE

    Narayanan, Chitra; Gagn?, Donald; Reynolds, Kimberly A; Doucet, Nicolas

    2017-01-01

    In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNase tertiary structure into spatially distributed yet physically connected networks of co-evolving amino acids, termed sectors. Comparison of this statistics-based description with new NMR experiments data sh...

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Photo-Crosslinked Poly(ε-caprolactone fumarate) Networks for Peripheral Nerve Regeneration: Physical Properties and Preliminary Biological Evaluations

    Science.gov (United States)

    Wang, Shanfeng; Yaszemski, Michael J.; Knight, Andrew M.; Gruetzmacher, James A.; Windebank, Anthony J.; Lu, Lichun

    2010-01-01

    In an effort of achieving suitable biomaterials for peripheral nerve regeneration, we present a material design strategy of combining a crystallite-based physical network and a crosslink-based chemical network. Biodegradable polymer disks and conduits have been fabricated by photo-crosslinking three poly(ε-caprolactone fumarate)s (PCLF530, PCLF1250, and PCLF2000), which were synthesized from the precursor poly(ε-caprolactone) (PCL) diols with nominal molecular weights of 530, 1250, and 2000 g.mol−1, respectively. Thermal properties such as glass transition temperature (Tg), melting temperature (Tm), and crystallinity of photo-crosslinked PCLFs were examined and correlated with their rheological and mechanical properties. Furthermore, in vitro degradation of uncrosslinked and crosslinked PCLFs in PBS crosslinked PCLFs in 1 N NaOH aqueous solution at 37 °C was studied. In vitro cytocompatibility, attachment, and proliferation of Schwann cell precursor line SPL201 cells on three PCLF networks were investigated. Crosslinked PCLF2000 with the highest crystallinity and mechanical properties was found to best support cell attachment and proliferation. Using a new photo-crosslinking method, single-lumen crosslinked PCLF nerve conduits without defects were fabricated in a glass mold. Crosslinked PCLF2000 nerve conduits were selected for evaluation in a 1-cm gap rat sciatic nerve model. Histological evaluation demonstrated that the material was biocompatible with sufficient strength to hold sutures in place after 6 and 17 weeks of implantation. Nerve cable with myelinated axons was found in the crosslinked PCLF2000 nerve conduit. PMID:19171506

  1. On the properties of input-to-output transformations in neuronal networks.

    Science.gov (United States)

    Olypher, Andrey; Vaillant, Jean

    2016-06-01

    Information processing in neuronal networks in certain important cases can be considered as maps of binary vectors, where ones (spikes) and zeros (no spikes) of input neurons are transformed into spikes and no spikes of output neurons. A simple but fundamental characteristic of such a map is how it transforms distances between input vectors into distances between output vectors. We advanced earlier known results by finding an exact solution to this problem for McCulloch-Pitts neurons. The obtained explicit formulas allow for detailed analysis of how the network connectivity and neuronal excitability affect the transformation of distances in neurons. As an application, we explored a simple model of information processing in the hippocampus, a brain area critically implicated in learning and memory. We found network connectivity and neuronal excitability parameter values that optimize discrimination between similar and distinct inputs. A decrease of neuronal excitability, which in biological neurons may be associated with decreased inhibition, impaired the optimality of discrimination.

  2. 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.

  3. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou

    2016-04-01

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

  4. On PAC learning of functions with smoothness properties using feedforward sigmoidal networks

    Energy Technology Data Exchange (ETDEWEB)

    Rao, N.S.V.; Protopopescu, V.A.

    1996-04-01

    We consider Probably and Approximately Corrct (PAC) learning of an unknown function f: [0,1]{sup d} {r_arrow} [0,1], based on finite samples using feedforward sigmoidal networks. The unknown function f is chosen from the family F{intersection}C([0,1]{sup d}) or F{intersection}L{sup {infinity}}([0,1]{sup d}), where F has either bounded modulus of smoothness or bounded capacity or both. The learning sample is given by (X{sub 1},f(X{sub 1})),(X{sub 2},f(X{sub 2})),{hor_ellipsis},(X{sub n},f(X{sub n})), where X{sub 1},X{sub 2},{hor_ellipsis},X{sub n} are independently and identically distributed according to an unknown distribution. We consider the feedforward networks with a a single hidden layer of 1/(1 + e{sup {minus}{gamma}z})-units and bounded parameters, but the results can be extended to other neural networks where the hidden units satisfy suitable smoothness conditions. We analyze three function estimators based on nearest neighbor rule, local averaging, and Nadaraya-Watson estimator, all computed using the Haar system. It is shown that given a sufficiently large sample, each of these estimators approximates the best neural network to any given error with arbitrarily high probability. This result is crucical for establishing the essentially equivalent capabilities of neural networks and the above estimators for PAC learning from finite samples. Practical importance of this ``equivalence`` stems from the fact that computing a neural network which approximates the best possible one is computationally difficult, whereas the three estimators are linear-time computable in terms of sample size.

  5. What if CLIQUE were fast? Maximum Cliques in Information Networks and Strong Components in Temporal Networks

    OpenAIRE

    Rossi, Ryan A.; Gleich, David F.; Gebremedhin, Assefaw H.; Patwary, Md. Mostofa Ali

    2012-01-01

    Exact maximum clique finders have progressed to the point where we can investigate cliques in million-node social and information networks, as well as find strongly connected components in temporal networks. We use one such finder to study a large collection of modern networks emanating from biological, social, and technological domains. We show inter-relationships between maximum cliques and several other common network properties, including network density, maximum core, and number of trian...

  6. 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.

  7. Artificial Neural Network Prediction of Chemical-Disease Relationships using Readily Available Chemical Properties

    Science.gov (United States)

    2014-03-27

    solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 64, Supplement(0), 4-17. doi:10.1016/j.addr...2013). EPA/NSF Networks for Characterizing Chemical Lifecycle. Arlington, Virginia, U.S.A. Nguyen, T., Malley, R., Inkelis , S., & Kuppermann, N

  8. Mnemonic convergence in social networks: The emergent properties of cognition at a collective level.

    Science.gov (United States)

    Coman, Alin; Momennejad, Ida; Drach, Rae D; Geana, Andra

    2016-07-19

    The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.

  9. Synthesis and properties of photo-crosslinked mixed-macromer networks

    NARCIS (Netherlands)

    Zant, E.

    2015-01-01

    Regenerative medicine aims at replacing, engineering or regenerating human cells and tissues. There is a need for novel biomaterials to function as a temporal replacement of damaged tissues or organs. Synthetic biodegradable polymer networks can be such materials, since they offer benefits such as

  10. 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.

  11. Contribution of collagen network features to functional properties of engineered cartilage

    NARCIS (Netherlands)

    Bastiaansen-Jenniskens, Y.M.; Koevoet, W.; Bart, A.C.W. de; Linden, J.C. van der; Zuurmond, A.M.; Weinans, H.; Verhaar, J.A.N.; Osch, G.J.V.M. van; Groot, J. de

    2008-01-01

    Background: Damage to articular cartilage is one of the features of osteoarthritis (OA). Cartilage damage is characterised by a net loss of collagen and proteoglycans. The collagen network is considered highly important for cartilage function but little is known about processes that control

  12. Effect of polymerization conditions on the network properties of dex-HEMA microspheres and macro-hydrogels.

    Science.gov (United States)

    Chung, J T; Vlugt-Wensink, K D F; Hennink, W E; Zhang, Z

    2005-01-06

    Dextran-hydroxy-ethyl-methacrylate (dex-HEMA) hydrogels in the form of microspheres are an attractive system for the controlled delivery of protein drugs. In this work, the microspheres were prepared by a water-in-water emulsion polymerization process. The polymerization reaction was initiated by potassium peroxodisulfate (KPS) and catalyzed by N,N,N',N'-tetramethylethylenediamine (TEMED). The effect of the initiator concentration, reaction temperature and pH on the mechanical and network properties of the microspheres were investigated. The size and size distribution of the microspheres, equilibrium water content, and methacrylate conversion were also determined. The mechanical properties of single microspheres were measured by a micromanipulation technique and the rheological characteristics of the same material in the form of macroscopic hydrogel slabs were determined by a controlled stress rheometer. The results showed that the Young's moduli of the microspheres and of macroscopic slabs measured by these two methods were in good agreement. Higher KPS initiator concentrations resulted in a more rapid polymerization with a shorter gelation and lag time, and a higher Young's modulus of the gels. An increase in temperature also resulted in a more rapid polymerization with a shorter gelation and lag time. However, the Young's modulus of the gels decreased with an increase in polymerization temperature. The pH had no significant effect on the mechanical properties of the microspheres. This study demonstrates that the network properties of dex-HEMA hydrogels can be tailored by the polymerization conditions, which opens the possibility to modulate the release rate of entrapped compounds.

  13. Effects of cross-linking molecular weights in a hyaluronic acid-poly(ethylene oxide) hydrogel network on its properties

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Insup [Department of Chemical Engineering, Seoul National University of Technology, 172 Gongnung-dong, Nowon-gu, Seoul 139-743 (Korea, Republic of); Kim, Gun-Woo [Department of Chemical Engineering, Seoul National University of Technology, 172 Gongnung-dong, Nowon-gu, Seoul 139-743 (Korea, Republic of); Choi, Yoon-Jeong [Department of Chemical Engineering, Seoul National University of Technology, 172 Gongnung-dong, Nowon-gu, Seoul 139-743 (Korea, Republic of); Kim, Mi-Sook [Department of Chemical Engineering, Seoul National University of Technology, 172 Gongnung-dong, Nowon-gu, Seoul 139-743 (Korea, Republic of); Park, Yongdoo [Korea Artificial Organ Center, Korea University, Seoul 136-705 (Korea, Republic of); Lee, Kyu-Back [Korea Artificial Organ Center, Korea University, Seoul 136-705 (Korea, Republic of); Kim, In-Sook [Dental Research Institute, Seoul National University, Seoul 110-749 (Korea, Republic of); Hwang, Soon-Jung [Dental Research Institute, Seoul National University, Seoul 110-749 (Korea, Republic of); Tae, Giyoong [Department of Materials Science and Engineering, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of)

    2006-09-15

    We examined the effects of cross-linking molecular weights on the properties of a hyaluronic acid (HA)-poly(ethylene oxide) (PEO) hydrogel. Swelling behaviors, mechanical strength and rheological behaviors of the HA-PEO hydrogel were evaluated by employing different cross-linking molecular weights (100 kDa and 1.63 mDa) of the HAs in the hydrogel networks. The low molecular weight of HA was obtained in advance by treating high molecular weight HA with a hydrogen chloride solution. Methacrylation of HA was obtained by grafting aminopropylmethacrylate to its caroboxylic acid functional groups. While reduction of the HA molecular weights was confirmed by gel permeation chromatography, the degree of methacrylate grafting to the HA was measured by {sup 1}H-nuclear magnetic resonance. Synthesis of the HA-PEO hydrogel was successfully achieved via the Michael-type addition reaction between the methacrylate arm groups in the HA and the six thiol groups in PEO. The hydrogel formation was not dependent upon the HA molecular weights and its gelation behaviors were markedly different. Compared to the properties of the high molecular weight HA-based PEO one, the low molecular weight HA-based hydrogel induced quicker hydrogelation, as observed from the behaviors of the elastic and viscous modulus. Furthermore, the low molecular weight HA-based hydrogel demonstrated stronger mechanical properties as measured with a texture analyzer, lower water absorption as measured with a microbalance and smaller pore sizes on its surface and cross section as observed with scanning electron microscopy. The information about the effects of the cross-linking molecular weights of the gel network on the properties of the HA-based PEO hydrogel may lead to better design of hydrogels, especially in tissue engineering applications.

  14. 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.

  15. 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.

  16. 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;…

  17. 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.

  18. 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.

  19. Plane-wave-implementation of the k.p-formalism including strain and piezoelectricity to study the optoelectronic properties of semiconductor nanostructures

    Energy Technology Data Exchange (ETDEWEB)

    Marquardt, Oliver; Hickel, Tilmann; Neugebauer, Joerg [Max-Planck-Institut fuer Eisenforschung (Germany)

    2008-07-01

    Optical properties of semiconductor nanostructures such as quantum dots and wires are a direct consequence of their shape, size and material composition. The k.p formalism provides a real space approach to compute relevant parameters of nanostructures as e.g. needed to simulate optoelectronic devices such as light and laser emitting diodes. Contributions like strain and piezoelectric potentials entering the k.p formalism are typically calculated using continuum elasticity theory. We have reformulated this approach into a mixed real / reciprocal space formalism and implemented it into our plane-wave DFT-package S/Phi/nX. This allowed us to make efficient use of the existing highly optimized minimization routines as well as the efficient preconditioner techniques in a plane-wave basis set. We investigate different nanostructures with a focus on the III-nitride materials in the zincblende and wurtzite phase. A detailed comparison to approaches resolving fully the atomistic structure will be shown in order to verify the validity of our approach. Further the influence of the spin-orbital coupling which has been commonly neglected is shown to lift the artificial degeneracy of the hole ground state.

  20. Influence of Halide Solutions on Collagen Networks: Measurements of Physical Properties by Atomic Force Microscopy

    OpenAIRE

    Birgit Spitzer-Sonnleitner; André Kempe; Maximilian Lackner

    2016-01-01

    The influence of aqueous halide solutions on collagen coatings was tested. The effects on resistance against indentation/penetration on adhesion forces were measured by atomic force microscopy (AFM) and the change of Young's modulus of the coating was derived. Comparative measurements over time were conducted with halide solutions of various concentrations. Physical properties of the mesh-like coating generally showed large variability. Starting with a compact set of physical properties, data...

  1. Empirical Research on the Topological Properties of Internet+ Information Resources Network Nodes

    Directory of Open Access Journals (Sweden)

    Wu Bin

    2017-01-01

    Full Text Available The “Internet+” is the product of the Internet development, and its network topology isn’t the same as the traditional Internet. The relevance of the average daily visiting data and the daily page viewing data are studied empirically, the rich-club coefficient and the node access probability are redefined, and the topological entropy model to measure the degree of nodes information aggregation is built by using the entropy theory. The experimental results showed that the calculation model scaled the degree of information aggregation of the nodes in the “Internet+” topology efficiently. It provides an available computational model for the observation of resource access behaviors in the “Internet+” network.

  2. Studies of Properties of Pain Networks as Predictors of Targets of Stimulation for Treatment of Pain

    Science.gov (United States)

    2011-12-05

    humans may be uniquely useful to design and optimize anatomically based pain therapies , such as stimulation of the S1 or critical sites through...inter- connections (Churchland and Sejnowski, 1992; Arbib, 2002; Korzeniewska et al., 2008). THE “ PAIN NETWORK” AND STIMULATION EVOKED ANALGESIA Studies...al. Stimulation targets in pain networks or might augment behavioral therapies (Mohler, 2009) based upon their ability to influence I category firing

  3. Assessing Robustness Properties in Dynamic Discovery of Ad Hoc Network Services (Briefing Charts)

    Science.gov (United States)

    2001-10-04

    Task() start Aging Task() Serv ice Cache Manager() 0..1 Contains 1 Contains SERVICE MANAGER discov er Network Context() <<not shr>> Cache Manager...service availabilty requests 0..* 0..* service availability requests Service Manager Service Cache Manager Service User Service Description Service...Discovery Multicast Group Service Manager Service User Service Cache Manager Aggressive Discovery Multicast Group SM4 SCM3 T ATT API GUI 20

  4. Empirical Research on the Topological Properties of Internet+ Information Resources Network Nodes

    OpenAIRE

    Wu Bin; Wu Ping; Ma Ji-Tao; Guo Ting-Ting; Li Jun; Liu Wei

    2017-01-01

    The “Internet+” is the product of the Internet development, and its network topology isn’t the same as the traditional Internet. The relevance of the average daily visiting data and the daily page viewing data are studied empirically, the rich-club coefficient and the node access probability are redefined, and the topological entropy model to measure the degree of nodes information aggregation is built by using the entropy theory. The experimental results showed that the calculation model sca...

  5. 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.

  6. Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

    Science.gov (United States)

    Maksimenko, Vladimir A.; Lüttjohann, Annika; Makarov, Vladimir V.; Goremyko, Mikhail V.; Koronovskii, Alexey A.; Nedaivozov, Vladimir; Runnova, Anastasia E.; van Luijtelaar, Gilles; Hramov, Alexander E.; Boccaletti, Stefano

    2017-07-01

    We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators, which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied to getting a glance into the microscopic interactions occurring in a neurophysiological system, namely, in the thalamocortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities and to estimate the regions' participation in the generation of the different levels of consciousness.

  7. 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.

  8. 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.

  9. 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.

  10. 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 (p<0.1). Additionally, local network properties, such as local efficiency and the strength of connections, captured statistically significant (p<0.01) differences 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.

  11. [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.

  12. 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

  13. Synthesis, characterization, quantum chemical calculations and evaluation of antioxidant properties of 1,3,4-thiadiazole derivatives including 2- and 3-methoxy cinnamic acids

    Science.gov (United States)

    Gür, Mahmut; Muğlu, Halit; Çavuş, M. Serdar; Güder, Aytaç; Sayıner, Hakan S.; Kandemirli, Fatma

    2017-04-01

    A series of 1,3,4-thiadiazole derivatives including 2- and 3-methoxy cinnamic acids were synthesized, and their structures were elucidated by the UV, IR, 1H NMR, 13C NMR spectroscopies and elemental analysis. The UV and IR calculations of the molecules were performed by using B3LYP, HF and MP2 methods with selected 6-311++G(2d,2p), 6-311++G(3df,3pd) and cc-pvtz basis sets. Dipole moment, polarizability, chemical hardness/softness and electronegativity were also calculated and analyzed. Experimental FT-IR spectra and UV-Vis spectrum of the compounds were compared with theoretical data. Furthermore, antioxidant activities of the compounds were practised via different test methods such as 2,2-diphenyl-1-picryl-hydrazyl (DPPHrad), N,N-dimethyl-p-phenylenediamine (DMPDrad +), and 2,2‧-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTSrad +) scavenging activity assays. When compared with standards (BHA-Butylated hydroxyanisole, RUT-Rutin, and TRO-Trolox), it was observed that especially XIII and XIV which include methoxy groups at the o- and m-positions, respectively, had effective activities.

  14. Expansion of syndromic vaccine preventable disease surveillance to include bacterial meningitis and Japanese encephalitis: evaluation of adapting polio and measles laboratory networks in Bangladesh, China and India, 2007-2008.

    Science.gov (United States)

    Cavallaro, Kathleen F; Sandhu, Hardeep S; Hyde, Terri B; Johnson, Barbara W; Fischer, Marc; Mayer, Leonard W; Clark, Thomas A; Pallansch, Mark A; Yin, Zundong; Zuo, Shuyan; Hadler, Stephen C; Diorditsa, Serguey; Hasan, A S M Mainul; Bose, Anindya S; Dietz, Vance

    2015-02-25

    Surveillance for acute flaccid paralysis with laboratory confirmation has been a key strategy in the global polio eradication initiative, and the laboratory platform established for polio testing has been expanded in many countries to include surveillance for cases of febrile rash illness to identify measles and rubella cases. Vaccine-preventable disease surveillance is essential to detect outbreaks, define disease burden, guide vaccination strategies and assess immunization impact. Vaccines now exist to prevent Japanese encephalitis (JE) and some etiologies of bacterial meningitis. We evaluated the feasibility of expanding polio-measles surveillance and laboratory networks to detect bacterial meningitis and JE, using surveillance for acute meningitis-encephalitis syndrome in Bangladesh and China and acute encephalitis syndrome in India. We developed nine syndromic surveillance performance indicators based on international surveillance guidelines and calculated scores using supervisory visit reports, annual reports, and case-based surveillance data. Scores, variable by country and targeted disease, were highest for the presence of national guidelines, sustainability, training, availability of JE laboratory resources, and effectiveness of using polio-measles networks for JE surveillance. Scores for effectiveness of building on polio-measles networks for bacterial meningitis surveillance and specimen referral were the lowest, because of differences in specimens and techniques. Polio-measles surveillance and laboratory networks provided useful infrastructure for establishing syndromic surveillance and building capacity for JE diagnosis, but were less applicable for bacterial meningitis. Laboratory-supported surveillance for vaccine-preventable bacterial diseases will require substantial technical and financial support to enhance local diagnostic capacity. Published by Elsevier Ltd.

  15. The mechanical properties and cytotoxicity of cell-laden double-network hydrogels based on photocrosslinkable gelatin and gellan gum biomacromolecules

    Science.gov (United States)

    Shin, Hyeongho; Olsen, Bradley D.; Khademhosseini, Ali

    2012-01-01

    A major goal in the application of hydrogels for tissue engineering scaffolds, especially for load-bearing tissues such as cartilage, is to develop hydrogels with high mechanical strength. In this study, a double-network (DN) strategy was used to engineer strong hydrogels that can encapsulate cells. We improved upon previously studied double-network (DN) hydrogels by using a processing condition compatible with cell survival. The DN hydrogels were created by a two-step photocrosslinking using gellan gum methacrylate (GGMA) for the rigid and brittle first network, and gelatin methacrylamide (GelMA) for the soft and ductile second network. We controlled the degree of methacrylation of each polymer so that they obtain relevant mechanical properties as each network. The DN was formed by photocrosslinking the GGMA, diffusing GelMA into the first network, and photocrosslinking the GelMA to form the second network. The formation of the DN was examined by diffusion tests of the large GelMA molecules into the GGMA network, the resulting enhancement in the mechanical properties, and the difference in mechanical properties between GGMA/GelMA single networks (SN) and DNs. The resulting DN hydrogels exhibited the compressive failure stress of up to 6.9 MPa, which approaches the strength of cartilage. It was found that there is an optimal range of the crosslink density of the second network for high strength of DN hydrogels. DN hydrogels with a higher mass ratio of GelMA to GGMA exhibited higher strength, which shows promise in developing even stronger DN hydrogels in the future. Three dimensional (3D) encapsulation of NIH-3T3 fibroblasts and the following viability test showed the cell-compatibility of the DN formation process. Given the high strength and the ability to encapsulate cells, the DN hydrogels made from photocrosslinkable macromolecules could be useful for the regeneration of load-bearing tissues. PMID:22265786

  16. GraphCrunch: A tool for large network analyses

    Directory of Open Access Journals (Sweden)

    Pržulj Nataša

    2008-01-01

    specified list of machines on which to perform compute intensive searches for local network properties. Furthermore, GraphCrunch is easily extendible to include additional network measures and models. Conclusion GraphCrunch is a software tool that implements the latest research on biological network models and properties: it compares real-world networks against a series of random graph models with respect to a multitude of local and global network properties. We present GraphCrunch as a comprehensive, parallelizable, and easily extendible software tool for analyzing and modeling large biological networks. The software is open-source and freely available at http://www.ics.uci.edu/~bio-nets/graphcrunch/. It runs under Linux, MacOS, and Windows Cygwin. In addition, it has an easy to use on-line web user interface that is available from the above web page.

  17. GraphCrunch: a tool for large network analyses.

    Science.gov (United States)

    Milenković, Tijana; Lai, Jason; Przulj, Natasa

    2008-01-30

    compute intensive searches for local network properties. Furthermore, GraphCrunch is easily extendible to include additional network measures and models. GraphCrunch is a software tool that implements the latest research on biological network models and properties: it compares real-world networks against a series of random graph models with respect to a multitude of local and global network properties. We present GraphCrunch as a comprehensive, parallelizable, and easily extendible software tool for analyzing and modeling large biological networks. The software is open-source and freely available at http://www.ics.uci.edu/~bio-nets/graphcrunch/. It runs under Linux, MacOS, and Windows Cygwin. In addition, it has an easy to use on-line web user interface that is available from the above web page.

  18. Prenatal drug exposure to illicit drugs alters working memory-related brain activity and underlying network properties in adolescence.

    Science.gov (United States)

    Schweitzer, Julie B; Riggins, Tracy; Liang, Xia; Gallen, Courtney; Kurup, Pradeep K; Ross, Thomas J; Black, Maureen M; Nair, Prasanna; Salmeron, Betty Jo

    2015-01-01

    The persistence of effects of prenatal drug exposure (PDE) on brain functioning during adolescence is poorly understood. We explored neural activation to a visuospatial working memory (VSWM) versus a control task using functional magnetic resonance imaging (fMRI) in adolescents with PDE and a community comparison group (CC) of non-exposed adolescents. We applied graph theory metrics to resting state data using a network of nodes derived from the VSWM task activation map to further explore connectivity underlying WM functioning. Participants (ages 12-15 years) included 47 adolescents (27 PDE and 20 CC). All analyses controlled for potentially confounding differences in birth characteristics and postnatal environment. Significant group by task differences in brain activation emerged in the left middle frontal gyrus (BA 6) with the CC group, but not the PDE group, activating this region during VSWM. The PDE group deactivated the culmen, whereas the CC group activated it during the VSWM task. The CC group demonstrated a significant relation between reaction time and culmen activation, not present in the PDE group. The network analysis underlying VSWM performance showed that PDE group had lower global efficiency than the CC group and a trend level reduction in local efficiency. The network node corresponding to the BA 6 group by task interaction showed reduced nodal efficiency and fewer direct connections to other nodes in the network. These results suggest that adolescence reveals altered neural functioning related to response planning that may reflect less efficient network functioning in youth with PDE. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Sea Level Rise Impact on Drainage Network Properties following Restoration Activities

    Science.gov (United States)

    Jiménez Tobío, M.; Castanedo Bárcena, S.; Zhou, Z.; Coco, G.; Medina, R.; Rodriguez-Iturbe, I.

    2014-12-01

    For centuries estuarine systems have been losing portions of their natural domain as a consequence of human actions. In the past, estuaries were perceived as sources of disease, often drained or heavily engineered. Our current understanding shows that estuaries are instead rich ecosystems that need to be restored to their natural state. However, returning these areas into the tidal system may cause morphological changes on its present behavior. For this reason, it is important to understand, and attempt to predict, what morphodynamic changes an estuarine system may experience due to different restoration actions. In order to drain and use portions of the estuary, dikes are often built to disconnect them from the estuary. In this work we focus our attention on the restoration of these areas and specifically on dike removal. Dikes may be totally or partially removed to allow the tidal flow to enter into the area being restored. Morphodynamic effects of dike removal are computed numerically using Delft3d. Different dike removal configurations are studied and their effect on the recovery of the estuary quantified computing the probability distribution of drainage area and drainage volume. Tidal network characterization is carried out using a new approach that considers spatial hydrodynamic fields during a complete tidal cycle. Connectivity is thus allowed to evolve with time. The impact of different restorations strategies in the drainage area and volume of the network has been studied in the short term (5 -10 years) and in the long term (100 years). Results show the differences in tidal network characteristics after different dike removal actions for different scenarios. These differences are quantified with the new approach, allowing to highlight the changes that induce deep behavioral change in the system. The importance of sea level rise in these behavioral changes is also assessed in the study.

  20. 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.

  1. Influence of the base and diluent monomer on network characteristics and mechanical properties of neat resin and composite materials.

    Science.gov (United States)

    Fróes-Salgado, Nívea Regina de Godoy; Gajewski, Vinícius; Ornaghi, Bárbara Pick; Pfeifer, Carmem Silvia Costa; Meier, Marcia Margarete; Xavier, Tathy Aparecida; Braga, Roberto Ruggiero

    2015-05-01

    This study evaluated the effect of the combination of two dimethacrylate-based monomers [bisphenol A diglycidyl dimethacrylate (BisGMA) or bisphenol A ethoxylated dimethacrylate (BisEMA)] with diluents either derived from ethylene glycol dimethacrylate (ethylene glycol dimethacrylate, diethylene glycol dimethacrylate, triethylene glycol dimethacrylate, tetraethylene glycol dimethacrylate) or 1,10-decanediol dimethacrylate (D3MA) on network characteristics and mechanical properties of neat resin and composite materials. The degree of conversion, maximum rate of polymerization and water sorption/solubility of unfilled resins and the flexural strength and microhardness of composites (after 24 h storage in water and 3 months storage in a 75 vol% ethanol aqueous solution) were evaluated. Data were analyzed with two-way ANOVA and Tukey's test (α = 0.05). The higher conversion and lower water sorption presented by BisEMA co-polymers resulted in greater resistance to degradation in ethanol compared with BisGMA-based materials. In general, conversion and mechanical properties were optimized with the use of long-chain dimethacrylate derivatives of ethylene glycol. D3MA rendered more hydrophobic materials, but with relatively low conversion and mechanical properties.

  2. 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

  3. An artificial neural network model for the prediction of mechanical and barrier properties of biodegradable films.

    Science.gov (United States)

    Nobrega, Marcelo Medre; Bona, Evandro; Yamashita, Fabio

    2013-10-01

    Nowadays, the production of biodegradable starch-based films is of great interest because of the growing environmental concerns regarding pollution and the need to reduce dependence on the plastics industry. A broad view of the role of different components, added to starch-based films to improve their properties, is required to guide the future development. The self-organizing maps (SOMs) provide comparisons that initially were complicated due to the large volume of the data. Furthermore, the construction of a model capable of predicting the mechanical and barrier properties of these films will accelerate the development of films with improved characteristics. The water vapor permeability (WVP) analysis using the SOM algorithm showed that the presence of glycerol is very important for films with low amounts of poly (butylene adipate co-terephthalate) and confirms the role of the equilibrium relative humidity in the determination of WVP. Considering the mechanical properties, the SOM analysis emphasizes the important role of poly (butylene adipate co-terephthalate) in thermoplastic starch based films. The properties of biodegradable films were predicted and optimized by using a multilayer perceptron coupled with a genetic algorithm, presenting a great correlation between the experimental and theoretical values with a maximum error of 24%. To improve the response of the model and to ensure the compatibility of the components more information will be necessary. © 2013.

  4. 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.

  5. 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.

  6. 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 (aw), 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 aw 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 aw, 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, aw, 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.

  7. Experimental and Computational Studies of Cortical Neural Network Properties Through Signal Processing

    Science.gov (United States)

    Clawson, Wesley Patrick

    Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized using mutual information between sensory input, visual stimulus, and neural response,. The primary finding of our experiments in the visual cortex in turtles and neuronal network modeling confirms this theoretical prediction. We show that sensory discrimination is maximized when visual cortex operates near criticality. In addition to presenting this primary finding in detail, this thesis will also address our preliminary results on change-point-detection in experimentally measured cortical dynamics.

  8. Graphene networks with low percolation threshold in ABS nanocomposites: selective localization and electrical and rheological properties.

    Science.gov (United States)

    Gao, Chong; Zhang, Shimin; Wang, Feng; Wen, Bin; Han, Chunchun; Ding, Yanfen; Yang, Mingshu

    2014-08-13

    Acrylonitrile-butadiene-styrene resin (ABS)/graphene nanocomposites were prepared through a facile coagulation method. Because the chemical reduction of graphene oxide was in situ conducted in the presence of ABS at the dispersion stage, the aggregation of the graphene nanosheets was avoided. It was shown by transmission electron microscopy that the graphene nanosheets were selectively located and homogeneously dispersed in the styrene-acrylonitrile (SAN) phase. The electrical conductivity and linear viscoelastic behavior of the nanocomposites were systematically studied. With increasing filler content, graphene networks were established in the SAN phase. Consequently, the nanocomposites underwent a transition from electrical insulator to conductor at a percolation threshold of 0.13 vol %, which is smaller than that of other ABS composites. Such a low percolation threshold results from extreme geometry, selective localization, and homogeneous dispersion of the graphene nanosheets in SAN phase. Similarly, the rheological response of the nanocomposites also showed a transition to solid-like behavior. Due to the thermal reduction of graphene nanosheets and structure improvement of graphene networks, enhanced electrical conductivity of the nanocomposites was obtained after annealing.

  9. Geometrical properties of a discontinuity network in gneissic rock, a case study in high alpine terrain

    Science.gov (United States)

    Koppensteiner, Matthias; Zangerl, Christian

    2017-04-01

    For the purposes of estimating slope stability and investigating landslide formation processes, it is indispensable to obtain information about the discontinuity properties of the rock mass. These properties control failure processes, deformation behaviour and groundwater flow. Scanline measurements represent a systematic surveying method, however they make certain demands in case of natural outcorps in a high alpine terrain. The performance of the scanline method is tested and the thereby obtained and evaluated data is compared to findings from other studies. An area of a well exposed, fractured rock mass composed of granodioritic gneisses in the Oetztal-Stubai crytalline basement of the Alps (Austria) has been chosen to perform the investigations. Eight scanlines have been measured on a single hillside with varying lengths between 8 and 30 meters. The orientations of the scanlines have been varied in order to minimize the sampling bias associated with the angle between the scanlines and the intersected discontinuities. For every intersecting discontinuity at a certain tape length, the orientation, the trace length and the terminations of the trace have been recorded. Primarily, the discontinuity data from all scanlines have been analyzed with the software package Dips (Rocscience, 1989) in order to determine their allocation in sets. For the evaluation of the spacing and trace length properties, two scripts have been developed in the language Matlab (The MathWorks, 1984) to faciliate setwise processing of the entire dataset. Variation of the scanline directions and lengths returned homogeneous sample sizes for the individual discontinuity sets. Both, normal spacings and trace lengths show negative exponential distributions for all sets. A comparison of four different methods to estimate trace lengths show that the result is highly dependent on the chosen method itself. However, when the relation of the results for the respective sets within one of the methods is

  10. A neural network-based method for merging ocean color and Argo data to extend surface bio-optical properties to depth: Retrieval of the particulate backscattering coefficient

    Science.gov (United States)

    Sauzède, R.; Claustre, H.; Uitz, J.; Jamet, C.; Dall'Olmo, G.; D'Ortenzio, F.; Gentili, B.; Poteau, A.; Schmechtig, C.

    2016-04-01

    The present study proposes a novel method that merges satellite ocean color bio-optical products with Argo temperature-salinity profiles to infer the vertical distribution of the particulate backscattering coefficient (bbp). This neural network-based method (SOCA-BBP for Satellite Ocean-Color merged with Argo data to infer the vertical distribution of the Particulate Backscattering coefficient) uses three main input components: (1) satellite-based surface estimates of bbp and chlorophyll a concentration matched up in space and time with (2) depth-resolved physical properties derived from temperature-salinity profiles measured by Argo profiling floats and (3) the day of the year of the considered satellite-Argo matchup. The neural network is trained and validated using a database including 4725 simultaneous profiles of temperature-salinity and bio-optical properties collected by Bio-Argo floats, with concomitant satellite-derived products. The Bio-Argo profiles are representative of the global open-ocean in terms of oceanographic conditions, making the proposed method applicable to most open-ocean environments. SOCA-BBP is validated using 20% of the entire database (global error of 21%). We present additional validation results based on two other independent data sets acquired (1) by four Bio-Argo floats deployed in major oceanic basins, not represented in the database used to train the method; and (2) during an AMT (Atlantic Meridional Transect) field cruise in 2009. These validation tests based on two fully independent data sets indicate the robustness of the predicted vertical distribution of bbp. To illustrate the potential of the method, we merged monthly climatological Argo profiles with ocean color products to produce a depth-resolved climatology of bbp for the global ocean.

  11. INVESTIGATION OF FOSSIL FUEL AND LIQUID BIOFUEL BLEND PROPERTIES USING ARTIFICIAL NEURAL NETWORK

    OpenAIRE

    Najafi, G.; B Ghobadian; P. Nematizade

    2012-01-01

    Gasoline fuel is the baseline fuel in this research, to which bioethanol, biodiesel and diesel are additives. The fuel blends were prepared based on different volumes and following which, ASTM (American Society for Testing and Materials) test methods analysed some of the important properties of the blends, such as: density, dynamic viscosity, kinematic viscosity and water and sediment. Experimental data were analysed by means of Matlab software. The results obtained from artificial neural net...

  12. How the Statistical Validation of Functional Connectivity Patterns Can Prevent Erroneous Definition of Small-World Properties of a Brain Connectivity Network

    Directory of Open Access Journals (Sweden)

    J. Toppi

    2012-01-01

    Full Text Available The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. However, no common procedure is currently applied for extracting the adjacency matrix from a connectivity pattern. To understand how the topographical properties of a network inferred by means of graph indices can be affected by this procedure, we compared one of the methods extensively used in Neuroscience applications (i.e. fixing the edge density with an approach based on the statistical validation of achieved connectivity patterns. The comparison was performed on the basis of simulated data and of signals acquired on a polystyrene head used as a phantom. The results showed (i the importance of the assessing process in discarding the occurrence of spurious links and in the definition of the real topographical properties of the network, and (ii a dependence of the small world properties obtained for the phantom networks from the spatial correlation of the neighboring electrodes.

  13. Application of network properties and signal strength to identify face-to-face links in an electronic dataset

    CERN Document Server

    Sekara, Vedran

    2014-01-01

    Understanding how people interact and socialize is important in many contexts, from disease control to urban planning. Datasets that capture this specific aspect of human life have increased in size and availability over the last few years. We have yet to understand, however, to what extent such electronic datasets may serve as a valid proxy for real life face-to-face interactions. For an observational dataset, gathered by mobile phones, we attack the problem of identifying transient and non-important links, as well as how to highlight important interactions. Using the Bluetooth signal strength parameter to distinguish between observations, we demonstrate that weak links, compared to strong links, have a lower probability of being observed at later times, while such links--on average--also have lower link-weights and a lower probability of sharing an online friendship. Further, the role of link-strength is investigated in relation to social network properties.

  14. 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

  15. Statistical properties of Olami-Feder-Christensen model on Barabasi-Albert scale-free network

    Science.gov (United States)

    Tanaka, Hiroki; Hatano, Takahiro

    2017-12-01

    The Olami-Feder-Christensen model on the Barabasi-Albert type scale-free network is investigated in the context of statistical seismology. This simple model may be regarded as the interacting faults obeying power-law size distribution under two assumptions: (i) each node represents a distinct fault; (ii) the degree of a node is proportional to the fault size and the energy accumulated around it. Depending on the strength of an interaction, the toppling events exhibit temporal clustering as is ubiquitously observed for natural earthquakes. Defining a geometrical parameter that characterizes the heterogeneity of the energy stored in the nodes, we show that aftershocks are characterized as a process of regaining the heterogeneity that is lost by the main shock. The heterogeneity is not significantly altered during the loading process and foreshocks.

  16. Improved Antifouling Properties of Polydimethylsiloxane Films via Formation of Polysiloxane/Polyzwitterion Interpenetrating Networks.

    Science.gov (United States)

    Dundua, Alexander; Franzka, Steffen; Ulbricht, Mathias

    2016-12-01

    Nonspecific adsorption of proteins is a challenging problem for the development of biocompatible materials, as well as for antifouling and fouling-release coatings, for instance for the marine industry. The concept of preparing amphiphilic systems based on low surface energy hydrophobic materials via their hydrophilic modification is being widely pursued. This work describes a novel two-step route for the preparation of interpenetrating polymer networks of otherwise incompatible poly(dimethylsiloxane) and zwitterionic polymers. Changes in surface hydrophilicity as well as surface charge at different pH values are investigated. Characterization using atomic force microscopy provides thorough insight into surface changes upon hydrophilic modification. Protein fouling of the materials is assessed using fibrinogen as a model protein. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. 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

  18. Application of a Neural Network Model for Prediction of Wear Properties of Ultrahigh Molecular Weight Polyethylene Composites

    Directory of Open Access Journals (Sweden)

    Halil Ibrahim Kurt

    2015-01-01

    Full Text Available In the current study, the effect of applied load, sliding speed, and type and weight percentages of reinforcements on the wear properties of ultrahigh molecular weight polyethylene (UHMWPE was theoretically studied. The extensive experimental results were taken from literature and modeled with artificial neural network (ANN. The feed forward (FF back-propagation (BP neural network (NN was used to predict the dry sliding wear behavior of UHMWPE composites. Eleven input vectors were used in the construction of the proposed NN. The carbon nanotube (CNT, carbon fiber (CF, graphene oxide (GO, and wollastonite additives are the main input parameters and the volume loss is the output parameter for the developed NN. It was observed that the sliding speed and applied load have a stronger effect on the volume loss of UHMWPE composites in comparison to other input parameters. The proper condition for achieving the desired wear behaviors of UHMWPE by tailoring the weight percentage and reinforcement particle size and composition was presented. The proposed NN model and the derived explicit form of mathematical formulation show good agreement with test results and can be used to predict the volume loss of UHMWPE composites.

  19. 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.

  20. Discovering network structure beyond communities.

    Science.gov (United States)

    Nishikawa, Takashi; Motter, Adilson E

    2011-01-01

    To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest.

  1. Brain network properties in depressed patients receiving seizure therapy: A graph theoretical analysis of peri-treatment resting EEG.

    Science.gov (United States)

    Deng, Zhi-De; McClinctock, Shawn M; Lisanby, Sarah H

    2015-08-01

    Electroconvulsive therapy (ECT), the most efficacious antidepressant therapy for treatment-resistant depression, has been reported to alter functional brain network architecture by down-regulating connectivity in frontotemporal circuitry. Magnetic seizure therapy (MST), which induces therapeutic seizures with high dose repetitive transcranial magnetic stimulation, has been introduced to improve the seizure therapy risk/benefit ratio. Unfortunately, there is limited understanding of seizure therapy's underlying mechanisms of action. In this study, we apply graph theory-based connectivity analysis to peri-treatment, resting-state, topographical electroencephalography (EEG) in patients with depression receiving seizure therapy. Functional connectivity was assessed using the de-biased weighted phase lag index, a measure of EEG phase synchronization. Brain network structure was quantified using graph theory metrics, including betweenness centrality, clustering coefficient, network density, and characteristic path length. We found a significant reduction in the phase synchronization and aberration of the small-world architecture in the beta frequency band, which could be related to acute clinical and cognitive effects of seizure therapy.

  2. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

    Science.gov (United States)

    Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano

    2017-11-08

    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 ("mixed

  3. 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.

  4. Nonuniversality in the spectral properties of time-reversal-invariant microwave networks and quantum graphs.

    Science.gov (United States)

    Dietz, Barbara; Yunko, Vitalii; Białous, Małgorzata; Bauch, Szymon; Ławniczak, Michał; Sirko, Leszek

    2017-05-01

    We present experimental and numerical results for the long-range fluctuation properties in the spectra of quantum graphs with chaotic classical dynamics and preserved time-reversal invariance. Such systems are generally believed to provide an ideal basis for the experimental study of problems originating from the field of quantum chaos and random matrix theory. Our objective is to demonstrate that this is true only for short-range fluctuation properties in the spectra, whereas the observation of deviations in the long-range fluctuations is typical for quantum graphs. This may be attributed to the unavoidable occurrence of short periodic orbits, which explore only the individual bonds forming a graph and thus do not sense the chaoticity of its dynamics. In order to corroborate our supposition, we performed numerous experimental and corresponding numerical studies of long-range fluctuations in terms of the number variance and the power spectrum. Furthermore, we evaluated length spectra and compared them to semiclassical ones obtained from the exact trace formula for quantum graphs.

  5. Structure, mechanical property and corrosion behaviors of (HA+β-TCP)/Mg-5Sn composite with interpenetrating networks.

    Science.gov (United States)

    Wang, X; Li, J T; Xie, M Y; Qu, L J; Zhang, P; Li, X L

    2015-11-01

    In this paper, a novel (Hydroxyapatite+β-tricalcium phosphate)/Mg-5Sn ((HA+β-TCP)/Mg-5Sn) composite with interpenetrating networks was fabricated by infiltrating Mg-5Sn alloy into porous HA+β-TCP using suction casting technique. The structure, mechanical property and corrosion behaviors of the composite have been evaluated by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), mechanical testing, electrochemical and immersion test. It is shown that the molten Mg-5Sn alloy has infiltrated not only into the pores but also into the struts of the HA+β-TCP scaffold to forming a compact composite. The microstructure observation also shows that the Mg alloy contacts to the HA+β-TCP closely, and no reaction layer can be found between Mg-5Sn alloy and scaffold. The ultimate compressive strength of the composite is as high as 176MPa, which is about four fifths of the strength of the Mg-5Sn bulk alloy. The electrochemical and immersion tests indicate that the corrosion resistance of the composite is better than that of the Mg-5Sn bulk alloy. The corrosion products on the composite surface are mainly Mg(OH)2, Ca3(PO4)2 and HA. Appropriate mechanical and corrosion properties of the (HA+β-TCP)/Mg-5Sn composite indicate its possibility for new bone tissue implant materials. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Quantifying the bioadhesive properties of surface-modified polyurethane-urea nanoparticles in the vascular network.

    Science.gov (United States)

    Melgar-Lesmes, Pedro; Morral-Ruíz, Genoveva; Solans, Conxita; García-Celma, María José

    2014-06-01

    Nanomedicine research is currently requiring new standard methods to quantify the biocompatibility and bioadhesivity of emerging biomaterials designed to be used in contact with blood or soft tissues. In this study, we used biotinylated polyurethane-urea nanoparticles as a model to examine the applicabitility of an adapted hemagglutination assay to quantify the bioadhesive potential of these nanoparticles to red blood cells and, in turn, to extrapolate this data to vascular endothelial cells. We demonstrated that biotinylated nanoparticles adsorb to human erythrocytes and preferentially gather in erythrocyte contact areas. Moreover, these nanoparticles promoted a higher percentage of pig and human erythrocyte agglutination than naked polyurethane-urea nanoparticles in a biotin concentration-dependent manner. Conversely, pegylated nanoparticles were used as a negative control of the technique thus showing decreasing hemagglutination values as compared to naked nanoparticles until a minimum threshold. Furthermore, hemagglutination assay demonstrated an excellent positive correlation with bioadhesion quantification in human endothelial cells and the endothelial layer of pig aorta thus validating the hemagglutination assay described here as a useful method for predicting nanoparticle bioadhesivity to vascular endothelium. Therefore, the methodology described here is a versatile and straightforward method that allows evaluating the bioadhesive features of surface-modified polyurethane-urea nanoparticles in contact with blood and the vascular network and appears as a powerful tool to better design any drug delivery systems or implantable devices for biomedical applications. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. 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.

  8. 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.

  9. Dynamics and nature of support in the personal networks of people with type 2 diabetes living in Europe: qualitative analysis of network properties.

    Science.gov (United States)

    Kennedy, Anne; Rogers, Anne; Vassilev, Ivaylo; Todorova, Elka; Roukova, Poli; Foss, Christina; Knutsen, Ingrid; Portillo, Mari Carmen; Mujika, Agurtzane; Serrano-Gil, Manuel; Lionis, Christos; Angelaki, Agapi; Ratsika, Nikoleta; Koetsenruijter, Jan; Wensing, Michel

    2015-12-01

    Living with and self-managing a long-term condition implicates a diversity of networked relationships. This qualitative study examines the personal communities of support of people with type 2 diabetes. We conducted 170 biographical interviews in six European countries (Bulgaria, Greece, the Netherlands, Norway, Spain and UK) to explore social support and networks. Analysis was framed with reference to three predetermined social support mechanisms: the negotiation of support enabling engagement with healthy practices, navigation to sources of support and collective efficacy. Each interview was summarized to describe navigation and negotiation of participants' networks and the degree of collective efficacy. Analysis highlighted the similarities and differences between countries and provided insights into capacities of networks to support self-management. The network support mechanisms were identified in all interviews, and losses and gains in networks impacted on diabetes management. There were contextual differences between countries, most notably the impact of financial austerity on network dynamics. Four types of network are suggested: generative, diverse and beneficial to individuals; proxy, network members undertook diabetes management work; avoidant, support not engaged with; and struggling, diabetes management a struggle or not prioritized. It is possible to differentiate types of network input to living with and managing diabetes. Recognizing the nature of active, generative aspects of networks support is likely to have relevance for self-management support interventions either through encouraging continuing development and maintenance of these contacts or intervening to address struggling networks through introducing the means to connect people to additional sources of support. © 2014 John Wiley & Sons Ltd.

  10. Investigation of aerosol optical properties for remote sensing through DRAGON (distributed regional aerosol gridded observation networks) campaign in Korea

    Science.gov (United States)

    Lim, Jae-Hyun; Ahn, Joon Young; Park, Jin-Soo; Hong, You-Deok; Han, Jin-Seok; Kim, Jhoon; Kim, Sang-Woo

    2014-11-01

    Aerosols in the atmosphere, including dust and pollutants, scatters/absorbs solar radiation and change the microphysics of clouds, thus influencing the Earth's energy budget, climate, air quality, visibility, agriculture and water circulation. Pollutants have also been reported to threaten the human health. The present research collaborated with the U.S. NASA and the U.S. Aerosol Robotic Network (AERONET) is to study the aerosol characteristics in East Asia and improve the long-distance transportation monitoring technology by analyzing the observations of aerosol characteristics in East Asia during Distributed Regional Aerosol Gridded Observation Networks (DRAGON) Campaign (March 2012-May 2012). The sun photometers that measure the aerosol optical characteristics were placed evenly throughout the Korean Peninsula and concentrated in Seoul and the metropolitan area. Observation data are obtained from the DRAGON campaign and the first year (2012) observation data (aerosol optical depth and aerosol spatial distribution) are analyzed. Sun photometer observations, including aerosol optical depth (AOD), are utilized to validate satellite observations from Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS). Additional analysis is performed associated with the Northeast Asia, the Korean Peninsula in particular, to determine the spatial distribution of the aerosol.

  11. Reworking the language network.

    Science.gov (United States)

    Fedorenko, Evelina; Thompson-Schill, Sharon L

    2014-03-01

    Prior investigations of functional specialization have focused on the response profiles of particular brain regions. Given the growing emphasis on regional covariation, we propose to reframe these questions in terms of brain 'networks' (collections of regions jointly engaged by some mental process). Despite the challenges that investigations of the language network face, a network approach may prove useful in understanding the cognitive architecture of language. We propose that a language network plausibly includes a functionally specialized 'core' (brain regions that coactivate with each other during language processing) and a domain-general 'periphery' (a set of brain regions that may coactivate with the language core regions at some times but with other specialized systems at other times, depending on task demands). Framing the debate around network properties such as this may prove to be a more fruitful way to advance our understanding of the neurobiology of language. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Comparison of Trial and Error and Genetic Algorithm in Neural Network Development for Estimating Farinograph Properties of Wheat-flour Dough

    Directory of Open Access Journals (Sweden)

    Hajar Abbasi

    2015-06-01

    Conclusions: An ANN is a powerful method for predicting the Farinograph properties of dough. Taking advantages of performance criteria proved that the GA is more powerful than trial-and-error in determining the critical parameters of ANN’s structure, and improving its performance. Keywords: Artificial neural network, Genetic algorithm, Rheological characterization, Wheat-flour dough

  13. New and unexpected properties from polycyanurate networks prepared from bio based monomers

    Science.gov (United States)

    2017-04-02

    for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data...sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden...BPC Polycarbonate Polyamideimide (PAI) PTFE Polybenzimidazole (PBI) Polyimide (PI) PBO BPT polyarylate NOMEX BHDB arylate BHDB polyphosphonate FEP

  14. Structure-Property Relationships for Polycyanurate Networks Derived from Renewable Sources (Briefing Charts)

    Science.gov (United States)

    2015-08-18

    AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NO. Air Force Research Laboratory (AFMC) AFRL/RQRP 10 E. Saturn Blvd. Edwards AFB, CA93524-7680...THIS PAGE Unclassified SAR 23 19b. TELEPHONE NO (include area code ) 661-275-5857 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std

  15. Drug-selected human lung cancer stem cells: cytokine network, tumorigenic and metastatic properties.

    Directory of Open Access Journals (Sweden)

    Vera Levina

    with efficient cytokine network production that may represent a target for increased efficacy of cancer therapy.

  16. Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction

    Science.gov (United States)

    2012-01-01

    Background Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. Results Fifty percent of drug targets have a degree of less than nine, and ninety-five percent have a degree of less than ninety. We found that drug targets are over-represented in higher degree bins – this relationship is only seen for the consolidated interactome and it is not dependent on n-ary interaction data or its representation. Degree acts as a weak predictive feature for drug-target status and using more reliable subsets of the data does not increase this performance. However, performance does increase if only cancer-related drug targets are considered. We also note that a protein’s membership in pathway records can act as a predictive feature that is better than degree and that high-centrality may be an indicator of a drug that is more likely to be withdrawn. Conclusions These results show that protein interaction data integration and cleaning is an important consideration when incorporating network properties as predictive features for drug-target status. The provided scripts and data sets offer a starting point for further studies and cross-comparison of methods. PMID:23146171

  17. Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction

    Directory of Open Access Journals (Sweden)

    Mora Antonio

    2012-11-01

    Full Text Available Abstract Background Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. Results Fifty percent of drug targets have a degree of less than nine, and ninety-five percent have a degree of less than ninety. We found that drug targets are over-represented in higher degree bins – this relationship is only seen for the consolidated interactome and it is not dependent on n-ary interaction data or its representation. Degree acts as a weak predictive feature for drug-target status and using more reliable subsets of the data does not increase this performance. However, performance does increase if only cancer-related drug targets are considered. We also note that a protein’s membership in pathway records can act as a predictive feature that is better than degree and that high-centrality may be an indicator of a drug that is more likely to be withdrawn. Conclusions These results show that protein interaction data integration and cleaning is an important consideration when incorporating network properties as predictive features for drug-target status. The provided scripts and data sets offer a starting point for further studies and cross-comparison of methods.

  18. 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

  19. 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.

  20. State dependent properties of epileptic brain networks: comparative graph-theoretical analyses of simultaneously recorded EEG and MEG.

    Science.gov (United States)

    Horstmann, Marie-Therese; Bialonski, Stephan; Noennig, Nina; Mai, Heinke; Prusseit, Jens; Wellmer, Jörg; Hinrichs, Hermann; Lehnertz, Klaus

    2010-02-01

    To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval. We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics. Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings. Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks. An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks. Copyright (c) 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  1. 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.

  2. 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.

  3. Hydraulic properties of fracture networks; Analyse des proprietes hydrauliques des reseaux de fractures: discussion des modeles d'ecoulement compatibles avec les principales proprietes geometriques

    Energy Technology Data Exchange (ETDEWEB)

    Dreuzy, J.R. de

    1999-12-15

    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)

  4. 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.

  5. 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.

  6. Effects of specimen preparation on the electromagnetic property measurements of solid materials with an automatic network analyzer

    Science.gov (United States)

    Long, E. R., Jr.

    1986-01-01

    Effects of specimen preparation on measured values of an acrylic's electomagnetic properties at X-band microwave frequencies, TE sub 1,0 mode, utilizing an automatic network analyzer have been studied. For 1 percent or less error, a gap between the specimen edge and the 0.901-in. wall of the specimen holder was the most significant parameter. The gap had to be less than 0.002 in. The thickness variation and alignment errors in the direction parallel to the 0.901-in. wall were equally second most significant and had to be less than 1 degree. Errors in the measurement f the thickness were third most significant. They had to be less than 3 percent. The following parameters caused errors of 1 percent or less: ratios of specimen-holder thicknesses of more than 15 percent, gaps between the specimen edge and the 0.401-in. wall less than 0.045 in., position errors less than 15 percent, surface roughness, hickness variation in the direction parallel to the 0.401-in. wall less than 35 percent, and specimen alignment in the direction parallel to the 0.401-in. wall mass than 5 degrees.

  7. Synthesis and gas adsorption properties of tetra-armed microporous organic polymer networks based on triphenylamine.

    Science.gov (United States)

    Yang, Xiao; Yao, Shuwen; Yu, Miao; Jiang, Jia-Xing

    2014-04-01

    Two novel tetra-armed microporous organic polymers have been designed and synthesized via a nickel-catalyzed Yamamoto-type Ullmann cross-coupling reaction or Suzuki cross-coupling polycondensation. These polymers are stable in various solvents, including concentrated hydrochloric acid, and are thermally stable. The homocoupled polymer YPTPA shows much higher Brunauer-Emmet-Teller-specific surface area up to 1557 m(2) g(-1) than the copolymer SPTPA (544 m(2) g(-1)), and a high CO2 uptake ability of 3.03 mmol g(-1) (1.13 bar/273 K) with a CO2 /N2 sorption selectivity of 17.3:1. Both polymers show high isosteric heats of CO2 adsorption (22.7-26.5 kJ mol(-1)) because the incorporation of nitrogen atoms into the skeleton of microporous organic polymers enhances the interaction between the pore wall and the CO2 molecules. The values are higher than those of the porous aromatic frameworks, which contain neither additional polar functional groups nor nitrogen atoms, and are rather close to those of previously reported microporous organic polymers containing the nitrogen atoms on the pore wall. These data show that these materials would be potential candidates for applications in post-combustion CO2 capture and sequestration technology. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. 34 CFR 303.15 - Include; including.

    Science.gov (United States)

    2010-07-01

    ... 34 Education 2 2010-07-01 2010-07-01 false Include; including. 303.15 Section 303.15 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF SPECIAL EDUCATION AND REHABILITATIVE SERVICES, DEPARTMENT OF EDUCATION EARLY INTERVENTION PROGRAM FOR INFANTS AND TODDLERS WITH...

  9. Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties.

    Science.gov (United States)

    Rogasch, Nigel C; Thomson, Richard H; Farzan, Faranak; Fitzgibbon, Bernadette M; Bailey, Neil W; Hernandez-Pavon, Julio C; Daskalakis, Zafiris J; Fitzgerald, Paul B

    2014-11-01

    following motor cortex stimulation (N15, P30, N45, P60, N100) could be recovered from artefactual data, corroborating the reliability of ICA-based artefact correction. Various different artefacts contaminate TMS-EEG recordings over the DLPFC and motor cortex. However, these artefacts can be removed with apparent minimal impact on neural activity using ICA, allowing the study of TMS-evoked cortical network properties. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. 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.

  11. A mathematical model for networks with structures in the mesoscale

    OpenAIRE

    Criado, Regino; Flores, Julio; Gacia Del Amo, Alejandro Jose; Gómez, Jesus; Romance, Miguel

    2011-01-01

    Abstract The new concept of multilevel network is introduced in order to embody some topological properties of complex systems with structures in the mesoscale which are not completely captured by the classical models. This new model, which generalizes the hyper-network and hyper-structure models, fits perfectly with several real-life complex systems, including social and public transportation networks. We present an analysis of the structural properties of the mu...

  12. Polyacrylamide hydrogels and semi-interpenetrating networks (IPNs) with poly(N-isopropylacrylamide): mechanical properties by measure of compressive elastic modulus.

    Science.gov (United States)

    Muniz, E C; Geuskens, G

    2001-01-01

    Semi-IPN hydrogels (based on cross-linked polyacrylamide having poly(N-isopropylacrylamide) (PN1PAAm) inside) were synthesized and their properties, such as swelling ratio and compressive elastic moduli, were studied at several temperatures. Equilibrium swelling ratios of semi-IPN markedly decreased due to the presence of less hydrophilic PNIPAAm chains. The semi-IPN presented greater elastic modulus when compared to the cross-linked PAAm hydrogel. The effect was explained as being an additional contribution of the PNIPAAm chains, which collapsed around the PAAm networks, to the elastic modulus. It was pointed out that the PAAm networks support the collapsed chains. According to the results presented in this work, semi-IPN hydrogels present better mechanical properties than the PAAm hydrogel, mainly when the PNIPAAm chains are in a collapsed state. Copyright 2001 Kluwer Academic Publishers

  13. Properties of grain boundary networks in the NEEM ice core analyzed by combined transmission and reflection optical microscopy

    Science.gov (United States)

    Binder, Tobias; Weikusat, Ilka; Garbe, Christoph; Svensson, Anders; Kipfstuhl, Sepp

    2014-05-01

    Microstructure analysis of ice cores is vital to understand the processes controlling the flow of ice on the microscale. To quantify the microstructural variability (and thus occurring processes) on centimeter, meter and kilometer scale along deep polar ice cores, a large number of sections has to be analyzed. In the last decade, two different methods have been applied: On the one hand, transmission optical microscopy of thin sections between crossed polarizers yields information on the distribution of crystal c-axes. On the other hand, reflection optical microscopy of polished and controlled sublimated section surfaces allows to characterize the high resolution properties of a single grain boundary, e.g. its length, shape or curvature (further developed by [1]). Along the entire NEEM ice core (North-West Greenland, 2537 m length) drilled in 2008-2011 we applied both methods to the same set of vertical sections. The data set comprises series of six consecutive 6 x 9 cm2 sections in steps of 20 m - in total about 800 images. A dedicated method for automatic processing and matching both image types has recently been developed [2]. The high resolution properties of the grain boundary network are analyzed. Furthermore, the automatic assignment of c-axis misorientations to visible sublimation grooves enables us to quantify the degree of similarity between the microstructure revealed by both analysis techniques. The reliability to extract grain boundaries from both image types as well as the appearance of sublimation groove patterns exhibiting low misorientations is investigated. X-ray Laue diffraction measurements (yielding full crystallographic orientation) have validated the sensitivity of the surface sublimation method for sub-grain boundaries [3]. We introduce an approach for automatic extraction of sub-grain structures from sublimation grooves. A systematic analysis of sub-grain boundary densities indicates a possible influence of high impurity contents (amongst

  14. 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

  15. 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.

  16. 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.

  17. Nonreciprocal effects and their applications in fiber optic networks

    OpenAIRE

    Fang, Xiaojun

    1996-01-01

    Nonreciprocity is a fundamental property of networks. Unlike electronic networks theory, optical network theory is still a field to be investigated. Lightwave systems, including fiber optic and integrated optic, are becoming more and more complex, new function blocks ( or components) and networking strategies are very important for future highly integrated lightwave circuits. Several common nonreciprocal optical effects studied in this disseration and several basic applications...

  18. Elastic regimes of sub-isostatic athermal fiber networks

    OpenAIRE

    Licup, Albert James; Sharma, Abhinav; MacKintosh, Fred C.

    2015-01-01

    Athermal models of disordered fibrous networks are highly useful for studying the mechanics of elastic networks composed of stiff biopolymers. The underlying network architecture is a key aspect that can affect the elastic properties of these systems, which include rich linear and nonlinear elasticity. Existing computational approaches have focused on both lattice-based and off-lattice networks obtained from the random placement of rods. It is not obvious, a priori, whether the two architectu...

  19. Self-assembly of tetracyanonaphtho-quinodimethane (TNAP) based metal–organic networks on Pb(1 1 1): Structural, electronic, and magnetic properties

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadi, Gelavizh; Franke, Katharina J., E-mail: franke@physik.fu-berlin.de

    2016-06-15

    Highlights: • Self-assembled metal–organic networks of tetracyanonaphtho-quinodimethane (TNAP) on Pb(1 1 1) are investigated. • Pb atoms from surface are incorporated in porous networks. • NaCl islands are dissolved in favor of ionically bonded Na-TNAP metal–organic network. • Co-deposition of Fe leads to irregular Fe-TNAP structures. • Some Fe centers exhibit Shiba states as a fingerprint of magnetic interaction with the superconductor. - Abstract: We use scanning tunneling microscopy and spectroscopy to investigate structural and electronic properties of tetracyanonaphtho-quinodimethane (TNAP) based metal–organic networks on a superconducting Pb(1 1 1) surface. At low temperatures, the TNAP molecules form densely packed islands. When deposited at room temperature, Pb adatoms are incorporated into fourfold bonding nodes with the TNAP molecules leading to long-range ordered porous structures. Co-deposition of NaCl with TNAP yields a Na source for an ionically bonded Na-TNAP structure. Fourfold bonding motifs are also created by Fe atoms with the cyano terminations of TNAP. However, the structures are irregular and do not sustain the formation of long-range ordered networks. Some Fe centers with molecules surrounded in a local C2 symmetry exhibit Shiba states as a fingerprint of a magnetic interaction with the superconducting surface.

  20. 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.

  1. 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

  2. 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...

  3. Electrical And Optical Properties Of Colloidal Quantum Dots And Quantum Dot Networks: Role Of Surface States And Using Biomolecular Links In Network Assembly

    National Research Council Canada - National Science Library

    Stroscio, Michael A; Dutta, Mitra; Ramadurai, Dinakar; Shi, Peng; Li, Yang; Alexson, Dimitri; Kohanpour, Babak; Sethuraman, Akil; Saini, Vikas; Raichura, Amit; Yang, Jianyong

    2004-01-01

    .... Absorption spectra and photoluminescence (PL) spectra of colloidal cadmium sulfide (CdS) quantum dots are analyzed to investigate the role of surface states in determining the electrical and optical properties of these semiconductor quantum dots...

  4. Spatial Structure and Scaling of Agricultural Networks

    CERN Document Server

    Sousa, Daniel

    2016-01-01

    Considering agricultural landscapes as networks can provide information about spatial connectivity relevant for a wide range of applications including pollination, pest management, and ecology. Global agricultural networks are well-described by power law rank-size distributions. However, regional analyses capture only a subset of the total global network. Most analyses are regional. In this paper, we seek to address the following questions: Does the globally observed scale-free property of agricultural networks hold over smaller spatial domains? Can similar properties be observed at kilometer to meter scales? We analyze 9 intensively cultivated Landsat scenes on 5 continents with a wide range of vegetation distributions. We find that networks of vegetation fraction within the domain of each of these Landsat scenes exhibit substantial variability - but still possess similar scaling properties to the global distribution of agriculture. We also find similar results using a 39 km2 IKONOS image. To illustrate an a...

  5. 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

  6. Network Frontier Workshop 2013

    Science.gov (United States)

    2014-11-11

    networks, biological networks, cognitive and semantic networks and social networks. This field has received a major boost caused by the availability of huge...networks, which require new ways of thinking about the world. Part of the new cognition is provided by the fractional calculus description of temporal...structures in a wide range of examples—including road networks in large urban areas, a rabbit warren, a dolphin social network, a European interbank network

  7. Large networks and graph limits

    CERN Document Server

    Lovász, László

    2012-01-01

    Recently, it became apparent that a large number of the most interesting structures and phenomena of the world can be described by networks. Developing a mathematical theory of very large networks is an important challenge. This book describes one recent approach to this theory, the limit theory of graphs, which has emerged over the last decade. The theory has rich connections with other approaches to the study of large networks, such as "property testing" in computer science and regularity partition in graph theory. It has several applications in extremal graph theory, including the exact for

  8. Network neuroscience.

    Science.gov (United States)

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

  9. 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

  10. Poly(ethylene glycol)-grafted cyclic acetals based polymer networks with non-water-swellable, biodegradable and surface hydrophilic properties.

    Science.gov (United States)

    Yin, Ruixue; Zhang, Nan; Wu, Wentao; Wang, Kemin

    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. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. 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

  12. Social inheritance can explain the structure of animal social networks.

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-06-28

    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.

  13. Network graph analysis of category fluency testing.

    Science.gov (United States)

    Lerner, Alan J; Ogrocki, Paula K; Thomas, Peter J

    2009-03-01

    Category fluency is impaired early in Alzheimer disease (AD). Graph theory is a technique to analyze complex relationships in networks. Features of interest in network analysis include the number of nodes and edges, and variables related to their interconnectedness. Other properties important in network analysis are "small world properties" and "scale-free" properties. The small world property (popularized as the so-called "6 degrees of separation") arises when the majority of connections are local, but a number of connections are to distant nodes. Scale-free networks are characterized by the presence of a few nodes with many connections, and many more nodes with fewer connections. To determine if category fluency data can be analyzed using graph theory. To compare normal elderly, mild cognitive impairment (MCI) and AD network graphs, and characterize changes seen with increasing cognitive impairment. Category fluency results ("animals" recorded over 60 s) from normals (n=38), MCI (n=33), and AD (n=40) completing uniform data set evaluations were converted to network graphs of all unique cooccurring neighbors, and compared for network variables. For Normal, MCI and AD, mean clustering coefficients were 0.21, 0.22, 0.30; characteristic path lengths were 3.27, 3.17, and 2.65; small world properties decreased with increasing cognitive impairment, and all graphs showed scale-free properties. Rank correlations of the 25 commonest items ranged from 0.75 to 0.83. Filtering of low-degree nodes in normal and MCI graphs resulted in properties similar to the AD network graph. Network graph analysis is a promising technique for analyzing changes in category fluency. Our technique results in nonrandom graphs consistent with well-characterized properties for these types of graphs.

  14. 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.

  15. A preliminary study on the effects of acute ethanol ingestion on default mode network and temporal fractal properties of the brain.

    Science.gov (United States)

    Weber, Alexander M; Soreni, Noam; Noseworthy, Michael D

    2014-08-01

    To study the effect of acute alcohol intoxication on the functional connectivity of the default mode network (DMN) and temporal fractal properties of the healthy adult brain. Eleven healthy male volunteers were asked to drink 0.59 g/kg of ethanol. Resting state blood oxygen level dependent (rsBOLD) MRI scans were obtained before consumption, 60 min post-consumption and 90 min post-consumption. Before each rsBOLD scan, pointed-resolved spectroscopy (PRESS) (1)H-MRS (magnetic resonance spectroscopy) scans were acquired to measure ethanol levels in the right basal ganglia. Significant changes in DMN connectivity were found following alcohol consumption (p alcohol consumption (p alcohol intoxication. The reduced fractal dimension implies a change in function of small-scale neural networks towards less complex signaling.

  16. 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.

  17. 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.

  18. Controllability of flow-conservation networks

    Science.gov (United States)

    Zhao, Chen; Zeng, An; Jiang, Rui; Yuan, Zhengzhong; Wang, Wen-Xu

    2017-07-01

    The ultimate goal of exploring complex networks is to control them. As such, controllability of complex networks has been intensively investigated. Despite recent advances in studying the impact of a network's topology on its controllability, a comprehensive understanding of the synergistic impact of network topology and dynamics on controllability is still lacking. Here, we explore the controllability of flow-conservation networks, trying to identify the minimal number of driver nodes that can guide the network to any desirable state. We develop a method to analyze the controllability on flow-conservation networks based on exact controllability theory, transforming the original analysis on adjacency matrix to Laplacian matrix. With this framework, we systematically investigate the impact of some key factors of networks, including link density, link directionality, and link polarity, on the controllability of these networks. We also obtain the analytical equations by investigating the network's structural properties approximatively and design the efficient tools. Finally, we consider some real networks with flow dynamics, finding that their controllability is significantly different from that predicted by only considering the topology. These findings deepen our understanding of network controllability with flow-conservation dynamics and provide a general framework to incorporate real dynamics in the analysis of network controllability.

  19. Percolation in Self-Similar Networks

    Science.gov (United States)

    Serrano, M. Ángeles; Krioukov, Dmitri; Boguñá, Marián

    2011-01-01

    We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering, scale-free graphs with finite clustering and metric structure, growing scale-free networks, and many real networks. The proof and the derivation of the giant component size do not require the assumption that networks are treelike. Our results rely only on the observation that self-similar networks possess a hierarchy of nested subgraphs whose average degree grows with their depth in the hierarchy. We conjecture that this property is pivotal for percolation in networks.

  20. 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.

  1. Properties of radiation synthesized PVP-kappa carrageenan hydrogel blends[PVP; Carrageenan; Hydrogels; Radiation crosslinking; Radiation grafting; Semi-interpenetrating network

    Energy Technology Data Exchange (ETDEWEB)

    Abad, L.V. E-mail: lvabad@pnri.dost.gov.ph; Relleve, L.S.; Aranilla, C.T.; Rosa, A.M. dela

    2003-12-01

    Hydrogels have been synthesized from varying concentrations of polyvinyl pyrolidone (PVP) and kappa carrageenan (KC) using gamma radiation. Physical properties such as gel fraction and swelling behavior were determined. Data revealed the presence of a network structure whereby KC is physically entangled into the crosslinked PVP (SIPN). TGA, X-RF and FT-IR analyses of the gel fractions also indicated grafting and crosslinking of the PVP. The degree of grafting and crosslinking depended on the concentrations of KC and PVP. Maximum grafting was obtained at higher KC concentration and lower PVP.

  2. Modeling of technological processes of heat supply, as a tool for assessing the state of objects of the property fund and engineering networks of enterprises

    Science.gov (United States)

    Azimov, U. I.; Gilmanshin, I. R.

    2017-09-01

    The approach to the mathematical modeling of technological processes of production, manufacture and consumption energyresources on the property fund facilities and engineering networks is presented. This approach is defining the information support system analysis of the kinetic changes of thermodynamic parameters sequentially occurring thermal processes in the flows of heat transfer agent in a closed structures of heating energy working in the recycle mode of the heat flow. It is determined the possibility of setting and solving problems of energyefficiency on the objects with close cycle operating and working in the fluctuation mode of the environmental parameters.

  3. 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.

  4. 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.

  5. 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.

  6. 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 ...

  7. 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

  8. 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

  9. 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.

  10. 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...

  11. Wetting Properties of Polysiloxane Networks Modified in Situ with Fluoroalkyl-Substituted Linear and POSS Cage Structures (Briefing Charts)

    Science.gov (United States)

    2015-08-17

    of PDMS/siloxane networks - Primarily oxide formation via O2 plasma, UV/ ozone , etc. and subsequent functionalization - Functional PDMS (e.g...coating Transparent Omniphobicity Oil /water emulsion gravity seperation Golovin et al., Ang. Chem., 2013 Extreme Omniphobicity Pan et al., JACS

  12. 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.

  13. Habitat fragmentation alters the properties of a host-parasite network: rodents and their helminths in South-East Asia.

    Science.gov (United States)

    Bordes, Frédéric; Morand, Serge; Pilosof, Shai; Claude, Julien; Krasnov, Boris R; Cosson, Jean-François; Chaval, Yannick; Ribas, Alexis; Chaisiri, Kittipong; Blasdell, Kim; Herbreteau, Vincent; Dupuy, Stéphane; Tran, Annelise

    2015-09-01

    1. While the effects of deforestation and habitat fragmentation on parasite prevalence or richness are well investigated, host-parasite networks are still understudied despite their importance in understanding the mechanisms of these major disturbances. Because fragmentation may negatively impact species occupancy, abundance and co-occurrence, we predict a link between spatiotemporal changes in habitat and the architecture of host-parasite networks. 2. For this, we used an extensive data set on 16 rodent species and 29 helminth species from seven localities of South-East Asia. We analysed the effects of rapid deforestation on connectance and modularity of helminth-parasite networks. We estimated both the degree of fragmentation and the rate of deforestation through the development of land uses and their changes through the last 20 to 30 years in order to take into account the dynamics of habitat fragmentation in our statistical analyses. 3. We found that rapid fragmentation does not affect helminth species richness per se but impacts host-parasite interactions as the rodent-helminth network becomes less connected and more modular. 4. Our results suggest that parasite sharing among host species may become more difficult to maintain with the increase of habitat disturbance. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

  14. 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...

  15. 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

  16. Optical modulator including grapene

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Ming; Yin, Xiaobo; Zhang, Xiang

    2016-06-07

    The present invention provides for a one or more layer graphene optical modulator. In a first exemplary embodiment the optical modulator includes an optical waveguide, a nanoscale oxide spacer adjacent to a working region of the waveguide, and a monolayer graphene sheet adjacent to the spacer. In a second exemplary embodiment, the optical modulator includes at least one pair of active media, where the pair includes an oxide spacer, a first monolayer graphene sheet adjacent to a first side of the spacer, and a second monolayer graphene sheet adjacent to a second side of the spacer, and at least one optical waveguide adjacent to the pair.

  17. Visual Impairment, Including Blindness

    Science.gov (United States)

    ... Who Knows What? (log-in required) Select Page Visual Impairment, Including Blindness Mar 31, 2017 Links updated, ... doesn’t wear his glasses. Back to top Visual Impairments in Children Vision is one of our ...

  18. Physical properties of reservoirs using an artificial neural network approach: Example from the Jeanne d'Arc basin, eastern offshore Canada

    Energy Technology Data Exchange (ETDEWEB)

    Zehui Huang; Williamson, M.A. (Geological Survey of Canada, Dartmouth (Canada))

    1996-01-01

    Quantitative statements of the evolution of petroleum systems in the Jeanne d'Arc Basin provides a solid basis for future exploration, reservoir modelling, reservoir development and resource management. As a contribution to such statements, we have integrated physical property measurements (porosity and permeability) and well log data from the major reservoir intervals throughout the basin using an efficient backpropagation artificial neural network (BP-ANN) modified with the Marquardt algorithm. The bulk of the data are from the Avalon Formation (13 wells), the Hibernia Formation (7 wells) and the Jeanne d'Arc Formation (12 wells). After data preprocessing and training/supervising example preparation, a model for the relationship of physical property and well log response was established with the BP-ANN technique. Test of the BP-ANN model in other Mesozoic reservoir intervals in the same basin whose data were not used as the training and supervising examples shows good agreement between the measured and predicted values. The BP-ANN model established was used to construct permeability porosity profiles in 40 wells for the Avalon Formation, 36 wells for the Hibernia Formation and 37 wells for the Jeanne d'Arc Formation from well logs. These profiles offer a more complete basis for understanding physical properties of reservoir intervals of this basin. They allow a detailed review of vertical and horizontal variations of physical properties in key areas of this basin.

  19. Physical properties of reservoirs using an artificial neural network approach: Example from the Jeanne d`Arc basin, eastern offshore Canada

    Energy Technology Data Exchange (ETDEWEB)

    Zehui Huang; Williamson, M.A. [Geological Survey of Canada, Dartmouth (Canada)

    1996-12-31

    Quantitative statements of the evolution of petroleum systems in the Jeanne d`Arc Basin provides a solid basis for future exploration, reservoir modelling, reservoir development and resource management. As a contribution to such statements, we have integrated physical property measurements (porosity and permeability) and well log data from the major reservoir intervals throughout the basin using an efficient backpropagation artificial neural network (BP-ANN) modified with the Marquardt algorithm. The bulk of the data are from the Avalon Formation (13 wells), the Hibernia Formation (7 wells) and the Jeanne d`Arc Formation (12 wells). After data preprocessing and training/supervising example preparation, a model for the relationship of physical property and well log response was established with the BP-ANN technique. Test of the BP-ANN model in other Mesozoic reservoir intervals in the same basin whose data were not used as the training and supervising examples shows good agreement between the measured and predicted values. The BP-ANN model established was used to construct permeability porosity profiles in 40 wells for the Avalon Formation, 36 wells for the Hibernia Formation and 37 wells for the Jeanne d`Arc Formation from well logs. These profiles offer a more complete basis for understanding physical properties of reservoir intervals of this basin. They allow a detailed review of vertical and horizontal variations of physical properties in key areas of this basin.

  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.

  2. Mapping Judicial Dialogue across National Borders: An Exploratory Network Study of Learning from Lobbying among European Intellectual Property Judges

    Directory of Open Access Journals (Sweden)

    Emmanuel Lazega

    2012-05-01

    Full Text Available This paper looks at dialogue and collective learning across borders through personal networks of judges. We focus on judges participating in the Venice Forum, bringing together European patent judges involved in institutional lobbying for the construction of a European Patent Court. Empirical observation shows that personal networks of discussion with foreign judges, reading of their work and references to their decisions do exist in this milieu and can be mapped. Our network study shows that judges from some European countries are more active in this dialogue than judges from other countries. The learning process is driven, to some extent, by a small subset of super-central judges who frame this dialogue and can be considered to be opinion leaders in this social milieu. We measure a strong level of consensus among the judges on several controversial issues surrounding the procedure of a possible future European Patent Court. But strong differences between them remain. Dialogue and collective learning do not, by themselves, lead to convergence towards a uniform position in these controversies.

  3. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions.

    Directory of Open Access Journals (Sweden)

    Zixuan Cang

    2017-07-01

    Full Text Available Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH method. ESPH represents 3D complex geometry by one-dimensional (1D topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN. We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes.weilab.math.msu.edu/TDL/.

  4. Morphological properties of the action-observation cortical network in adolescents with low and high resistance to peer influence.

    Science.gov (United States)

    Paus, Tomás; Toro, Roberto; Leonard, Gabriel; Lerner, Jacqueline V; Lerner, Richard M; Perron, Michel; Pike, G Bruce; Richer, Louis; Steinberg, Laurence

    2008-01-01

    Children with high resistance to peer influences differ from their low-resistance counterparts in the degree of functional connectivity in fronto-parietal and prefrontal cortical networks. Here we explored the possibility that the degree of morphological similarities across the same cortical regions also varies as a function of this behavioral trait. Using structural magnetic-resonance (MR) images, we measured cortical thickness in a total of 295 adolescents (12 to 18 years of age). We found that inter-regional correlations in cortical thickness increased with the resistance to peer influence (RPI); this was especially the case, in female adolescents, in the premotor and prefrontal networks. We also observed significant differences between the adolescents with high and low RPI scores in their general intelligence and the scores of positive youth development. We suggest that these morphological findings might reflect differences, between adolescents with high vs. low resistance to peer influences, in a repeated and concurrent engagement of these networks in social context.

  5. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

    Science.gov (United States)

    2017-01-01

    Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

  6. Listening to Include

    Science.gov (United States)

    Veck, Wayne

    2009-01-01

    This paper attempts to make important connections between listening and inclusive education and the refusal to listen and exclusion. Two lines of argument are advanced. First, if educators and learners are to include each other within their educational institutions as unique individuals, then they will need to listen attentively to each other.…

  7. On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account

    Science.gov (United States)

    Li, Huajiao; An, Haizhong; Gao, Xiangyun; Huang, Jiachen; Xu, Qun

    2014-07-01

    Shareholders are the owners of listed companies, and their relationships can directly affect the structure of the stock market. In this paper, we analyze the topological properties and evolution of the cross-shareholding networks of listed companies in the past 5 years in China from 2007 to 2011, an infrequently considered topic, by taking shareholders' cross-shareholding relationships into account. This analysis arrives at a deeper insight into the inner characteristics of China's stock market. We find that the cross-shareholding networks of listed companies with shareholders' cross-shareholding relationships display statistical features that reveal the stock market's complex relationships more precisely. In particular, the results show that when the shareholders' cross-shareholding relationships are considered, first, the In-degree and Out-degree of the cross-shareholding networks follow power-law distribution and the R2 of the linear regression analysis of the cumulative degree distribution is relatively higher; second, the modularity of the communities is larger; finally, both the number of members of top-ranked communities and the number of communities that have a large number of members are larger than those of which only considering the relationships between shareholders and listed companies are taken into account. Such cross-shareholding networks analysis taking shareholders' cross-shareholding relations into account would be a helpful tool for supervisory departments and for stock market researchers to grasp the inner cross-shareholding relationships of listed companies in China, and it will be also helpful for the further researches about the "agent problems" in the stock markets from a whole point of view.

  8. Quantifying randomness in real networks

    Science.gov (United States)

    Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-10-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

  9. Affective Networks

    OpenAIRE

    Jodi Dean

    2010-01-01

    This article sets out the idea of affective networks as a constitutive feature of communicative capitalism. It explores the circulation of intensities in contemporary information and communication networks, arguing that this circulation should be theorized in terms of the psychoanalytic notion of the drive. The article includes critical engagements with theorists such as Guy Debord, Jacques Lacan, Tiziana Terranova, and Slavoj Zizek.

  10. Robustness and Optimization of Complex Networks : Reconstructability, Algorithms and Modeling

    NARCIS (Netherlands)

    Liu, D.

    2013-01-01

    The infrastructure networks, including the Internet, telecommunication networks, electrical power grids, transportation networks (road, railway, waterway, and airway networks), gas networks and water networks, are becoming more and more complex. The complex infrastructure networks are crucial to our

  11. Analytic device including nanostructures

    KAUST Repository

    Di Fabrizio, Enzo M.

    2015-07-02

    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.

  12. Clustering signatures classify directed networks

    Science.gov (United States)

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

    2008-09-01

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

  13. Pore network extraction for fractured porous media

    Science.gov (United States)

    Jiang, Z.; van Dijke, M. I. J.; Geiger, S.; Ma, J.; Couples, G. D.; Li, X.

    2017-09-01

    Although flow through fractured rocks involves many different length-scales, it is crucial for the prediction of continuum-scale single- and multi-phase flow functions to understand, at the pore-scale, the interaction between the rock matrix and fractures. Here we present a pore-network extraction method in which the pore diameters and fracture apertures are of similar size. The method involves a shrinking algorithm to extract a hybrid skeleton of medial axes and surfaces, and it includes a workflow to convert the medial surfaces of fractures into dense networks of virtual medial axes, allowing generation of an integrated pore-network for the entire pore space. Appropriate single- and two-phase flow properties are assigned to network elements representing the fractures. We validate the method via comparisons between pore network flow simulations and an analytical solution, direct flow simulations and experimental observations. The network calculations are several orders of magnitude faster than the direct simulations.

  14. Structural properties of Ge-S amorphous networks in relationship with rigidity transitions: An ab initio molecular dynamics study

    Science.gov (United States)

    Chakraborty, S.; Boolchand, P.; Micoulaut, M.

    2017-09-01

    We investigate the amorphous GexS100 -x (with 10 ≤x ≤40 ) system from ab initio simulations. Results show a very good agreement with experimental findings from diffraction and the topology of the obtained structural models is further analyzed and compared with the selenide analog. Differences emerge, however, from a detailed molecular dynamics analysis showing that the ring statistics and the homopolar defects do not evolve similarly. The findings are also connected to rigidity theory, which provides a topological approach to decoding the physics of network glasses, and the effects of composition and temperature are analyzed.

  15. Measurement of Dielectric Properties at 75 - 325 GHz using a Vector Network Analyzer and Full Wave Simulator

    Directory of Open Access Journals (Sweden)

    S.Khanal

    2012-06-01

    Full Text Available This paper presents a fast and easy to use method to determine permittivity and loss tangent in the frequency range of 75 to 325 GHz. To obtain the permittivity and the loss tangent of the test material, the reflection and transmission S-parameters of a waveguide section filled with the test material are measured using a vector network analyzer and then compared with the simulated plots from a full wave simulator (HFSS, or alternatively the measurement results are used in mathematical formulas. The results are coherent over multiple waveguide bands.

  16. Metamorphosis in the Porosity of Recycled Concretes Through the Use of a Recycled Polyethylene Terephthalate (PET Additive. Correlations between the Porous Network and Concrete Properties

    Directory of Open Access Journals (Sweden)

    José Miguel Mendivil-Escalante

    2017-02-01

    Full Text Available In the field of construction, sustainable building materials are currently undergoing a process of technological development. This study aims to contribute to understanding the behavior of the fundamental properties of concretes prepared with recycled coarse aggregates that incorporate a polyethylene terephthalate (PET-based additive in their matrix (produced by synthesis and glycolysis of recycled PET bottles in an attempt to reduce their high porosity. Techniques to measure the gas adsorption, water porosity, Fourier transform infrared spectroscopy (FTIR and X-ray diffraction (XRD were used to evaluate the effect of the additive on the physical, mechanical and microstructural properties of these concretes. Porosity reductions of up to 30.60% are achieved with the addition of 1%, 3%, 4%, 5%, 7% and 9% of the additive, defining a new state in the behavioral model of the additive (the overdosage point in the concrete matrix; in addition, the porous network of these concretes and their correlation with other physical and mechanical properties are also explained.

  17. Comparative Study of Structure-Property Relationships in Polymer Networks Based on Bis-GMA, TEGDMA and Various Urethane-Dimethacrylates

    Directory of Open Access Journals (Sweden)

    Izabela Barszczewska-Rybarek

    2015-03-01

    Full Text Available The effect of various dimethacrylates on the structure and properties of homo- and copolymer networks was studied. The 2,2-bis-[4-(2-hydroxy-3- methacryloyloxypropoxyphenyl]-propane (Bis-GMA, triethylene glycol dimethacrylate (TEGDMA and 1,6-bis-(methacryloyloxy-2-ethoxycarbonylamino-2,4,4-trimethylhexane (HEMA/TMDI, all popular in dentistry, as well as five urethane-dimethacrylate (UDMA alternatives of HEMA/TMDI were used as monomers. UDMAs were obtained from mono-, di- and tri(ethylene glycol monomethacrylates and various commercial diisocyanates. The chemical structure, degree of conversion (DC and scanning electron microscopy (SEM fracture morphology were related to the mechanical properties of the polymers: flexural strength and modulus, hardness, as well as impact strength. Impact resistance was widely discussed, being lower than expected in the case of poly(UDMAs. It was caused by the heterogeneous morphology of these polymers and only moderate strength of hydrogen bonds between urethane groups, which was not high enough to withstand high impact energy. Bis-GMA, despite having the highest polymer morphological heterogeneity, ensured fair impact resistance, due to having the strongest hydrogen bonds between hydroxyl groups. The TEGDMA homopolymer, despite being heterogeneous, produced the smoothest morphology, which resulted in the lowest brittleness. The UDMA monomer, having diethylene glycol monomethacrylate wings and the isophorone core, could be the most suitable HEMA/TMDI alternative. Its copolymer with Bis-GMA and TEGDMA had improved DC as well as all the mechanical properties.

  18. Mechanical Properties of Re-constituted Actin Networks at an Oil/Water Interface Determined by Microrheology

    NARCIS (Netherlands)

    Ershov, D.S.; Cohen Stuart, M.A.; Gucht, van der J.

    2012-01-01

    There have been various attempts to investigate the mechanical properties of the actin cortex in cells, but the factors that control them remain poorly understood. To make progress, we develop a reconstituted model of the actin cortex that mimics its structure. We attach actin filaments to lipids

  19. distribution network

    African Journals Online (AJOL)

    user

    This paper examined the acidic properties of distribution transformer oil insulation in service at Jericho distribution network Ibadan, Nigeria. Five oil samples each from six distribution transformers (DT1, DT2, DT3, DT4 and DT5) making a total of thirty samples were taken from different installed distribution transformers all ...

  20. Network Affordances

    DEFF Research Database (Denmark)

    Samson, Audrey; Soon, Winnie

    2015-01-01

    This paper examines the notion of network affordance within the context of network art. Building on Gibson's theory (Gibson, 1979) we understand affordance as the perceived and actual parameters of a thing. We expand on Gaver's affordance of predictability (Gaver, 1996) to include ecological...... and computational parameters of unpredictability. We illustrate the notion of unpredictability by considering four specific works that were included in a network art exhibiton, SPEED SHOW [2.0] Hong Kong. The paper discusses how the artworks are contingent upon the parameteric relations (Parisi, 2013......), of the network. We introduce network affordance as a dynamic framework that could articulate the experienced tension arising from the (visible) symbolic representation of computational processes and its hidden occurrences. We base our proposal on the experience of both organising the SPEED SHOW and participating...

  1. Being Included and Excluded

    DEFF Research Database (Denmark)

    Korzenevica, Marina

    2016-01-01

    Following the civil war of 1996–2006, there was a dramatic increase in the labor mobility of young men and the inclusion of young women in formal education, which led to the transformation of the political landscape of rural Nepal. Mobility and schooling represent a level of prestige that rural...... politics. It analyzes how formal education and mobility either challenge or reinforce traditional gendered norms which dictate a lowly position for young married women in the household and their absence from community politics. The article concludes that women are simultaneously excluded and included from...... people regard as a prerequisite for participating in local community politics. Based on a fieldwork in two villages of Panchthar district in eastern Nepal, this article explores how these changes strengthen or weaken women’s political agency and how this is reflected in their participation in community...

  2. The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.

    Directory of Open Access Journals (Sweden)

    Duygu Balcan

    Full Text Available The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple "sequence-matching" rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements.

  3. Statistical Network Analysis for Functional MRI: Mean Networks and Group Comparisons.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    2014-05-01

    Full Text Available Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i the construction of summary networks, such as how to compute and visualize the mean network from a sample of network-valued data points; and (ii how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN, or by directly computing the mean network, provided that a metric has been specified on the space of all networks with a given number of nodes. In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks.

  4. Routing in Vehicular Networks: Feasibility, Modeling, and Security

    Directory of Open Access Journals (Sweden)

    Ioannis Broustis

    2008-01-01

    Full Text Available Vehicular networks are sets of surface transportation systems that have the ability to communicate with each other. There are several possible network architectures to organize their in-vehicle computing systems. Potential schemes may include vehicle-to-vehicle ad hoc networks, wired backbone with wireless last hops, or hybrid architectures using vehicle-to-vehicle communications to augment roadside communication infrastructures. Some special properties of these networks, such as high mobility, network partitioning, and constrained topology, differentiate them from other types of wireless networks. We provide an in-depth discussion on the important studies related to architectural design and routing for such networks. Moreover, we discuss the major security concerns appearing in vehicular networks.

  5. Social networks of old people in India: research and policy.

    Science.gov (United States)

    van Willigen, John; Chadha, N K

    2003-01-01

    This article presents a comparative analysis of the available research on the social networks of older persons in India. Most of this research has been done in North Indian cities. The research foci of the available studies include network size, core networks and beyond, life course changes in networks, impacts of residency in old-age homes, gender differences, and joint and nuclear family residence. This research is discussed in terms of its policy implications. Because the research demonstrates that social networks are important for the welfare of older Indians, one can conclude that social policy that encourages the maintenance of robust networks throughout the life course may be worth pursuing. One aspect of policy is discussed. The analysis of the relationship between social network and gender suggests that current policies that can be seen as supporting gender inequality in terms of property may have a negative impact on the networks of older women.

  6. Introduction to computer networking

    CERN Document Server

    Robertazzi, Thomas G

    2017-01-01

    This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional. • Features a concise, accessible treatment of computer networking, focusing on new technological topics; • Provides non-mathematical introduction to networks in their most common forms today;< • Includes new developments in switching, optical networks, WiFi, Bluetooth, LTE, 5G, and quantum cryptography.

  7. Constant properties of plant-frugivore networks despite fluctuations in fruit and bird communities in space and time.

    Science.gov (United States)

    Plein, Michaela; Längsfeld, Laura; Neuschulz, Eike Lena; Schultheiss, Christina; Ingmann, Lili; Töpfer, Till; Böhning-Gaese, Katrin; Schleuning, Matthias

    2013-06-01

    Human-induced changes in anthropogenic landscapes are a predominant threat to biodiversity and have been documented to affect mutualistic interactions between plants and animals, such as avian seed dispersal. Interactions between fleshy-fruited plants and frugivorous birds are highly seasonal in temperate ecosystems. Nevertheless, combined effects of landscape modification and seasonal variation on plant-frugivore interactions have never been assessed from a network perspective. Here, we present the first study that simultaneously investigates effects of landscape modification and seasonal variation on plant-frugivore interactions and on functional and interaction diversity of plant-frugivore networks. We recorded visitation rates of 39 frugivorous bird species to 28 fruiting-plant species in Central Germany from early summer to late autumn in hedgerows within three landscape types arranged along a gradient of decreasing anthropogenic modification and increasing structural diversity (i.e., farmland, orchard, forest edge). We analyzed how species richness, abundance, and community composition, as well as functional and interaction diversity of fruiting plants and frugivorous birds changed with landscape type, fruit availability, and season. We found that visitation rates of frugivorous birds were lower in farmland, but only in summer. In autumn, visitation rates were similar in all landscape types and strongly increased with increasing local fruit availability. The functional diversity of fruits and frugivorous birds and their interaction diversity remained surprisingly constant in all landscape types. Due to seasonal changes in communities of fruiting plants and frugivorous birds, functional dispersion of fruiting plants was lower in autumn than in summer, whereas functional richness and dispersion of frugivorous birds was higher in autumn than in summer. Our results indicate that seasonal changes in fruit availability influence the abundance of frugivorous birds

  8. Structural interconversion between a chain polymer and a two-dimensional network accompanied by tunable magnetic properties.

    Science.gov (United States)

    Chen, Chao; Sun, Jian-Ke; Li, Wei; Chen, Chang-Neng; Zhang, Jie

    2011-06-21

    The reaction of 2-hydroxypyrimidine-4,6-dicarboxylic acid (H(3)hpdc) with CuCl(2) under different temperatures gives a chain-like compound [Cu(2)(hpdc)(OH)(H(2)O)(4)]·H(2)O and a layer-like compound [Cu(2)(hpdc)(OH)(H(2)O)], which exhibit structural interconversion and tunable magnetic properties upon dehydration and hydration. This journal is © The Royal Society of Chemistry 2011

  9. Composition Distribution, Damping and Thermal Properties of the Thickness-Continuous Gradient Epoxy/Polyurethane Interpenetrating Polymer Networks

    Directory of Open Access Journals (Sweden)

    Xuesong Lv

    2017-01-01

    Full Text Available A thickness gradient interpenetrating polymer network (IPN was easily created that takes advantage of the relatively poor compatibility and curing rates discrepancy between epoxy (EP and polyurethane (PU. Ultraviolet absorption spectrum (UV-Vis, thermogravimetric (TG, Differential scanning calorimetry (DSC, Dynamic thermomechanical analysis (DMA, Atomic force microscope (AFM and water contact angle were adopted to characterize this IPN structure. We found that the absorption in visible light region, glass-transition temperatures (Tg, thermal decomposition temperatures (Td and Derjaguin–Muller–Toporov (DMT modulus were increasing along with the gradient direction from bottom side to top side of the IPN. While the absorption in ultraviolet region and adhesion force were decreasing along with the gradient direction from bottom side to top side of the IPN. DMA analysis demonstrates that this continuous gradient IPN has a good balance between the damping temperature range and the loss factor which is suitable for using as a self-supporting damping structure.

  10. The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks

    Science.gov (United States)

    Hartman, D.; Hlinka, J.; Paluš, M.; Mantini, D.; Corbetta, M.

    2011-03-01

    In recent years, there has been an increasing interest in the study of large-scale brain activity interaction structure from the perspective of complex networks, based on functional magnetic resonance imaging (fMRI) measurements. To assess the strength of interaction (functional connectivity, FC) between two brain regions, the linear (Pearson) correlation coefficient of the respective time series is most commonly used. Since a potential use of nonlinear FC measures has recently been discussed in this and other fields, the question arises whether particular nonlinear FC measures would be more informative for the graph analysis than linear ones. We present a comparison of network analysis results obtained from the brain connectivity graphs capturing either full (both linear and nonlinear) or only linear connectivity using 24 sessions of human resting-state fMRI. For each session, a matrix of full connectivity between 90 anatomical parcel time series is computed using mutual information. For comparison, connectivity matrices obtained for multivariate linear Gaussian surrogate data that preserve the correlations, but remove any nonlinearity are generated. Binarizing these matrices using multiple thresholds, we generate graphs corresponding to linear and full nonlinear interaction structures. The effect of neglecting nonlinearity is then assessed by comparing the values of a range of graph-theoretical measures evaluated for both types of graphs. Statistical comparisons suggest a potential effect of nonlinearity on the local measures—clustering coefficient and betweenness centrality. Nevertheless, subsequent quantitative comparison shows that the nonlinearity effect is practically negligible when compared to the intersubject variability of the graph measures. Further, on the group-average graph level, the nonlinearity effect is unnoticeable.

  11. Nitrogen-Enriched Carbon/CNT Composites Based on Schiff-Base Networks: Ultrahigh N Content and Enhanced Lithium Storage Properties.

    Science.gov (United States)

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

    2018-02-19

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

  12. Basics of Computer Networking

    CERN Document Server

    Robertazzi, Thomas

    2012-01-01

    Springer Brief Basics of Computer Networking provides a non-mathematical introduction to the world of networks. This book covers both technology for wired and wireless networks. Coverage includes transmission media, local area networks, wide area networks, and network security. Written in a very accessible style for the interested layman by the author of a widely used textbook with many years of experience explaining concepts to the beginner.

  13. Understanding complex interactions using social network analysis.

    Science.gov (United States)

    Pow, Janette; Gayen, Kaberi; Elliott, Lawrie; Raeside, Robert

    2012-10-01

    The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Review of literature and illustration of the application of the method of social network analysis using research examples. First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider. © 2012 Blackwell Publishing Ltd.

  14. Study on the morphology and thermomechanical properties of poly(urethane-siloxane networks based on hyperbranched polyester

    Directory of Open Access Journals (Sweden)

    Pergal Marija V.

    2013-01-01

    Full Text Available Two series of polyurethane films based on hyperbranched polyester of the second pseudogeneration (Boltorn®, 4,4'-methylenediphenyl diisocyanate and two different siloxane prepolymers, α,ω-dihydroxy-(ethylene oxide-poly(dimethylsiloxane-ethylene oxide (EO-PDMS-EO and α,ω-dihydroxypropyl-poly(dimethylsiloxane (HP-PDMS, were prepared by two-step polymerization in solution. The influence of the type and content of soft segment on the morphology, thermomechanical and surface properties of the synthesized polyurethanes was studied by atomic force microscopy (AFM, small-angle X-ray scattering (SAXS, scanning electron microscopy (SEM, dynamic mechanical thermal analysis (DMTA and water absorption measurements. It was found that these techniques confirmed existence of microphase separated morphology. Synthesized polyurethanes exhibited two glass transition temperatures and one second relaxation process. The results showed that polyurethanes based on HP-PDMS had higher surface roughness, better microphase separation and waterproof performances. Samples synthesized with lower PDMS content had less hydrophobic surface, but higher crosslinking density and better thermomechanical properties. (Projekat Ministarstva nauke Republike Srbije, br. 172062

  15. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    Energy Technology Data Exchange (ETDEWEB)

    Biyanto, Totok R. [Department of Engineering Physics, Institute Technology of Sepuluh Nopember Surabaya, Surabaya, Indonesia 60111 (Indonesia)

    2016-06-03

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  16. Effects of Hot-Hydrostatic Canned Extrusion on the Stock Utilization, Microstructure and Mechanical Properties of TiBw/TC4 Composites with Quasi-Continuous Network.

    Science.gov (United States)

    Feng, Yangju; Li, Bing; Cui, Guorong; Zhang, Wencong

    2017-10-25

    In-situ TiB whisker-reinforced Ti-6Al-4V (TC4) titanium matrix composites (TiBw/TC4) with quasi-continuous networks were successfully fabricated by vacuum hot-pressing sintering. The effects of the hot-hydrostatic canned extrusion on stock utilization, microstructure and mechanical properties of the TiBw/TC4 composites were investigated. It was satisfactory that the utilization of composites could be obviously improved by canned extrusion compared to that extruded without canned extrusion. The microstructure results showed that after canned extrusion the grain was refined and the TiB whiskers were distributed from a random array state to a state in which the whiskers were distributed along the extrusion direction. The properties testing results revealed that the tensile strength, the hardness and the ductility of the composites all significantly improved after extrusion due to the grain refinement and orientation of the TiB whisker caused by extrusion. Tensile fracture results showed that when the TiB whiskers were randomly distributed only part of them played a role in strengthening the matrix during the deformation process (as-sintered composites), while when the TiB whiskers were oriented all whiskers could strengthen the matrix during the tensile testing process (as-extruded composites).

  17. Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

    Directory of Open Access Journals (Sweden)

    Ramiro Samano-Robles

    2013-01-01

    Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

  18. Syntheses, Crystal Structures, Magnetic Behaviours, and Thermal Properties of Three Hydrogen-Bonding Networks Containing Dicyanamide and 4-Hydroxypyridine

    Directory of Open Access Journals (Sweden)

    Lingling Zheng

    2013-01-01

    Full Text Available Three new dicyanamide-bridged polymeric complexes of {[Mn(dca2(L2]·2H2O}n (1, {[Cd(dca2(L2]·2H2O}n (2, and {[Co(dca2(L2]2(L}n (3 (dca = dicyanamide, L = pyridinium-4-olate have been synthesized and structurally characterized. In the three compounds, the protons of hydroxyl groups of 4-hydroxypyridine transfer to pyridyl nitrogen atoms. Compounds 1 and 2 are isomorphous forming one-dimensional [M(dca2(L2]n chains where metals are connected by double dca anions. These one-dimensional chains are extended into two-dimensional layers through weak C–H⋯N hydrogen bonds. Further, these layers are assembled into a three-dimensional supramolecular network through N–H⋯O, O–H⋯O hydrogen bonds. Complex 3 is a coordination layer of (4, 4 topology with octahedral metal centers linked by four single μ1,5-bridges. These layers are interlocked by N–H⋯O, O–H⋯O hydrogen bonds from coordinated water molecules and free L molecules, which leads to a three-dimensional supramolecular architecture. The variable temperature magnetic susceptibilities measurement of compounds 1 and 3 shows the existence of weak antiferromagnetic interactions between the metal centers. The thermogravimetric analyses of the compounds 1–3 are also discussed.

  19. TRENDS IN THE CONVERGENCE OF WIRELESS NETWORKS

    Directory of Open Access Journals (Sweden)

    Daniel SORA

    2011-01-01

    Full Text Available In today’s technological market, there are many types of networks. These networks include wireless personal area networks (WPANs, wireless local area networks (WLANs, wireless metropolitan area networks (WMANs, and cellular networks. A vision of a future convergence of networks envisaged for WPANs, WLANs, WiMax, and cellular networks is presented in this paper.

  20. Hydraulic response in flooded stream networks

    Science.gov (United States)

    Åkesson, Anna; Wörman, Anders; Bottacin-Busolin, Andrea

    2015-01-01

    Average water travel times through a stream network were determined as a function of stage (discharge) and stream network properties. Contrary to most previous studies on the topic, the present work allowed for streamflow velocities to vary spatially (for most of the analyses) as well as temporally. The results show that different stream network mechanisms and properties interact in a complex and stage-dependent manner, implying that the relative importance of the different hydraulic properties varies in space and over time. Theoretical reasoning, based on the central temporal moments derived from the kinematic-diffusive wave equation in a semi-2-D formulation including the effects of flooded cross sections, shows that the hydraulic properties in contrast to the geomorphological properties will become increasingly important as the discharge increases, stressing the importance of accurately describing the hydraulic mechanisms within stream networks. Using the physically based, stage-dependent response function as a parameterization basis for the streamflow routing routine (a linear reservoir) of a hydrological model, discharge predictions were shown to improve in two Swedish catchments, compared with a conventional, statistically based parameterization scheme. Predictions improved for a wide range of modeled scenarios, for the entire discharge series as well as for peak flow conditions. The foremost novelty of the study lies in that the physically based response function for a streamflow routing routine has successfully been determined independent of calibration, i.e., entirely through process-based hydraulic stream network modeling.

  1. Emergent complex network geometry.

    Science.gov (United States)

    Wu, Zhihao; Menichetti, Giulia; Rahmede, Christoph; Bianconi, Ginestra

    2015-05-18

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geometrical growing networks are present in a large set of real networks describing biological, social and technological systems.

  2. Dynamics of social networks

    OpenAIRE

    Ebel, Holger; Davidsen, Joern; Bornholdt, Stefan

    2003-01-01

    Complex networks as the World Wide Web, the web of human sexual contacts or criminal networks often do not have an engineered architecture but instead are self-organized by the actions of a large number of individuals. From these local interactions non-trivial global phenomena can emerge as small-world properties or scale-free degree distributions. A simple model for the evolution of acquaintance networks highlights the essential dynamical ingredients necessary to obtain such complex network ...

  3. Mutational robustness of gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

    Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.

  4. Random graph models for dynamic networks

    Science.gov (United States)

    Zhang, Xiao; Moore, Cristopher; Newman, Mark E. J.

    2017-10-01

    Recent theoretical work on the modeling of network structure has focused primarily on networks that are static and unchanging, but many real-world networks change their structure over time. There exist natural generalizations to the dynamic case of many static network models, including the classic random graph, the configuration model, and the stochastic block model, where one assumes that the appearance and disappearance of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. Here we give an introduction to this class of models, showing for instance how one can compute their equilibrium properties. We also demonstrate their use in data analysis and statistical inference, giving efficient algorithms for fitting them to observed network data using the method of maximum likelihood. This allows us, for example, to estimate the time constants of network evolution or infer community structure from temporal network data using cues embedded both in the probabilities over time that node pairs are connected by edges and in the characteristic dynamics of edge appearance and disappearance. We illustrate these methods with a selection of applications, both to computer-generated test networks and real-world examples.

  5. Efficient exploration of multiplex networks

    Science.gov (United States)

    Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

    2016-04-01

    Efficient techniques to navigate networks with local information are fundamental to sample large-scale online social systems and to retrieve resources in peer-to-peer systems. Biased random walks, i.e. walks whose motion is biased on properties of neighbouring nodes, have been largely exploited to design smart local strategies to explore a network, for instance by constructing maximally mixing trajectories or by allowing an almost uniform sampling of the nodes. Here we introduce and study biased random walks on multiplex networks, graphs where the nodes are related through different types of links organised in distinct and interacting layers, and we provide analytical solutions for their long-time properties, including the stationary occupation probability distribution and the entropy rate. We focus on degree-biased random walks and distinguish between two classes of walks, namely those whose transition probability depends on a number of parameters which is extensive in the number of layers, and those whose motion depends on intrinsically multiplex properties of the neighbouring nodes. We analyse the effect of the structure of the multiplex network on the steady-state behaviour of the walkers, and we find that heterogeneous degree distributions as well as the presence of inter-layer degree correlations and edge overlap determine the extent to which a multiplex can be efficiently explored by a biased walk. Finally we show that, in real-world multiplex transportation networks, the trade-off between efficient navigation and resilience to link failure has resulted into systems whose diffusion properties are qualitatively different from those of appropriately randomised multiplex graphs. This fact suggests that multiplexity is an important ingredient to include in the modelling of real-world systems.

  6. Network Warrior

    CERN Document Server

    Donahue, Gary

    2011-01-01

    Pick up where certification exams leave off. With this practical, in-depth guide to the entire network infrastructure, you'll learn how to deal with real Cisco networks, rather than the hypothetical situations presented on exams like the CCNA. Network Warrior takes you step by step through the world of routers, switches, firewalls, and other technologies based on the author's extensive field experience. You'll find new content for MPLS, IPv6, VoIP, and wireless in this completely revised second edition, along with examples of Cisco Nexus 5000 and 7000 switches throughout. Topics include: An

  7. Engineering technology for networks

    Science.gov (United States)

    Paul, Arthur S.; Benjamin, Norman

    1991-01-01

    Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling.

  8. Softening in random networks of non-identical beams

    Science.gov (United States)

    Ban, Ehsan; Barocas, Victor H.; Shephard, Mark S.; Picu, R. Catalin

    2016-02-01

    Random fiber networks are assemblies of elastic elements connected in random configurations. They are used as models for a broad range of fibrous materials including biopolymer gels and synthetic nonwovens. Although the mechanics of networks made from the same type of fibers has been studied extensively, the behavior of composite systems of fibers with different properties has received less attention. In this work we numerically and theoretically study random networks of beams and springs of different mechanical properties. We observe that the overall network stiffness decreases on average as the variability of fiber stiffness increases, at constant mean fiber stiffness. Numerical results and analytical arguments show that for small variabilities in fiber stiffness the amount of network softening scales linearly with the variance of the fiber stiffness distribution. This result holds for any beam structure and is expected to apply to a broad range of materials including cellular solids.

  9. Softening in Random Networks of Non-Identical Beams.

    Science.gov (United States)

    Ban, Ehsan; Barocas, Victor H; Shephard, Mark S; Picu, Catalin R

    2016-02-01

    Random fiber networks are assemblies of elastic elements connected in random configurations. They are used as models for a broad range of fibrous materials including biopolymer gels and synthetic nonwovens. Although the mechanics of networks made from the same type of fibers has been studied extensively, the behavior of composite systems of fibers with different properties has received less attention. In this work we numerically and theoretically study random networks of beams and springs of different mechanical properties. We observe that the overall network stiffness decreases on average as the variability of fiber stiffness increases, at constant mean fiber stiffness. Numerical results and analytical arguments show that for small variabilities in fiber stiffness the amount of network softening scales linearly with the variance of the fiber stiffness distribution. This result holds for any beam structure and is expected to apply to a broad range of materials including cellular solids.

  10. Mining protein networks for synthetic genetic interactions

    Directory of Open Access Journals (Sweden)

    Zhao Shan

    2008-10-01

    Full Text Available Abstract Background The local connectivity and global position of a protein in a protein interaction network are known to correlate with some of its functional properties, including its essentiality or dispensability. It is therefore of interest to extend this observation and examine whether network properties of two proteins considered simultaneously can determine their joint dispensability, i.e., their propensity for synthetic sick/lethal interaction. Accordingly, we examine the predictive power of protein interaction networks for synthetic genetic interaction in Saccharomyces cerevisiae, an organism in which high confidence protein interaction networks are available and synthetic sick/lethal gene pairs have been extensively identified. Results We design a support vector machine system that uses graph-theoretic properties of two proteins in a protein interaction network as input features for prediction of synthetic sick/lethal interactions. The system is trained on interacting and non-interacting gene pairs culled from large scale genetic screens as well as literature-curated data. We find that the method is capable of predicting synthetic genetic interactions with sensitivity and specificity both exceeding 85%. We further find that the prediction performance is reasonably robust with respect to errors in the protein interaction network and with respect to changes in the features of test datasets. Using the prediction system, we carried out novel predictions of synthetic sick/lethal gene pairs at a genome-wide scale. These pairs appear to have functional properties that are similar to those that characterize the known synthetic lethal gene pairs. Conclusion Our analysis shows that protein interaction networks can be used to predict synthetic lethal interactions with accuracies on par with or exceeding that of other computational methods that use a variety of input features, including functional annotations. This indicates that protein

  11. Affective Networks

    Directory of Open Access Journals (Sweden)

    Jodi Dean

    2010-02-01

    Full Text Available This article sets out the idea of affective networks as a constitutive feature of communicative capitalism. It explores the circulation of intensities in contemporary information and communication networks, arguing that this circulation should be theorized in terms of the psychoanalytic notion of the drive. The article includes critical engagements with theorists such as Guy Debord, Jacques Lacan, Tiziana Terranova, and Slavoj Zizek.

  12. Exploring network structure, dynamics, and function using networkx

    Energy Technology Data Exchange (ETDEWEB)

    Hagberg, Aric [Los Alamos National Laboratory; Swart, Pieter [Los Alamos National Laboratory; S Chult, Daniel [COLGATE UNIV

    2008-01-01

    NetworkX is a Python language package for exploration and analysis of networks and network algorithms. The core package provides data structures for representing many types of networks, or graphs, including simple graphs, directed graphs, and graphs with parallel edges and self loops. The nodes in NetworkX graphs can be any (hashable) Python object and edges can contain arbitrary data; this flexibility mades NetworkX ideal for representing networks found in many different scientific fields. In addition to the basic data structures many graph algorithms are implemented for calculating network properties and structure measures: shortest paths, betweenness centrality, clustering, and degree distribution and many more. NetworkX can read and write various graph formats for eash exchange with existing data, and provides generators for many classic graphs and popular graph models, such as the Erdoes-Renyi, Small World, and Barabasi-Albert models, are included. The ease-of-use and flexibility of the Python programming language together with connection to the SciPy tools make NetworkX a powerful tool for scientific computations. We discuss some of our recent work studying synchronization of coupled oscillators to demonstrate how NetworkX enables research in the field of computational networks.

  13. 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

    of physiochemical properties for mutations in HIV-1 protease (PR) and reverse transcriptase (RT) to predict phenotypic susceptibility to all currently approved ARVs. METHOD: We extracted pairs of PR and RT gene sequences (n=1507; 98.5% sub-type B) and their corresponding exact phenotype values (PhenoSense only, n...... observed and predicted phenotype values in the 10-fold cross-validation ranged from: 0.75 (tenofovir) to 0.94 [lamivudine (3TC)] for nucleoside RT inhibitors (NRTIs); 0.82 [efavirenz (EFV)] to 0.83 [nevirapine (NVP)] for non-nucleoside RT inhibitors (NNRTIs); and 0.83 (atazanavir) to 0.92 (ritonavir......) for PR inhibitors (PIs). For the validation set the correlation coefficients ranged from 0.76 (didanosine) to 0.96 (3TC) for NRTIs; 0.68 (EFV) to 0.81 (NVP) for NNRTIs; and 0.88 (amprenavir) to 0.95 (saquinavir) for PIs. For C sub-type predictions, with ANNs trained on sub-type B data, the correlation...

  14. A Network Formation Model Based on Subgraphs

    CERN Document Server

    Chandrasekhar, Arun

    2016-01-01

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

  15. Metal-organic and supramolecular networks driven by 5-chloronicotinic acid: Hydrothermal self-assembly synthesis, structural diversity, luminescent and magnetic properties

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Zhu-Qing, E-mail: zqgao2008@163.com [School of Chemical and Biological Engineering, Taiyuan University of Science and Technology, Taiyuan 030021 (China); Li, Hong-Jin [School of Chemical and Biological Engineering, Taiyuan University of Science and Technology, Taiyuan 030021 (China); Gu, Jin-Zhong, E-mail: gujzh@lzu.edu.cn [College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000 (China); Zhang, Qing-Hua [School of Chemical and Biological Engineering, Taiyuan University of Science and Technology, Taiyuan 030021 (China); Kirillov, Alexander M. [Centro de Química Estrutural, Complexo I, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049–001 Lisbon (Portugal)

    2016-09-15

    Four new crystalline solids, namely [Co{sub 2}(µ{sub 2}-5-Clnic){sub 2}(µ{sub 3}-5-Clnic){sub 2}(µ{sub 2}-H{sub 2}O)]{sub n} (1), [Co(5-Clnic){sub 2}(H{sub 2}O){sub 4}]·2(5-ClnicH) (2), [Pb(µ{sub 2}-5-Clnic){sub 2}(phen)]{sub n} (3), and [Cd(5-Clnic){sub 2}(phen){sub 2}]·3H{sub 2}O (4) were generated by hydrothermal self-assembly methods from the corresponding metal(II) chlorides, 5-chloronicotinic acid (5-ClnicH) as a principal building block, and 1,10-phenanthroline (phen) as an ancillary ligand (optional). All the products 1–4 were characterized by IR spectroscopy, elemental analysis, thermogravimetric (TGA), powder X-ray diffraction (PXRD) and single-crystal X-ray diffraction. Their structures range from an intricate 3D metal-organic network 1 with the 3,6T7 topology to a ladder-like 1D coordination polymer 3 with the 2C1 topology, whereas compounds 2 and 4 are the discrete 0D monomers. The structures of 2 and 4 are further extended (0D→2D or 0D→3D) by hydrogen bonds, generating supramolecular networks with the 3,8L18 and ins topologies, respectively. Synthetic aspects, structural features, thermal stability, magnetic (for 1) and luminescent (for 3 and 4) properties were also investigated and discussed. - Graphical abstract: A new series of crystalline solids was self-assembled and fully characterized; their structural, topological, luminescent and magnetic features were investigated. Display Omitted.

  16. The dichotomy in degree correlation of biological networks.

    Directory of Open Access Journals (Sweden)

    Dapeng Hao

    Full Text Available Most complex networks from different areas such as biology, sociology or technology, show a correlation on node degree where the possibility of a link between two nodes depends on their connectivity. It is widely believed that complex networks are either disassortative (links between hubs are systematically suppressed or assortative (links between hubs are enhanced. In this paper, we analyze a variety of biological networks and find that they generally show a dichotomous degree correlation. We find that many properties of biological networks can be explained by this dichotomy in degree correlation, including the neighborhood connectivity, the sickle-shaped clustering coefficient distribution and the modularity structure. This dichotomy distinguishes biological networks from real disassortative networks or assortative networks such as the Internet and social networks. We suggest that the modular structure of networks accounts for the dichotomy in degree correlation and vice versa, shedding light on the source of modularity in biological networks. We further show that a robust and well connected network necessitates the dichotomy of degree correlation, suggestive of an evolutionary motivation for its existence. Finally, we suggest that a dichotomous degree correlation favors a centrally connected modular network, by which the integrity of network and specificity of modules might be reconciled.

  17. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  18. A linear model for characterization of synchronization frequencies of neural networks.

    Science.gov (United States)

    Lv, Peili; Hu, Xintao; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

    2014-02-01

    The synchronization frequency of neural networks and its dynamics have important roles in deciphering the working mechanisms of the brain. It has been widely recognized that the properties of functional network synchronization and its dynamics are jointly determined by network topology, network connection strength, i.e., the connection strength of different edges in the network, and external input signals, among other factors. However, mathematical and computational characterization of the relationships between network synchronization frequency and these three important factors are still lacking. This paper presents a novel computational simulation framework to quantitatively characterize the relationships between neural network synchronization frequency and network attributes and input signals. Specifically, we constructed a series of neural networks including simulated small-world networks, real functional working memory network derived from functional magnetic resonance imaging, and real large-scale structural brain networks derived from diffusion tensor imaging, and performed synchronization simulations on these networks via the Izhikevich neuron spiking model. Our experiments demonstrate that both of the network synchronization strength and synchronization frequency change according to the combination of input signal frequency and network self-synchronization frequency. In particular, our extensive experiments show that the network synchronization frequency can be represented via a linear combination of the network self-synchronization frequency and the input signal frequency. This finding could be attributed to an intrinsically-preserved principle in different types of neural systems, offering novel insights into the working mechanism of neural systems.

  19. Network gravity

    Science.gov (United States)

    Lombard, John

    2017-01-01

    We introduce the construction of a new framework for probing discrete emergent geometry and boundary-boundary observables based on a fundamentally a-dimensional underlying network structure. Using a gravitationally motivated action with Forman weighted combinatorial curvatures and simplicial volumes relying on a decomposition of an abstract simplicial complex into realized embeddings of proper skeletons, we demonstrate properties such as a minimal volume-scale cutoff, the necessity of a term playing the role of a positive definite cosmological constant as a regulator for nondegenerate geometries, and naturally emergent simplicial structures from Metropolis network evolution simulations with no restrictions on attachment rules or regular building blocks. We see emergent properties which echo results from both the spinfoam formalism and causal dynamical triangulations in quantum gravity, and provide analytical and numerical results to support the analogy. We conclude with a summary of open questions and intent for future work in developing the program.

  20. Scaling solutions for connectivity and conductivity of continuous random networks.

    Science.gov (United States)

    Galindo-Torres, S A; Molebatsi, T; Kong, X-Z; Scheuermann, A; Bringemeier, D; Li, L

    2015-10-01

    Connectivity and conductivity of two-dimensional fracture networks (FNs), as an important type of continuous random networks, are examined systematically through Monte Carlo simulations under a variety of conditions, including different power law distributions of the fracture lengths and domain sizes. The simulation results are analyzed using analogies of the percolation theory for discrete random networks. With a characteristic length scale and conductivity scale introduced, we show that the connectivity and conductivity of FNs can be well described by universal scaling solutions. These solutions shed light on previous observations of scale-dependent FN behavior and provide a powerful method for quantifying effective bulk properties of continuous random networks.