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

DOE PAGES

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

2015-05-15

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

Chinese lexical networks: The structure, function and formation

NASA Astrophysics Data System (ADS)

Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

2012-11-01

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

Structure of Particle Networks in Capillary Suspensions with Wetting and Nonwetting Fluids

PubMed Central

2016-01-01

The mechanical properties of a suspension can be dramatically altered by adding a small amount of a secondary fluid that is immiscible with the bulk phase. The substantial changes in the strength of these capillary suspensions arise due to the capillary force inducing a percolating particle network. Spatial information on the structure of the particle networks is obtained using confocal microscopy. It is possible, for the first time, to visualize the different types of percolating structures of capillary suspensions in situ. These capillary networks are unique from other types of particulate networks due to the nature of the capillary attraction. We investigate the influence of the three-phase contact angle on the structure of an oil-based capillary suspension with silica microspheres. Contact angles smaller than 90° lead to pendular networks of particles connected with single capillary bridges or clusters comparable to the funicular state in wet granular matter, whereas a different clustered structure, the capillary state, forms for angles larger than 90°. Particle pair distribution functions are obtained by image analysis, which demonstrate differences in the network microstructures. When porous particles are used, the pendular conformation also appears for apparent contact angles larger than 90°. The complex shear modulus can be correlated to these microstructural changes. When the percolating structure is formed, the complex shear modulus increases by nearly three decades. Pendular bridges lead to stronger networks than the capillary state network conformations, but the capillary state clusters are nevertheless much stronger than pure suspensions without the added liquid. PMID:26807651

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Enhancing robustness and immunization in geographical networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang Liang; Department of Physics, Lanzhou University, Lanzhou 730000; Yang Kongqing

2007-03-15

We find that different geographical structures of networks lead to varied percolation thresholds, although these networks may have similar abstract topological structures. Thus, strategies for enhancing robustness and immunization of a geographical network are proposed. Using the generating function formalism, we obtain an explicit form of the percolation threshold q{sub c} for networks containing arbitrary order cycles. For three-cycles, the dependence of q{sub c} on the clustering coefficients is ascertained. The analysis substantiates the validity of the strategies with analytical evidence.

Understanding the role of hydrogen bonding in the aggregation of fumed silica particles in triglyceride solvents.

PubMed

Whitby, Catherine P; Krebsz, Melinda; Booty, Samuel J

2018-10-01

Fumed silica particles are thought to thicken organic solvents into gels by aggregating to form networks. Hydrogen bonding between silanol groups on different particle surfaces causes the aggregation. The gel structure and hence flow behaviour is altered by varying the proportion of silanol groups on the particle surfaces. However, characterising the gel using rheology measurements alone is not sufficient to optimise the aggregation. We have used confocal microscopy to characterise the changes in the network microstructure caused by altering the particle surface chemistry. Organogels were formed by dispersing fumed silica nanoparticles in a triglyceride solvent. The particle surface chemistry was systematically varied from oleophobic to oleophilic by functionalisation with hydrocarbons. We directly visualised the particle networks using confocal scanning laser microscopy and investigated the correlations between the network structure and the shear response of the organogels. Our key finding is that the sizes of the pore spaces in the networks depend on the fraction of silanol groups available to form hydrogen bonds. The reduction in the network elasticity of gels formed by methylated particles can be accounted for by the increasing pore size and tenuous nature of the networks. This is the first report that characterises the changes in the microstructure of fumed silica particle networks in non-polar solvents caused by manipulating the particle surface chemistry. Copyright © 2018 Elsevier Inc. All rights reserved.

Applications of Social Network Analysis

NASA Astrophysics Data System (ADS)

Thilagam, P. Santhi

A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

Structure and energetics of hydrogen-bonded networks of methanol on close packed transition metal surfaces

NASA Astrophysics Data System (ADS)

Murphy, Colin J.; Carrasco, Javier; Lawton, Timothy J.; Liriano, Melissa L.; Baber, Ashleigh E.; Lewis, Emily A.; Michaelides, Angelos; Sykes, E. Charles H.

2014-07-01

Methanol is a versatile chemical feedstock, fuel source, and energy storage material. Many reactions involving methanol are catalyzed by transition metal surfaces, on which hydrogen-bonded methanol overlayers form. As with water, the structure of these overlayers is expected to depend on a delicate balance of hydrogen bonding and adsorbate-substrate bonding. In contrast to water, however, relatively little is known about the structures methanol overlayers form and how these vary from one substrate to another. To address this issue, herein we analyze the hydrogen bonded networks that methanol forms as a function of coverage on three catalytically important surfaces, Au(111), Cu(111), and Pt(111), using a combination of scanning tunneling microscopy and density functional theory. We investigate the effect of intermolecular interactions, surface coverage, and adsorption energies on molecular assembly and compare the results to more widely studied water networks on the same surfaces. Two main factors are shown to direct the structure of methanol on the surfaces studied: the surface coverage and the competition between the methanol-methanol and methanol-surface interactions. Additionally, we report a new chiral form of buckled hexamer formed by surface bound methanol that maximizes the interactions between methanol monomers by sacrificing interactions with the surface. These results serve as a direct comparison of interaction strength, assembly, and chirality of methanol networks on Au(111), Cu(111), and Pt(111) which are catalytically relevant for methanol oxidation, steam reforming, and direct methanol fuel cells.

The Emergence of Embedded Relations and Group Formation in Networks of Competition

ERIC Educational Resources Information Center

Thye, Shane R.; Lawler, Edward J.; Yoon, Jeongkoo

2011-01-01

This study examines how and when small networks of self-interested agents generate a group tie or affiliation at the network level. A group affiliation is formed when actors (a) perceive themselves as members of a group and (b) share resources with each other despite an underlying competitive structure. We apply a concept of structural cohesion to…

LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA

PubMed Central

Salter-Townshend, Michael; McCormick, Tyler H.

2018-01-01

Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090–1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)]. PMID:29721127

LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA.

PubMed

Salter-Townshend, Michael; McCormick, Tyler H

2017-09-01

Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090-1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)].

Structural Behavioral Study on the General Aviation Network Based on Complex Network

NASA Astrophysics Data System (ADS)

Zhang, Liang; Lu, Na

2017-12-01

The general aviation system is an open and dissipative system with complex structures and behavioral features. This paper has established the system model and network model for general aviation. We have analyzed integral attributes and individual attributes by applying the complex network theory and concluded that the general aviation network has influential enterprise factors and node relations. We have checked whether the network has small world effect, scale-free property and network centrality property which a complex network should have by applying degree distribution of functions and proved that the general aviation network system is a complex network. Therefore, we propose to achieve the evolution process of the general aviation industrial chain to collaborative innovation cluster of advanced-form industries by strengthening network multiplication effect, stimulating innovation performance and spanning the structural hole path.

Stripline Antenna Beam-Forming Network

NASA Technical Reports Server (NTRS)

Cramer, P. W.

1984-01-01

Stripline antenna beam-forming network includes 87 beam ports and 136 feed-element ports and contained on only two microstrip boards. Both uplink and downlink strips supported on same boards. Originally used for communications coverage of continental United States for Land Mobile Satellite System, structure of interest to antenna designers in other applications.

Assembly kinetics determine the architecture of α-actinin crosslinked F-actin networks.

PubMed

Falzone, Tobias T; Lenz, Martin; Kovar, David R; Gardel, Margaret L

2012-05-29

The actin cytoskeleton is organized into diverse meshworks and bundles that support many aspects of cell physiology. Understanding the self-assembly of these actin-based structures is essential for developing predictive models of cytoskeletal organization. Here we show that the competing kinetics of bundle formation with the onset of dynamic arrest arising from filament entanglements and crosslinking determine the architecture of reconstituted actin networks formed with α-actinin crosslinks. Crosslink-mediated bundle formation only occurs in dilute solutions of highly mobile actin filaments. As actin polymerization proceeds, filament mobility and bundle formation are arrested concomitantly. By controlling the onset of dynamic arrest, perturbations to actin assembly kinetics dramatically alter the architecture of biochemically identical samples. Thus, the morphology of reconstituted F-actin networks is a kinetically determined structure similar to those formed by physical gels and glasses. These results establish mechanisms controlling the structure and mechanics in diverse semiflexible biopolymer networks.

Mental health network governance: comparative analysis across Canadian regions

PubMed Central

Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

2010-01-01

Objective Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Methods Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Results Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. Discussion In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration. PMID:21289999

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Structural network heterogeneities and network dynamics: A possible dynamical mechanism for hippocampal memory reactivation

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina R.; Zochowski, Michal

2007-01-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Reconciling Hierarchical and Edge Organizations: 9-11 Revisited

DTIC Science & Technology

2014-06-01

the hierarchical structure, despite claiming to be networked. Hence, our research asks whether these two archetypal forms can be reconciled with one...asks whether these two archetypal forms can be reconciled with one another. By revisiting a case study of the events of September 11th, 2001...organizational form best suited to network-centric operations. Drawing on Mintzberg’s (1979) work on organizational archetypes , five classic organizational

Spontaneous scale-free structure in adaptive networks with synchronously dynamical linking

NASA Astrophysics Data System (ADS)

Yuan, Wu-Jie; Zhou, Jian-Fang; Li, Qun; Chen, De-Bao; Wang, Zhen

2013-08-01

Inspired by the anti-Hebbian learning rule in neural systems, we study how the feedback from dynamical synchronization shapes network structure by adding new links. Through extensive numerical simulations, we find that an adaptive network spontaneously forms scale-free structure, as confirmed in many real systems. Moreover, the adaptive process produces two nontrivial power-law behaviors of deviation strength from mean activity of the network and negative degree correlation, which exists widely in technological and biological networks. Importantly, these scalings are robust to variation of the adaptive network parameters, which may have meaningful implications in the scale-free formation and manipulation of dynamical networks. Our study thus suggests an alternative adaptive mechanism for the formation of scale-free structure with negative degree correlation, which means that nodes of high degree tend to connect, on average, with others of low degree and vice versa. The relevance of the results to structure formation and dynamical property in neural networks is briefly discussed as well.

Physics textbooks from the viewpoint of network structures

NASA Astrophysics Data System (ADS)

Králiková, Petra; Teleki, Aba

2017-01-01

We can observe self-organized networks all around us. These networks are, in general, scale invariant networks described by the Bianconi-Barabasi model. The self-organized networks (networks formed naturally when feedback acts on the system) show certain universality. These networks, in simplified models, have scale invariant distribution (Pareto distribution type I) and parameter α has value between 2 and 5. The textbooks are extremely important in the learning process and from this reason we studied physics textbook at the level of sentences and physics terms (bipartite network). The nodes represent physics terms, sentences, and pictures, tables, connected by links (by physics terms and transitional words and transitional phrases). We suppose that learning process are more robust and goes faster and easier if the physics textbook has a structure similar to structures of self-organized networks.

Force Exertion and Transmission in Cross-Linked Actin Networks

NASA Astrophysics Data System (ADS)

Stam, Samantha

Cells are responsive to external cues in their environment telling them to proliferate or migrate within their surrounding tissue. Sensing of cues that are mechanical in nature, such stiffness of a tissue or forces transmitted from other cells, is believed to involve the cytoskeleton of a cell. The cytoskeleton is a complex network of proteins consisting of polymers that provide structural support, motor proteins that remodel these structures, and many others. We do not yet have a complete understanding of how cytoskeletal components respond to either internal or external mechanical force and stiffness. Such an understanding should involve mechanisms by which constituent molecules, such as motor proteins, are responsive to mechanics. Additionally, physical models of how forces are transmitted through biopolymer networks are necessary. My research has focused on networks formed by the cytoskeletal filament actin and the molecular motor protein myosin II. Actin filaments form networks and bundles that form a structural framework of the cell, and myosin II slides actin filaments. In this thesis, we show that stiffness of an elastic load that opposes myosin-generated actin sliding has a very sharp effect on the myosin force output in simulations. Secondly, we show that the stiffness and connectivity of cytoskeletal filaments regulates the contractility and anisotropy of network deformations that transmit force on material length scales. Together, these results have implications for predicting and interpreting the deformations and forces in biopolymeric active materials.

Correlation and network analysis of global financial indices

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

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

NASA Astrophysics Data System (ADS)

Mora, A.; Han, F.; Lubineau, G.

2018-04-01

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

Correlation and network analysis of global financial indices.

PubMed

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

Network Search: A New Way of Seeing the Education Knowledge Domain

ERIC Educational Resources Information Center

McFarland, Daniel; Klopfer, Eric

2010-01-01

Background: The educational knowledge domain may be understood as a system composed of multiple, co-evolving networks that reflect the form and content of a cultural field. This paper describes the educational knowledge domain as having a community structure (form) based in relations of production (authoring) and consumption (referencing), and a…

Structure and mechanics of aegagropilae fiber network.

PubMed

Verhille, Gautier; Moulinet, Sébastien; Vandenberghe, Nicolas; Adda-Bedia, Mokhtar; Le Gal, Patrice

2017-05-02

Fiber networks encompass a wide range of natural and manmade materials. The threads or filaments from which they are formed span a wide range of length scales: from nanometers, as in biological tissues and bundles of carbon nanotubes, to millimeters, as in paper and insulation materials. The mechanical and thermal behavior of these complex structures depends on both the individual response of the constituent fibers and the density and degree of entanglement of the network. A question of paramount importance is how to control the formation of a given fiber network to optimize a desired function. The study of fiber clustering of natural flocs could be useful for improving fabrication processes, such as in the paper and textile industries. Here, we use the example of aegagropilae that are the remains of a seagrass ( Posidonia oceanica ) found on Mediterranean beaches. First, we characterize different aspects of their structure and mechanical response, and second, we draw conclusions on their formation process. We show that these natural aggregates are formed in open sea by random aggregation and compaction of fibers held together by friction forces. Although formed in a natural environment, thus under relatively unconstrained conditions, the geometrical and mechanical properties of the resulting fiber aggregates are quite robust. This study opens perspectives for manufacturing complex fiber network materials.

Characterization of the fibrillar layer at the epithelial-mesenchymal junction in tooth germs.

PubMed

Sawada, T; Inoue, S

1994-12-01

A characteristic layer containing numerous fibrils is associated with the basement membrane of the inner enamel epithelium during the early stages of odontogenesis. However, its nature is not well understood. In this study, the layer was examined with high-resolution electron microscopy and immuno-histochemical staining. Tooth germs of monkeys (Macaca fuscata) were studied and each fibril in the layer was found to be a tubular structure, 8-9 nm in width, resembling a "basotubule", the tubular structure previously observed in various basement membranes. The space between the fibrils was filled with a network formed by irregular anastomosing strands with an average thickness of 4 nm; these strands resembled the "cords" forming the network in the lamina densa of basement membranes. After immunoperoxidase staining, fine threads immunoreactive for laminin staining were seen winding along the strands of the network, and 1.5-nm wide filaments, immunoreactive for type IV collagen, took the form of a network arrangement. The 5-nm-wide ribbon-like structures associated with the strands were identified as heparan sulfate proteoglycan by immunostaining. These results are similar to those obtained for the cord network of the lamina densa. The "fibrillar layer" therefore represents a highly specialized lamina fibroreticularis of the basement membrane of the inner enamel epithelium, and rich in basotubules.

Drying Affects the Fiber Network in Low Molecular Weight Hydrogels

PubMed Central

2017-01-01

Low molecular weight gels are formed by the self-assembly of a suitable small molecule gelator into a three-dimensional network of fibrous structures. The gel properties are determined by the fiber structures, the number and type of cross-links and the distribution of the fibers and cross-links in space. Probing these structures and cross-links is difficult. Many reports rely on microscopy of dried gels (xerogels), where the solvent is removed prior to imaging. The assumption is made that this has little effect on the structures, but it is not clear that this assumption is always (or ever) valid. Here, we use small angle neutron scattering (SANS) to probe low molecular weight hydrogels formed by the self-assembly of dipeptides. We compare scattering data for wet and dried gels, as well as following the drying process. We show that the assumption that drying does not affect the network is not always correct. PMID:28631478

Learning Orthographic Structure With Sequential Generative Neural Networks.

PubMed

Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

2016-04-01

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

Inferring and analysis of social networks using RFID check-in data in China

PubMed Central

Liu, Tao; Liu, Shouyin; Ge, Shuangkui

2017-01-01

Social networks play an important role in our daily lives. However, social ties are rather elusive to quantify, especially for large groups of subjects over prolonged periods of time. In this work, we first propose a methodology for extracting social ties from long spatio-temporal data streams, where the subjects are 17,795 undergraduates from a university of China and the data streams are the 9,147,106 time-stamped RFID check-in records left behind by them during one academic year. By several metrics mentioned below, we then analyze the structure of the social network. Our results center around three main observations. First, we characterize the global structure of the network, and we confirm the small-world phenomenon on a global scale. Second, we find that the network shows clear community structure. And we observe that younger students at lower levels tend to form large communities, while students at higher levels mostly form smaller communities. Third, we characterize the assortativity patterns by studying the basic demographic and network properties of users. We observe clear degree assortativity on a global scale. Furthermore, we find a strong effect of grade and school on tie formation preference, but we do not find any strong region homophily. Our research may help us to elucidate the structural characteristics and the preference of the formation of social ties in college students’ social network. PMID:28570586

Network, cellular, and molecular mechanisms underlying long-term memory formation.

PubMed

Carasatorre, Mariana; Ramírez-Amaya, Víctor

2013-01-01

The neural network stores information through activity-dependent synaptic plasticity that occurs in populations of neurons. Persistent forms of synaptic plasticity may account for long-term memory storage, and the most salient forms are the changes in the structure of synapses. The theory proposes that encoding should use a sparse code and evidence suggests that this can be achieved through offline reactivation or by sparse initial recruitment of the network units. This idea implies that in some cases the neurons that underwent structural synaptic plasticity might be a subpopulation of those originally recruited; However, it is not yet clear whether all the neurons recruited during acquisition are the ones that underwent persistent forms of synaptic plasticity and responsible for memory retrieval. To determine which neural units underlie long-term memory storage, we need to characterize which are the persistent forms of synaptic plasticity occurring in these neural ensembles and the best hints so far are the molecular signals underlying structural modifications of the synapses. Structural synaptic plasticity can be achieved by the activity of various signal transduction pathways, including the NMDA-CaMKII and ACh-MAPK. These pathways converge with the Rho family of GTPases and the consequent ERK 1/2 activation, which regulates multiple cellular functions such as protein translation, protein trafficking, and gene transcription. The most detailed explanation may come from models that allow us to determine the contribution of each piece of this fascinating puzzle that is the neuron and the neural network.

Assembly of one-dimensional supramolecular objects: From monomers to networks

NASA Astrophysics Data System (ADS)

Sayar, Mehmet; Stupp, Samuel I.

2005-07-01

One-dimensional supramolecular aggregates can form networks at exceedingly low concentrations. Recent experiments in several laboratories, including our own, have demonstrated the formation of gels by these systems at concentrations well under 1% by weight. The systems of interest in our laboratory form either cylindrical nanofibers or ribbons as a result of strong noncovalent interactions among monomers. The stiffness and interaction energies among these thread-like objects can vary significantly depending on the chemical structure of the monomers used. We have used Monte Carlo simulations to study the structure of the threads and their ability to form networks through bundle formation. The persistence length of the threads was found to be strongly affected not only by stiffness, but also by the strength of attractive two-body interactions among thread segments. The relative values of stiffness and attractive two-body interaction strength determine if threads collapse or create bundles. Only in the presence of sufficiently long threads and bundle formation can these systems assemble into networks of high connectivity.

Markets on Networks

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

2003-03-01

The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

Reinforced communication and social navigation: Remember your friends and remember yourself

NASA Astrophysics Data System (ADS)

Mirshahvalad, A.; Rosvall, M.

2011-09-01

In social systems, people communicate with each other and form groups based on their interests. The pattern of interactions, the network, and the ideas that flow on the network naturally evolve together. Researchers use simple models to capture the feedback between changing network patterns and ideas on the network, but little is understood about the role of past events in the feedback process. Here, we introduce a simple agent-based model to study the coupling between peoples’ ideas and social networks, and better understand the role of history in dynamic social networks. We measure how information about ideas can be recovered from information about network structure and, the other way around, how information about network structure can be recovered from information about ideas. We find that it is, in general, easier to recover ideas from the network structure than vice versa.

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

[Motivation and Emotional States: Structural Systemic, Neurochemical, Molecular and Cellular Mechanisms].

PubMed

Bazyan, A S

2016-01-01

The structural, systemic, neurochemical, molecular and cellular mechanisms of organization and coding motivation and emotional states are describe. The GABA and glutamatergic synaptic systems of basal ganglia form a neural network and participate in the implementation of voluntary behavior. Neuropeptides, neurohormones and paracrine neuromodulators involved in the organization of motivation and emotional states, integrated with synaptic systems, controlled by neural networks and organizing goal-directed behavior. Structural centers for united and integrated of information in voluntary and goal-directed behavior are globus pallidus. Substantia nigra pars reticulata switches the information from corticobasal networks to thalamocortical networks, induces global dopaminergic (DA) signal and organize interaction of mesolimbic and nigostriatnoy DA systems controlled by prefrontal and motor cortex. Together with the motor cortex, substantia nigra displays information in the brainstem and spinal cord to implementation of behavior. Motivation states are formed in the interaction of neurohormonal and neuropeptide systems by monoaminergic systems of brain. Emotional states are formed by monoaminergic systems of the mid-brain, where the leading role belongs to the mesolimbic DA system. The emotional and motivation state of the encoded specific epigenetic molecular and chemical pattern of neuron.

Gender Differences in the Structure and Support Characteristics of Black Adolescents' Social Networks.

ERIC Educational Resources Information Center

Coates, Deborah L.

1987-01-01

Examination of 390 Black American adolescents demonstrates that males and females experience very different structured forms of social support. Females report more frequent contact with network members, who were both male and female, slightly older, and met in private settings. Males report larger groups of intimate friends, who are overwhelmingly…

Symbols, Relations, and Structural Complexity.

ERIC Educational Resources Information Center

Reich, Peter A.

This paper discusses an alternate formalism for context-free phrase structure grammar. The author feels that if a grammar is stated completely explicitly it can be represented in the form of a relational network of the type proposed by Lamb. He discusses some formal properties of such networks and makes some revisions to Lamb's formulation which…

Spatial networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

Dynamic social networks promote cooperation in experiments with humans

PubMed Central

Rand, David G.; Arbesman, Samuel; Christakis, Nicholas A.

2011-01-01

Human populations are both highly cooperative and highly organized. Human interactions are not random but rather are structured in social networks. Importantly, ties in these networks often are dynamic, changing in response to the behavior of one's social partners. This dynamic structure permits an important form of conditional action that has been explored theoretically but has received little empirical attention: People can respond to the cooperation and defection of those around them by making or breaking network links. Here, we present experimental evidence of the power of using strategic link formation and dissolution, and the network modification it entails, to stabilize cooperation in sizable groups. Our experiments explore large-scale cooperation, where subjects’ cooperative actions are equally beneficial to all those with whom they interact. Consistent with previous research, we find that cooperation decays over time when social networks are shuffled randomly every round or are fixed across all rounds. We also find that, when networks are dynamic but are updated only infrequently, cooperation again fails. However, when subjects can update their network connections frequently, we see a qualitatively different outcome: Cooperation is maintained at a high level through network rewiring. Subjects preferentially break links with defectors and form new links with cooperators, creating an incentive to cooperate and leading to substantial changes in network structure. Our experiments confirm the predictions of a set of evolutionary game theoretic models and demonstrate the important role that dynamic social networks can play in supporting large-scale human cooperation. PMID:22084103

Modification of β-Sheet Forming Peptide Hydrophobic Face: Effect on Self-Assembly and Gelation

PubMed Central

2016-01-01

β-Sheet forming peptides have attracted significant interest for the design of hydrogels for biomedical applications. One of the main challenges is the control and understanding of the correlations between peptide molecular structure, the morphology, and topology of the fiber and network formed as well as the macroscopic properties of the hydrogel obtained. In this work, we have investigated the effect that functionalizing these peptides through their hydrophobic face has on their self-assembly and gelation. Our results show that the modification of the hydrophobic face results in a partial loss of the extended β-sheet conformation of the peptide and a significant change in fiber morphology from straight to kinked. As a consequence, the ability of these fibers to associate along their length and form large bundles is reduced. These structural changes (fiber structure and network topology) significantly affect the mechanical properties of the hydrogels (shear modulus and elasticity). PMID:27089379

Complex quantum network geometries: Evolution and phase transitions

NASA Astrophysics Data System (ADS)

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.

Complex quantum network geometries: Evolution and phase transitions.

PubMed

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.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.

PubMed

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-08-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

PubMed Central

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-01-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. PMID:26291697

Email networks and the spread of computer viruses

NASA Astrophysics Data System (ADS)

Newman, M. E.; Forrest, Stephanie; Balthrop, Justin

2002-09-01

Many computer viruses spread via electronic mail, making use of computer users' email address books as a source for email addresses of new victims. These address books form a directed social network of connections between individuals over which the virus spreads. Here we investigate empirically the structure of this network using data drawn from a large computer installation, and discuss the implications of this structure for the understanding and prevention of computer virus epidemics.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-08-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure.

PubMed

Schleussner, Carl-Friedrich; Donges, Jonathan F; Engemann, Denis A; Levermann, Anders

2016-08-11

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

Origin of the cosmic network in ΛCDM: Nature vs nurture

NASA Astrophysics Data System (ADS)

Shandarin, Sergei; Habib, Salman; Heitmann, Katrin

2010-05-01

The large-scale structure of the Universe, as traced by the distribution of galaxies, is now being revealed by large-volume cosmological surveys. The structure is characterized by galaxies distributed along filaments, the filaments connecting in turn to form a percolating network. Our objective here is to quantitatively specify the underlying mechanisms that drive the formation of the cosmic network: By combining percolation-based analyses with N-body simulations of gravitational structure formation, we elucidate how the network has its origin in the properties of the initial density field (nature) and how its contrast is then amplified by the nonlinear mapping induced by the gravitational instability (nurture).

Assembly Kinetics Determine the Architecture of α-actinin Crosslinked F-actin Networks

PubMed Central

Falzone, Tobias T.; Lenz, Martin; Kovar, David R.; Gardel, Margaret L.

2013-01-01

The actin cytoskeleton is organized into diverse meshworks and bundles that support many aspects of cell physiology. Understanding the self-assembly of these actin-based structures is essential for developing predictive models of cytoskeletal organization. Here we show that the competing kinetics of bundle formation with the onset of dynamic arrest arising from filament entanglements and cross-linking determine the architecture of reconstituted actin networks formed with α-actinin cross-links. Cross-link mediated bundle formation only occurs in dilute solutions of highly mobile actin filaments. As actin polymerization proceeds, filament mobility and bundle formation are arrested concomitantly. By controlling the onset of dynamic arrest, perturbations to actin assembly kinetics dramatically alter the architecture of biochemically identical samples. Thus, the morphology of reconstituted F-actin networks is a kinetically determined structure similar to those formed by physical gels and glasses. These results establish mechanisms controlling the structure and mechanics in diverse semi-flexible biopolymer networks. PMID:22643888

The network and transmission of based on the principle of laser multipoint communication

NASA Astrophysics Data System (ADS)

Fu, Qiang; Liu, Xianzhu; Jiang, Huilin; Hu, Yuan; Jiang, Lun

2014-11-01

Space laser communication is the perfectly choose to the earth integrated information backbone network in the future. This paper introduces the structure of the earth integrated information network that is a large capacity integrated high-speed broadband information network, a variety of communications platforms were densely interconnected together, such as the land, sea, air and deep air users or aircraft, the technologies of the intelligent high-speed processing, switching and routing were adopt. According to the principle of maximum effective comprehensive utilization of information resources, get accurately information, fast processing and efficient transmission through inter-satellite, satellite earth, sky and ground station and other links. Namely it will be a space-based, air-based and ground-based integrated information network. It will be started from the trends of laser communication. The current situation of laser multi-point communications were expounded, the transmission scheme of the dynamic multi-point between wireless laser communication n network has been carefully studied, a variety of laser communication network transmission schemes the corresponding characteristics and scope described in detail , described the optical multiplexer machine that based on the multiport form of communication is applied to relay backbone link; the optical multiplexer-based on the form of the segmentation receiver field of view is applied to small angle link, the optical multiplexer-based form of three concentric spheres structure is applied to short distances, motorized occasions, and the multi-point stitching structure based on the rotation paraboloid is applied to inter-satellite communications in detail. The multi-point laser communication terminal apparatus consist of the transmitting and receiving antenna, a relay optical system, the spectroscopic system, communication system and communication receiver transmitter system. The communication forms of optical multiplexer more than four goals or more, the ratio of received power and volume weight will be Obvious advantages, and can track multiple moving targets in flexible.It would to provide reference for the construction of earth integrated information networks.

Ownership strategies of multinational corporations: Towards designing effective global networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raghunathan, S.P.

1992-01-01

The thesis of this research is that MNCs, attempting to implement different international strategies in response to several environmental factors, let their global networks evolve. The ownership structure of the network is therefore a function of the international strategy and environment of a firm. A particular strategy (configuration/coordination), given a certain environment, may be effective if associated with the appropriate structure. This study is based on a survey of 318 US manufacturing-sector MNCs using a questionnaire. The ownership structure of an MNC network was identified by studying the nature of ownership - method and form - of overseas subsidiaries. Usingmore » network theoretic methods, ownership structure was empirically related to international environment, strategy, and performance. Results of this study throw light on the design of global networks and enable a general theory of the design of MNCs to be eventually developed.« less

The network of concepts in written texts

NASA Astrophysics Data System (ADS)

Caldeira, S. M. G.; Petit Lobão, T. C.; Andrade, R. F. S.; Neme, A.; Miranda, J. G. V.

2006-02-01

Complex network theory is used to investigate the structure of meaningful concepts in written texts of individual authors. Networks have been constructed after a two phase filtering, where words with less meaning contents are eliminated and all remaining words are set to their canonical form, without any number, gender or time flexion. Each sentence in the text is added to the network as a clique. A large number of written texts have been scrutinised, and it is found that texts have small-world as well as scale-free structures. The growth process of these networks has also been investigated, and a universal evolution of network quantifiers have been found among the set of texts written by distinct authors. Further analyses, based on shuffling procedures taken either on the texts or on the constructed networks, provide hints on the role played by the word frequency and sentence length distributions to the network structure.

Evaluating Form and Function of Regional Partnerships: Applying Social Network Analysis to the "Network for a Healthy California", 2001-2007

ERIC Educational Resources Information Center

Gregson, Jennifer; Sowa, Marcy; Flynn, Heather Kohler

2011-01-01

Objective: To evaluate the partnership structure of the "Network for a Healthy California" ("Network"), a social marketing program, from 2001-2007, to determine if California's program was able to establish and maintain partnerships that (1) provided access to a local audience, (2) facilitated regional collaboration, (3)…

Effect of water on self-assembled tubules in β-sitosterol + γ-oryzanol-based organogels

NASA Astrophysics Data System (ADS)

den Adel, Ruud; Heussen, Patricia C. M.; Bot, Arjen

2010-10-01

Mixtures of β-sitosterol and γ-oryzanol form a network in triglyceride oil that may serve as an alternative to the network of small crystallites of triglycerides occurring in regular oil structuring. The present x-ray diffraction study investigates the relation between the crystal forms of the individual compounds and the mixture in oil, water and emulsion. β-Sitosterol and γ-oryzanol form normal crystals in oil, in water, or in emulsions. The crystals are sensitive to the presence of water. The mixture of β-sitosterol + γ-oryzanol forms crystals in water and emulsions that can be traced back to the crystals of the pure compounds. Only in oil, a completely different structure emerges in the mixture of β-sitosterol + γ-oryzanol, which bears no relation to the structures that are formed by both individual compounds, and which can be identified as a self-assembled tubule (diameter 7.2±0.1 nm, wall thickness 0.8±0.2 nm).

Correlations between Community Structure and Link Formation in Complex Networks

PubMed Central

Liu, Zhen; He, Jia-Lin; Kapoor, Komal; Srivastava, Jaideep

2013-01-01

Background Links in complex networks commonly represent specific ties between pairs of nodes, such as protein-protein interactions in biological networks or friendships in social networks. However, understanding the mechanism of link formation in complex networks is a long standing challenge for network analysis and data mining. Methodology/Principal Findings Links in complex networks have a tendency to cluster locally and form so-called communities. This widely existed phenomenon reflects some underlying mechanism of link formation. To study the correlations between community structure and link formation, we present a general computational framework including a theory for network partitioning and link probability estimation. Our approach enables us to accurately identify missing links in partially observed networks in an efficient way. The links having high connection likelihoods in the communities reveal that links are formed preferentially to create cliques and accordingly promote the clustering level of the communities. The experimental results verify that such a mechanism can be well captured by our approach. Conclusions/Significance Our findings provide a new insight into understanding how links are created in the communities. The computational framework opens a wide range of possibilities to develop new approaches and applications, such as community detection and missing link prediction. PMID:24039818

Interplay between structure and transport properties of molten salt mixtures of ZnCl2-NaCl-KCl: A molecular dynamics study.

PubMed

Manga, Venkateswara Rao; Swinteck, Nichlas; Bringuier, Stefan; Lucas, Pierre; Deymier, Pierre; Muralidharan, Krishna

2016-03-07

Molten mixtures of network-forming covalently bonded ZnCl2 and network-modifying ionically bonded NaCl and KCl salts are investigated as high-temperature heat transfer fluids for concentrating solar power plants. Specifically, using molecular dynamics simulations, the interplay between the extent of the network structure, composition, and the transport properties (viscosity, thermal conductivity, and diffusion) of ZnCl2-NaCl-KCl molten salts is characterized. The Stokes-Einstein/Eyring relationship is found to break down in these network-forming liquids at high concentrations of ZnCl2 (>63 mol. %), while the Eyring relationship is seen with increasing KCl concentration. Further, the network modification due to the addition of K ions leads to formation of non-bridging terminal Cl ions, which in turn lead to a positive temperature dependence of thermal conductivity in these melts. This new understanding of transport in these ternary liquids enables the identification of appropriate concentrations of the network formers and network modifiers to design heat transfer fluids with desired transport properties for concentrating solar power plants.

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

PubMed

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.

Structural analysis of Precambrian rocks at the Hot Dry Rock Site at Fenton Hill, New Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burns, K.L.; Potter, R.M.

1995-01-01

The subcrop of basement rock at Fenton HIll comprises Precambrian gneiss, schist, amphibolite, pegmatite, and granitoids with affinities in metamorphic and structural history to surface outcrops in the Tusas and Picuris Ranges. Televiewer measurements of structures were analyzed by taking advantage of the spatial continuity of foliations. Folds in the foliation are predominantly conical forms due to interference between structures formed in F2 and F3 tectonic events. Field observations of outcrops in the Picuris Range show that the fractures are predominantly an X-T network controlled by the lithological layering, and statistical evidence indicates that this layer-controlled network persists to depthmore » at Fenton Hill.« less

Electron tomography reveals the fibril structure and lipid interactions in amyloid deposits

PubMed Central

Kollmer, Marius; Meinhardt, Katrin; Haupt, Christian; Liberta, Falk; Wulff, Melanie; Linder, Julia; Handl, Lisa; Heinrich, Liesa; Loos, Cornelia; Schmidt, Matthias; Syrovets, Tatiana; Simmet, Thomas; Westermark, Per; Westermark, Gunilla T.; Horn, Uwe; Schmidt, Volker; Walther, Paul; Fändrich, Marcus

2016-01-01

Electron tomography is an increasingly powerful method to study the detailed architecture of macromolecular complexes or cellular structures. Applied to amyloid deposits formed in a cell culture model of systemic amyloid A amyloidosis, we could determine the structural morphology of the fibrils directly in the deposit. The deposited fibrils are arranged in different networks, and depending on the relative fibril orientation, we can distinguish between fibril meshworks, fibril bundles, and amyloid stars. These networks are frequently infiltrated by vesicular lipid inclusions that may originate from the death of the amyloid-forming cells. Our data support the role of nonfibril components for constructing fibril deposits and provide structural views of different types of lipid–fibril interactions. PMID:27140609

Unusual Features of Crystal Structures of Some Simple Copper Compounds

ERIC Educational Resources Information Center

Douglas, Bodie

2009-01-01

Some simple copper compounds have unusual crystal structures. Cu[subscript 3]N is cubic with N atoms at centers of octahedra formed by 6 Cu atoms. Cu[subscript 2]O (cuprite) is also cubic; O atoms are in tetrahedra formed by 4 Cu atoms. These tetrahedra are linked by sharing vertices forming two independent networks without linkages between them.…

Translational networks in healthcare? Evidence on the design and initiation of organizational networks for knowledge mobilization.

PubMed

Fitzgerald, Louise; Harvey, Gill

2015-08-01

International attention has focussed on the variations between research evidence and practice in healthcare. This prompted the creation of formalized translational networks consisting of academic-service partnerships. The English Collaborations for Leadership in Applied Health Research and Care (CLAHRCs) are one example of a translational network. Using longitudinal, archival case study data from one CLAHRC over a 3-year period (2008-11), this article explores the relationship between organizational form and the function(s) of a translational network. The article focuses on the research gaps on the effective structures and appropriate governance to support a translational network. Data analysis suggested that the policy of setting up translational networks is insufficient of itself to produce positive translational activity. The data indicate that to leverage the benefits of the whole network, attention must be paid to devising a structure which integrates research production and use and facilitates lateral cross-disciplinary and cross-organizational communication. Equally, appropriate governance arrangements are necessary, particularly in large, multi-stakeholder networks, where shared governance may be questionable. Inappropriate network structure and governance inhibits the potential of the translational network. Finally, the case provides insights into the movement of knowledge within and between network organizations. The data demonstrate that knowledge mobilization extends beyond knowledge translation; knowledge mobilization includes the negotiated utilization of knowledge - a balanced power form of collaboration. Whilst much translational effort is externally focused on the health system, our findings highlight the essential need for the internal negotiation and mobilization of knowledge within academia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Research of future network with multi-layer IP address

NASA Astrophysics Data System (ADS)

Li, Guoling; Long, Zhaohua; Wei, Ziqiang

2018-04-01

The shortage of IP addresses and the scalability of routing systems [1] are challenges for the Internet. The idea of dividing existing IP addresses between identities and locations is one of the important research directions. This paper proposed a new decimal network architecture based on IPv9 [11], and decimal network IP address from E.164 principle of traditional telecommunication network, the IP address level, which helps to achieve separation and identification and location of IP address, IP address form a multilayer network structure, routing scalability problem in remission at the same time, to solve the problem of IPv4 address depletion. On the basis of IPv9, a new decimal network architecture is proposed, and the IP address of the decimal network draws on the E.164 principle of the traditional telecommunication network, and the IP addresses are hierarchically divided, which helps to realize the identification and location separation of IP addresses, the formation of multi-layer IP address network structure, while easing the scalability of the routing system to find a way out of IPv4 address exhausted. In addition to modifying DNS [10] simply and adding the function of digital domain, a DDNS [12] is formed. At the same time, a gateway device is added, that is, IPV9 gateway. The original backbone network and user network are unchanged.

Social network analysis of character interaction in the Stargate and Star Trek television series

NASA Astrophysics Data System (ADS)

Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

Viscoelastic and Functional Properties of Cod-Bone Gelatin in the Presence of Xylitol and Stevioside

NASA Astrophysics Data System (ADS)

Nian, Linyu; Cao, Ailing; Wang, Jing; Tian, Hongyu; Liu, Yongguo; Gong, Lingxiao; Cai, Luyun; Wang, Yuhao

2018-05-01

The physical, rheological, structural and functional properties of cod bone gelatin (CBG) with various concentrations (0, 2, 4, 6, 10 and 15%) of low-calorie sweeteners (xylitol (X) and stevioside (S)) to form gels were investigated. The gel strength of CBGX increased with increased xylitol due presumably to hydrogen bonds between xylitol and gelatin, but with CBGS the highest gel strength occurred when S concentration was 4%. Viscosity of CBGS samples were higher than CBGX due to S’s high molecular mass. The viscoelasticity (G' and G″), foaming capacity and fat binding capacity of CBGX were higher while foam stability was lower. The emulsion activity and emulsion stability of CBGX were a little lower than CBGS at the same concentration. The structure of X is linear making it easier to form a dense three-dimensional network structure, while the complex cyclic structure of S had more difficulty forming a network structure with cod bone gelatin. Therefore, X may be a better choice for sweetening gelatin gels.

Viscoelastic and Functional Properties of Cod-Bone Gelatin in the Presence of Xylitol and Stevioside.

PubMed

Nian, Linyu; Cao, Ailing; Wang, Jing; Tian, Hongyu; Liu, Yongguo; Gong, Lingxiao; Cai, Luyun; Wang, Yuhao

2018-01-01

The physical, rheological, structural and functional properties of cod bone gelatin (CBG) with various concentrations (0, 2, 4, 6, 10, and 15%) of low-calorie sweeteners [xylitol (X) and stevioside (S)] to form gels were investigated. The gel strength of CBGX increased with increased xylitol due presumably to hydrogen bonds between xylitol and gelatin, but with CBGS the highest gel strength occurred when S concentration was 4%. Viscosity of CBGS samples were higher than CBGX due to S's high molecular mass. The viscoelasticity (G' and G''), foaming capacity and fat binding capacity of CBGX were higher while foam stability was lower. The emulsion activity and emulsion stability of CBGX were a little lower than CBGS at the same concentration. The structure of X is linear making it easier to form a dense three-dimensional network structure, while the complex cyclic structure of S had more difficulty forming a network structure with cod bone gelatin. Therefore, X may be a better choice for sweetening gelatin gels.

Managing Network Partitions in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Shafaat, Tallat M.; Ghodsi, Ali; Haridi, Seif

Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale distributed system is destined to face network partitions. Consequently, the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems. This makes it a crucial requirement for building any structured peer-to-peer systems to be resilient to network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. Structured overlays have mainly been studied under churn (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this chapter, we motivate the problem of network partitions and mergers in structured overlays. We discuss how a structured overlay can automatically detect a network partition and merger. We present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger, something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger, the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.

Biomimetic oral mucin from polymer micelle networks

NASA Astrophysics Data System (ADS)

Authimoolam, Sundar Prasanth

Mucin networks are formed by the complexation of bottlebrush-like mucin glycoprotein with other small molecule glycoproteins. These glycoproteins create nanoscale strands that then arrange into a nanoporous mesh. These networks play an important role in ensuring surface hydration, lubricity and barrier protection. In order to understand the functional behavior in mucin networks, it is important to decouple their chemical and physical effects responsible for generating the fundamental property-function relationship. To achieve this goal, we propose to develop a synthetic biomimetic mucin using a layer-by-layer (LBL) deposition approach. In this work, a hierarchical 3-dimensional structures resembling natural mucin networks was generated using affinity-based interactions on synthetic and biological surfaces. Unlike conventional polyelectrolyte-based LBL methods, pre-assembled biotin-functionalized filamentous (worm-like) micelles was utilized as the network building block, which from complementary additions of streptavidin generated synthetic networks of desired thickness. The biomimetic nature in those synthetic networks are studied by evaluating its structural and bio-functional properties. Structurally, synthetic networks formed a nanoporous mesh. The networks demonstrated excellent surface hydration property and were able capable of microbial capture. Those functional properties are akin to that of natural mucin networks. Further, the role of synthetic mucin as a drug delivery vehicle, capable of providing localized and tunable release was demonstrated. By incorporating antibacterial curcumin drug loading within synthetic networks, bacterial growth inhibition was also demonstrated. Thus, such bioactive interfaces can serve as a model for independently characterizing mucin network properties and through its role as a drug carrier vehicle it presents exciting future opportunities for localized drug delivery, in regenerative applications and as bio-functional implant coats. KEYWORDS: Biomimic, Bioapplication, Drug delivery, Filomicelle, Mucin, Polymer networks.

Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics

PubMed Central

Henry, Teague; Gesell, Sabina B.; Ip, Edward H.

2016-01-01

Background Social networks influence children and adolescents’ physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Network interventions to increase physical activity are warranted but have not been conducted. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross sectional network structure, and activity level and change in network structure are assessed. Methods We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We used the exponential random graph model (ERGMs) and its longitudinal extension to evaluate the association between activity level and various demographic factors in having, forming, and dissolving friendship. Due to heterogeneity between the friendship networks within the aftercare programs, separate analyses were conducted for each network. Results There was heterogeneity in the effect of physical activity on both cross sectional network structure and the formation and dissolution processes, both across time and between networks. Conclusions Network analysis could be used to assess the unique structure and dynamics of a social network before an intervention is implemented, so as to optimize the effects of the network intervention for increasing childhood physical activity. Additionally, if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves. PMID:27867518

An evolutionary game approach for determination of the structural conflicts in signed networks

PubMed Central

Tan, Shaolin; Lü, Jinhu

2016-01-01

Social or biochemical networks can often divide into two opposite alliances in response to structural conflicts between positive (friendly, activating) and negative (hostile, inhibiting) interactions. Yet, the underlying dynamics on how the opposite alliances are spontaneously formed to minimize the structural conflicts is still unclear. Here, we demonstrate that evolutionary game dynamics provides a felicitous possible tool to characterize the evolution and formation of alliances in signed networks. Indeed, an evolutionary game dynamics on signed networks is proposed such that each node can adaptively adjust its choice of alliances to maximize its own fitness, which yet leads to a minimization of the structural conflicts in the entire network. Numerical experiments show that the evolutionary game approach is universally efficient in quality and speed to find optimal solutions for all undirected or directed, unweighted or weighted signed networks. Moreover, the evolutionary game approach is inherently distributed. These characteristics thus suggest the evolutionary game dynamic approach as a feasible and effective tool for determining the structural conflicts in large-scale on-line signed networks. PMID:26915581

Origin of the cosmic network in {Lambda}CDM: Nature vs nurture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shandarin, Sergei; Habib, Salman; Heitmann, Katrin

The large-scale structure of the Universe, as traced by the distribution of galaxies, is now being revealed by large-volume cosmological surveys. The structure is characterized by galaxies distributed along filaments, the filaments connecting in turn to form a percolating network. Our objective here is to quantitatively specify the underlying mechanisms that drive the formation of the cosmic network: By combining percolation-based analyses with N-body simulations of gravitational structure formation, we elucidate how the network has its origin in the properties of the initial density field (nature) and how its contrast is then amplified by the nonlinear mapping induced by themore » gravitational instability (nurture).« less

An Asymmetrical Network Model of the Japanese EFL Learner's Mental Lexicon

ERIC Educational Resources Information Center

Aotani, Noriko; Sugino, Naoki; Fraser, Simon; Koga, Yuya; Shojima, Kojiro

2016-01-01

The aim of this study is to construct a model of a simple lexical network showing the strength and asymmetry of the connections between vocabulary items in the L2 mental lexicon of Japanese learners. The study focuses on eight nouns and investigates how they are networked, and whether the existing network structure formed by these nouns would be…

Toughening of Thermoresponsive Arrested Networks of Elastin-Like Polypeptides To Engineer Cytocompatible Tissue Scaffolds.

PubMed

Glassman, Matthew J; Avery, Reginald K; Khademhosseini, Ali; Olsen, Bradley D

2016-02-08

Formulation of tissue engineering or regenerative scaffolds from simple bioactive polymers with tunable structure and mechanics is crucial for the regeneration of complex tissues, and hydrogels from recombinant proteins, such as elastin-like polypeptides (ELPs), are promising platforms to support these applications. The arrested phase separation of ELPs has been shown to yield remarkably stiff, biocontinuous, nanostructured networks, but these gels are limited in applications by their relatively brittle nature. Here, a gel-forming ELP is chain-extended by telechelic oxidative coupling, forming extensible, tough hydrogels. Small angle scattering indicates that the chain-extended polypeptides form a fractal network of nanoscale aggregates over a broad concentration range, accessing moduli ranging from 5 kPa to over 1 MPa over a concentration range of 5-30 wt %. These networks exhibited excellent erosion resistance and allowed for the diffusion and release of encapsulated particles consistent with a bicontinuous, porous structure with a broad distribution of pore sizes. Biofunctionalized, toughened networks were found to maintain the viability of human mesenchymal stem cells (hMSCs) in 2D, demonstrating signs of osteogenesis even in cell media without osteogenic molecules. Furthermore, chondrocytes could be readily mixed into these gels via thermoresponsive assembly and remained viable in extended culture. These studies demonstrate the ability to engineer ELP-based arrested physical networks on the molecular level to form reinforced, cytocompatible hydrogel matrices, supporting the promise of these new materials as candidates for the engineering and regeneration of stiff tissues.

Structure Shift of GaN Among Nanowall Network, Nanocolumn, and Compact Film Grown on Si (111) by MBE.

PubMed

Zhong, Aihua; Fan, Ping; Zhong, Yuanting; Zhang, Dongping; Li, Fu; Luo, Jingting; Xie, Yizhu; Hane, Kazuhiro

2018-02-13

Structure shift of GaN nanowall network, nanocolumn, and compact film were successfully obtained on Si (111) by plasma-assisted molecular beam epitaxy (MBE). As is expected, growth of the GaN nanocolumns was observed in N-rich condition on bare Si, and the growth shifted to compact film when the Ga flux was improved. Interestingly, if an aluminum (Al) pre-deposition for 40 s was carried out prior to the GaN growth, GaN grows in the form of the nanowall network. Results show that the pre-deposited Al exits in the form of droplets with typical diameter and height of ~ 80 and ~ 6.7 nm, respectively. A growth model for the nanowall network is proposed and the growth mechanism is discussed. GaN grows in the area without Al droplets while the growth above Al droplets is hindered, resulting in the formation of continuous GaN nanowall network that removes the obstacles of nano-device fabrication.

Structure Shift of GaN Among Nanowall Network, Nanocolumn, and Compact Film Grown on Si (111) by MBE

NASA Astrophysics Data System (ADS)

Zhong, Aihua; Fan, Ping; Zhong, Yuanting; Zhang, Dongping; Li, Fu; Luo, Jingting; Xie, Yizhu; Hane, Kazuhiro

2018-02-01

Structure shift of GaN nanowall network, nanocolumn, and compact film were successfully obtained on Si (111) by plasma-assisted molecular beam epitaxy (MBE). As is expected, growth of the GaN nanocolumns was observed in N-rich condition on bare Si, and the growth shifted to compact film when the Ga flux was improved. Interestingly, if an aluminum (Al) pre-deposition for 40 s was carried out prior to the GaN growth, GaN grows in the form of the nanowall network. Results show that the pre-deposited Al exits in the form of droplets with typical diameter and height of 80 and 6.7 nm, respectively. A growth model for the nanowall network is proposed and the growth mechanism is discussed. GaN grows in the area without Al droplets while the growth above Al droplets is hindered, resulting in the formation of continuous GaN nanowall network that removes the obstacles of nano-device fabrication.

Structure and function of complex brain networks

PubMed Central

Sporns, Olaf

2013-01-01

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed. PMID:24174898

A structural study of F-actin - filamin networks

NASA Astrophysics Data System (ADS)

Ahrens-Braunstein, Ashley; Nguyen, Lam; Hirst, Linda

2010-03-01

The cell's ability to move and contract is attributed to the semi-flexible filamentous protein, F -actin, one of the three filaments in the cytoskeleton. Actin bundling can be formed by a cross-linking actin binding protein (ABP) filamin. By examining filamin's cross-linking abilities at different concentrations and molar ratios, we can study the flexibility, structure and multiple network formations created when cross-linking F-actin with this protein. We have studied the phase diagram of this protein system using fluorescence microscopy, analyzing the network structures observed in the context of a coarse grained molecular dynamics simulation carried out by our group.

Ion aggregation in high salt solutions. VII. The effect of cations on the structures of ion aggregates and water hydrogen-bonding network

NASA Astrophysics Data System (ADS)

Choi, Jun-Ho; Choi, Hyung Ran; Jeon, Jonggu; Cho, Minhaeng

2017-10-01

Ions in high salt solutions have a strong propensity to form polydisperse ion aggregates with broad size and shape distributions. In a series of previous comparative investigations using femtosecond IR pump-probe spectroscopy, molecular dynamics simulation, and graph theoretical analysis, we have shown that there exists a morphological difference in the structures of ion aggregates formed in various salt solutions. As salt concentration increases, the ions in high salt solutions form either cluster-like structures excluding water molecules or network-like structures entwined with water hydrogen-bonding networks. Interestingly, such morphological characteristics of the ion aggregates have been found to be in correlation with the solubility limits of salts. An important question that still remains unexplored is why certain salts with different cations have notably different solubility limits in water. Here, carrying out a series of molecular dynamics simulations of aqueous salt solutions and analyzing the distributions and connectivity patterns of ion aggregates with a spectral graph analysis method, we establish the relationship between the salt solubility and the ion aggregate morphology with a special emphasis on the cationic effects on water structures and ion aggregation. We anticipate that the understanding of large scale ion aggregate structures revealed in this study will be critical for elucidating the specific ion effects on the solubility and conformational stability of co-solute molecules such as proteins in water.

An Open, Snow-based Hydrologic System on Noachian Mars

NASA Technical Reports Server (NTRS)

Zent, A. P.

1999-01-01

Properties of Noachian valley networks on Mars suggest that the conditions under which they formed were marginal for liquid water formation. The networks are sparsely scattered, poorly dissected, and tend to be small; a majority occupy areas only a few hundred kilometers in extent. Models in which networks formed by mass wasting are contra-indicated by the discovery of channels within the valleys. Greenhouse hypotheses for the stability of liquid water have foundered on familiar problems: first, a very substantial CO2 atmosphere would be required to bring global average conditions to 273 K; the CO2 should still be present in extensive carbonate deposits that have not been detected. Explanations that call upon groundwater sapping are hampered by the need for a hydrologic system to recharge the groundwater system, which effectively reinstates the need for a heavy CO2 atmosphere. Based upon field experience and geomorphic similarities between drainage developed in the periglacial terrain in and around the Haughton impact structure, Devon Island, Nuunavuut, Canada, we have suggested that some of the channel networks may have formed either subglacially, or as ice marginal structures.

Fracture Simulation of Highly Crosslinked Polymer Networks: Triglyceride-Based Adhesives

NASA Astrophysics Data System (ADS)

Lorenz, Christian; Stevens, Mark; Wool, Richard

2003-03-01

The ACRES program at the U. of Delaware has shown that triglyceride oils derived from plants are a favorable alternative to the traditional adhesives. The triglyceride networks are formed from an initial mixture of styrene monomers, free-radical initiators and triglycerides. We have performed simulations to study the effect of physical composition and physical characteristics of the triglyceride network on the strength of triglyceride network. A coarse-grained, bead-spring model of the triglyceride system is used. The average triglyceride consists of 6 beads per chain, the styrenes are represented as a single bead and the initiators are two bead chains. The polymer network is formed using an off-lattice 3D Monte Carlo simulation, in which the initiators activate the styrene and triglyceride reactive sites and then bonds are randomly formed between the styrene and active triglyceride monomers producing a highly crosslinked polymer network. Molecular dynamics simulations of the network under tensile and shear strains were performed to determine the strength as a function of the network composition. The relationship between the network structure and its strength will also be discussed.

Polymer-based platform for microfluidic systems

DOEpatents

Benett, William [Livermore, CA; Krulevitch, Peter [Pleasanton, CA; Maghribi, Mariam [Livermore, CA; Hamilton, Julie [Tracy, CA; Rose, Klint [Boston, MA; Wang, Amy W [Oakland, CA

2009-10-13

A method of forming a polymer-based microfluidic system platform using network building blocks selected from a set of interconnectable network building blocks, such as wire, pins, blocks, and interconnects. The selected building blocks are interconnectably assembled and fixedly positioned in precise positions in a mold cavity of a mold frame to construct a three-dimensional model construction of a microfluidic flow path network preferably having meso-scale dimensions. A hardenable liquid, such as poly (dimethylsiloxane) is then introduced into the mold cavity and hardened to form a platform structure as well as to mold the microfluidic flow path network having channels, reservoirs and ports. Pre-fabricated elbows, T's and other joints are used to interconnect various building block elements together. After hardening the liquid the building blocks are removed from the platform structure to make available the channels, cavities and ports within the platform structure. Microdevices may be embedded within the cast polymer-based platform, or bonded to the platform structure subsequent to molding, to create an integrated microfluidic system. In this manner, the new microfluidic platform is versatile and capable of quickly generating prototype systems, and could easily be adapted to a manufacturing setting.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

PubMed Central

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-01-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking. PMID:27510641

How Social Network Position Relates to Knowledge Building in Online Learning Communities

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

Social Network Analysis, Statistical Analysis, Content Analysis and other research methods were used to research online learning communities at Capital Normal University, Beijing. Analysis of the two online courses resulted in the following conclusions: (1) Social networks of the two online courses form typical core-periphery structures; (2)…

Community Structure of a Bank-Firm Credit Network in Japan

NASA Astrophysics Data System (ADS)

Iyetomi, Hiroshi; Matsuura, Yuki

2014-03-01

We study temporal change of community structure in a Japanese credit network formed by banks and listed firms through their financial relations over the last 30 years. The credit connectedness is regarded as a potenital source of systemic risk. Our network is a bipartite graph consisting of two species of nodes connected with bidirectional links. The direction of links is identified with that of risk flows and their weights are relative credit/loan with respect to the targets. In a partial credit network obtained only with the links pointing from firms toward banks, the city banks forms one major community in most of the time period to share risk when firms go wrong. On the other hand, a partial network only with the links from banks toward firms is decomposed into communities of similar size each of which has its own city bank, reflecting the main-bank system in Japan. Finally we take overlapping parts of the two community sets to find cores of the risk concentration in the credit network. This work was supported by JSPS KAKENHI Grant Number 22300080.

Unifying Inference of Meso-Scale Structures in Networks.

PubMed

Tunç, Birkan; Verma, Ragini

2015-01-01

Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities) of the brain, as well as its auxiliary characteristics (core-periphery).

Hierarchical organization of brain functional networks during visual tasks.

PubMed

Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

2011-09-01

The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

Dynamical networks with topological self-organization

NASA Technical Reports Server (NTRS)

Zak, M.

2001-01-01

Coupled evolution of state and topology of dynamical networks is introduced. Due to the well organized tensor structure, the governing equations are presented in a canonical form, and required attractors as well as their basins can be easily implanted and controlled.

The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

PubMed

Djurfeldt, Mikael

2012-07-01

The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

Holography as deep learning

NASA Astrophysics Data System (ADS)

Gan, Wen-Cong; Shu, Fu-Wen

Quantum many-body problem with exponentially large degrees of freedom can be reduced to a tractable computational form by neural network method [G. Carleo and M. Troyer, Science 355 (2017) 602, arXiv:1606.02318.] The power of deep neural network (DNN) based on deep learning is clarified by mapping it to renormalization group (RG), which may shed lights on holographic principle by identifying a sequence of RG transformations to the AdS geometry. In this paper, we show that any network which reflects RG process has intrinsic hyperbolic geometry, and discuss the structure of entanglement encoded in the graph of DNN. We find the entanglement structure of DNN is of Ryu-Takayanagi form. Based on these facts, we argue that the emergence of holographic gravitational theory is related to deep learning process of the quantum-field theory.

Tribromobenzene on Cu(111): Temperature-dependent formation of halogen-bonded, organometallic, and covalent nanostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Qitang; Wang, Tao; Zhu, Junfa, E-mail: jfzhu@ustc.edu.cn

2015-03-14

The temperature-controlled surface-assisted synthesis of halogen bonded, organometallic, and covalent nanostructures based on 1,3,5-tribromo-benzene (TriBB) was studied with scanning tunneling microscopy and X-ray photoemission spectroscopy in ultrahigh vacuum. Vapor deposition of TriBB onto a Cu(111) surface held at 90 K leads to the formation of large domains of a honeycomb-like organic monolayer structure stabilized by triangular nodes with Br⋯Br intermolecular bonds. Upon annealing the organic monolayer to ∼140 K, a new hexagonal close-packed structure with intact TriBB molecules connected by Cu adatoms is formed. Further warming up the sample to 300 K gives rise to the scission of C–Br bondsmore » and formation of C–Cu–C bonds between phenyl fragments such that stable dendritic organometallic networks are formed. Larger islands of organometallic networks are obtained by maintaining the temperature of Cu(111) at 420 K during deposition of TriBB. Simultaneously, large islands of Br atoms are formed around the organometallic networks. Annealing the more extended organometallic network (prepared at 420 K) to 520 K leads to the formation of a branched covalent organic framework (COF) which comprises structural elements of porous graphene and is surrounded by Br islands. These organometallic networks and COFs appear as small dendritic and branched domains, most likely due to the steric influence exerted by the Br islands.« less

The Magnetic Structure of H-Alpha Macrospicules in Solar Coronal Holes

NASA Technical Reports Server (NTRS)

Yamauchi, Y.; Moore, R. L.; Suess, S. T.; Wang, H.; Sakuri, T.

2003-01-01

Measurements by Ulysses in the high-speed polar solar wind have shown the wind to carry some fine-scale structures in which the magnetic field reverses direction by having a switchback fold in it. The lateral span of these magnetic switchbacks, translated to the Sun, is of the scale of the lanes and cells of the magnetic network in which the open magnetic flux of the polar coronal hole and polar solar wind are rooted. This suggests that the magnetic switchbacks might be formed from network-scale magnetic loops that erupt into the corona and then undergo reconnection with the open field. This possibility motivated us to undertake the study reported here of the structure of H-alpha macrospicules observed at the limb in polar coronal holes, to determine whether a significant fraction of these eruptions appear to be erupting loops. From a search of the polar-coronal holes in 6 days of image-processed full-disk H-alpha movies from Big Bear Solar Observatory, we found a total of 35 macrospicules. Nearly all of these (32) were of one or the other of two different forms: 15 were in the form of an erupting loop, and 17 were in the form of a single-column spiked jet. The erupting-loop macrospicules are appropriate for producing the magnetic switchbacks in the polar wind. The spiked-jet macrospicules show the appropriate structure and evolution to be driven by reconnection between network-scale closed field (a network bipole) and the open field rooted against the closed field. This evidence for reconnection in a large fraction of our macrospicules (1) suggests that many spicules may be generated by similar but smaller reconnection events, and (2) supports the view that coronal heating and solar wind acceleration in coronal holes and in quiet regions and corona are driven by explosive reconnection events in the magnetic network.

The Magnetic Structure of H-alpha Macrospicules in Solar Coronal Holes

NASA Technical Reports Server (NTRS)

Yamauchi, Y.; Moore, R. L.; Suess, S. T.; Wang, H.; Sakurai, T.

2004-01-01

Measurements by Ulysses in the high-speed polar solar wind have shown the wind to carry some fine-scale structures in which the magnetic field reverses direction by having a switchback fold in it. The lateral span of these magnetic switchbacks, translated back to the Sun, is of the scale of the lanes and cells of the magnetic network in which the open magnetic field of the polar coronal hole and polar solar wind are rooted. This suggests that the magnetic switchbacks might be formed from network-scale magnetic loops that erupt into the corona and then undergo reconnection with the open field. This possibility motivated us to undertake the study reported here of the structure of Ha macrospicules observed at the limb in polar coronal holes, to determine whether a significant fraction of these eruptions appear to be erupting loops. From a search of the polar coronal holes in 6 days of image- processed full-disk Ha movies from Big Bear Solar Observatory, we found a total of 35 macrospicules. Nearly all of these (32) were of one or the other of two different forms: 15 were in the form of an erupting loop, and 17 were in the form of a single column spiked jet. The erupting-loop macrospicules are appropriate for producing the magnetic switchbacks in the polar wind. The spiked-jet macrospicules show the appropriate structure and evolution to be driven by reconnection between network-scale closed field (a network bipole) and the open field rooted against the closed field. This evidence for reconnection in a large fraction of our macrospicules (1) suggests that many spicules may be generated by similar but smaller reconnection events and (2) supports the view that coronal heating and solar wind acceleration in coronal holes and in quiet regions are driven by explosive reconnection events in the magnetic network.

Classification of epilepsy types through global network analysis of scalp electroencephalograms

NASA Astrophysics Data System (ADS)

Lee, Uncheol; Kim, Seunghwan; Jung, Ki-Young

2006-04-01

Epilepsy is a dynamic disease in which self-organization and emergent structures occur dynamically at multiple levels of neuronal integration. Therefore, the transient relationship within multichannel electroencephalograms (EEGs) is crucial for understanding epileptic processes. In this paper, we show that the global relationship within multichannel EEGs provides us with more useful information in classifying two different epilepsy types than pairwise relationships such as cross correlation. To demonstrate this, we determine the global network structure within channels of the scalp EEG based on the minimum spanning tree method. The topological dissimilarity of the network structures from different types of temporal lobe epilepsy is described in the form of the divergence rate and is computed for 11 patients with left (LTLE) and right temporal lobe epilepsy (RTLE). We find that patients with LTLE and RTLE exhibit different large scale network structures, which emerge at the epoch immediately before the seizure onset, not in the preceding epochs. Our results suggest that patients with the two different epilepsy types display distinct large scale dynamical networks with characteristic epileptic network structures.

Protein enriched pasta: structure and digestibility of its protein network.

PubMed

Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

2016-02-01

Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

Integrated Circuit For Simulation Of Neural Network

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

1988-01-01

Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

Morphology and linear-elastic moduli of random network solids.

PubMed

Nachtrab, Susan; Kapfer, Sebastian C; Arns, Christoph H; Madadi, Mahyar; Mecke, Klaus; Schröder-Turk, Gerd E

2011-06-17

The effective linear-elastic moduli of disordered network solids are analyzed by voxel-based finite element calculations. We analyze network solids given by Poisson-Voronoi processes and by the structure of collagen fiber networks imaged by confocal microscopy. The solid volume fraction ϕ is varied by adjusting the fiber radius, while keeping the structural mesh or pore size of the underlying network fixed. For intermediate ϕ, the bulk and shear modulus are approximated by empirical power-laws K(phi)proptophin and G(phi)proptophim with n≈1.4 and m≈1.7. The exponents for the collagen and the Poisson-Voronoi network solids are similar, and are close to the values n=1.22 and m=2.11 found in a previous voxel-based finite element study of Poisson-Voronoi systems with different boundary conditions. However, the exponents of these empirical power-laws are at odds with the analytic values of n=1 and m=2, valid for low-density cellular structures in the limit of thin beams. We propose a functional form for K(ϕ) that models the cross-over from a power-law at low densities to a porous solid at high densities; a fit of the data to this functional form yields the asymptotic exponent n≈1.00, as expected. Further, both the intensity of the Poisson-Voronoi process and the collagen concentration in the samples, both of which alter the typical pore or mesh size, affect the effective moduli only by the resulting change of the solid volume fraction. These findings suggest that a network solid with the structure of the collagen networks can be modeled in quantitative agreement by a Poisson-Voronoi process. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Implications of network structure on public health collaboratives.

PubMed

Retrum, Jessica H; Chapman, Carrie L; Varda, Danielle M

2013-10-01

Interorganizational collaboration is an essential function of public health agencies. These partnerships form social networks that involve diverse types of partners and varying levels of interaction. Such collaborations are widely accepted and encouraged, yet very little comparative research exists on how public health partnerships develop and evolve, specifically in terms of how subsequent network structures are linked to outcomes. A systems science approach, that is, one that considers the interdependencies and nested features of networks, provides the appropriate methods to examine the complex nature of these networks. Applying Mays and Scutchfields's categorization of "structural signatures" (breadth, density, and centralization), this research examines how network structure influences the outcomes of public health collaboratives. Secondary data from the Program to Analyze, Record, and Track Networks to Enhance Relationships (www.partnertool.net) data set are analyzed. This data set consists of dyadic (N = 12,355), organizational (N = 2,486), and whole network (N = 99) data from public health collaborations around the United States. Network data are used to calculate structural signatures and weighted least squares regression is used to examine how network structures can predict selected intermediary outcomes (resource contributions, overall value and trust rankings, and outcomes) in public health collaboratives. Our findings suggest that network structure may have an influence on collaborative-related outcomes. The structural signature that had the most significant relationship to outcomes was density, with higher density indicating more positive outcomes. Also significant was the finding that more breadth creates new challenges such as difficulty in reaching consensus and creating ties with other members. However, assumptions that these structural components lead to improved outcomes for public health collaboratives may be slightly premature. Implications of these findings for research and practice are discussed.

DNA-nanoparticle assemblies go organic: macroscopic polymeric materials with nanosized features.

PubMed

Mentovich, Elad D; Livanov, Konstantin; Prusty, Deepak K; Sowwan, Mukules; Richter, Shachar

2012-05-30

One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network.

Movement of feeder-using songbirds: the influence of urban features.

PubMed

Cox, Daniel T C; Inger, Richard; Hancock, Steven; Anderson, Karen; Gaston, Kevin J

2016-11-23

Private gardens provide vital opportunities for people to interact with nature. The most popular form of interaction is through garden bird feeding. Understanding how landscape features and seasons determine patterns of movement of feeder-using songbirds is key to maximising the well-being benefits they provide. To determine these patterns we established three networks of automated data loggers along a gradient of greenspace fragmentation. Over a 12-month period we tracked 452 tagged blue tits Cyantistes caeruleus and great tits Parus major moving between feeder pairs 9,848 times, to address two questions: (i) Do urban features within different forms, and season, influence structural (presence-absence of connections between feeders by birds) and functional (frequency of these connections) connectivity? (ii) Are there general patterns of structural and functional connectivity across forms? Vegetation cover increased connectivity in all three networks, whereas the presence of road gaps negatively affected functional but not structural connectivity. Across networks structural connectivity was lowest in the summer when birds maintain breeding territories, however patterns of functional connectivity appeared to vary with habitat fragmentation. Using empirical data this study shows how key urban features and season influence movement of feeder-using songbirds, and we provide evidence that this is related to greenspace fragmentation.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Epidermolysis bullosa care in Germany.

PubMed

Bruckner-Tuderman, Leena

2010-04-01

Until 2003, no structures existed in Germany for special care of patients with rare diseases, such as epidermolysis bullosa (EB). At that point, the Federal Ministry of Education and Research announced a clinical research program-networks for rare diseases. The Network Epidermolysis Bullosa (EB Network), coordinated from the Department of Dermatology, University Medical Center Freiburg, has operated since October 2003 with the goal of improving diagnostics and clinical management, elucidating disease mechanisms, and development of novel therapies for EB (www.netzwerk-eb.de). Future goals of the EB Network include securing the clinical-diagnostic and IT structures established with grant support and focusing research on molecular disease mechanisms in EB and novel biologically valid therapies. Intensive collaborations with other networks for rare genetic diseases will generate durable structures in Germany and form a basis for future international consortia. Copyright 2010 Elsevier Inc. All rights reserved.

Bonding by Hydroxide-Catalyzed Hydration and Dehydration

NASA Technical Reports Server (NTRS)

Gwo, Dz-Hung

2008-01-01

A simple, inexpensive method for bonding solid objects exploits hydroxide-catalyzed hydration and dehydration to form silicate-like networks in thin surface and interfacial layers between the objects. The method can be practiced at room temperature or over a wide range of temperatures. The method was developed especially to enable the formation of precise, reliable bonds between precise optical components. The bonds thus formed exhibit the precision and transparency of bonds formed by the conventional optical-contact method and the strength and reliability of high-temperature frit bonds. The method also lends itself to numerous non-optical applications in which there are requirements for precise bonds and/or requirements for bonds, whether precise or imprecise, that can reliably withstand severe environmental conditions. Categories of such non-optical applications include forming composite materials, coating substrates, forming laminate structures, and preparing objects of defined geometry and composition. The method is applicable to materials that either (1) can form silicate-like networks in the sense that they have silicate-like molecular structures that are extensible into silicate-like networks or (2) can be chemically linked to silicate-like networks by means of hydroxide-catalyzed hydration and dehydration. When hydrated, a material of either type features surface hydroxyl (-OH) groups. In this method, a silicate-like network that bonds two substrates can be formed either by a bonding material alone or by the bonding material together with material from either or both of the substrates. Typically, an aqueous hydroxide bonding solution is dispensed and allowed to flow between the mating surfaces by capillary action. If the surface figures of the substrates do not match precisely, bonding could be improved by including a filling material in the bonding solution. Preferably, the filling material should include at least one ingredient that can be hydrated to have exposed hydroxyl groups and that can be chemically linked, by hydroxide catalysis, to a silicate-like network. The silicate-like network could be generated in situ from the filling material and/or substrate material, or could be originally present in the bonding material.

Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network.

PubMed

Petrescu-Prahova, Miruna; Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B; Anderson, Lynda A

2015-08-20

Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level.

Universal partitioning of the hierarchical fold network of 50-residue segments in proteins

PubMed Central

Ito, Jun-ichi; Sonobe, Yuki; Ikeda, Kazuyoshi; Tomii, Kentaro; Higo, Junichi

2009-01-01

Background Several studies have demonstrated that protein fold space is structured hierarchically and that power-law statistics are satisfied in relation between the numbers of protein families and protein folds (or superfamilies). We examined the internal structure and statistics in the fold space of 50 amino-acid residue segments taken from various protein folds. We used inter-residue contact patterns to measure the tertiary structural similarity among segments. Using this similarity measure, the segments were classified into a number (Kc) of clusters. We examined various Kc values for the clustering. The special resolution to differentiate the segment tertiary structures increases with increasing Kc. Furthermore, we constructed networks by linking structurally similar clusters. Results The network was partitioned persistently into four regions for Kc ≥ 1000. This main partitioning is consistent with results of earlier studies, where similar partitioning was reported in classifying protein domain structures. Furthermore, the network was partitioned naturally into several dozens of sub-networks (i.e., communities). Therefore, intra-sub-network clusters were mutually connected with numerous links, although inter-sub-network ones were rarely done with few links. For Kc ≥ 1000, the major sub-networks were about 40; the contents of the major sub-networks were conserved. This sub-partitioning is a novel finding, suggesting that the network is structured hierarchically: Segments construct a cluster, clusters form a sub-network, and sub-networks constitute a region. Additionally, the network was characterized by non-power-law statistics, which is also a novel finding. Conclusion Main findings are: (1) The universe of 50 residue segments found here was characterized by non-power-law statistics. Therefore, the universe differs from those ever reported for the protein domains. (2) The 50-residue segments were partitioned persistently and universally into some dozens (ca. 40) of major sub-networks, irrespective of the number of clusters. (3) These major sub-networks encompassed 90% of all segments. Consequently, the protein tertiary structure is constructed using the dozens of elements (sub-networks). PMID:19454039

Centrality measures in temporal networks with time series analysis

NASA Astrophysics Data System (ADS)

Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun

2017-05-01

The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

Self-Assembly of Phenylalanine Oligopeptides: Insights from Experiments and Simulations

PubMed Central

Tamamis, Phanourios; Adler-Abramovich, Lihi; Reches, Meital; Marshall, Karen; Sikorski, Pawel; Serpell, Louise; Gazit, Ehud; Archontis, Georgios

2009-01-01

Abstract Studies of peptide-based nanostructures provide general insights into biomolecular self-assembly and can lead material engineering toward technological applications. The diphenylalanine peptide (FF) self-assembles into discrete, hollow, well ordered nanotubes, and its derivatives form nanoassemblies of various morphologies. Here we demonstrate for the first time, to our knowledge, the formation of planar nanostructures with β-sheet content by the triphenylalanine peptide (FFF). We characterize these structures using various microscopy and spectroscopy techniques. We also obtain insights into the interactions and structural properties of the FF and FFF nanostructures by 0.4-μs, implicit-solvent, replica-exchange, molecular-dynamics simulations of aqueous FF and FFF solutions. In the simulations the peptides form aggregates, which often contain open or ring-like peptide networks, as well as elementary and network-containing structures with β-sheet characteristics. The networks are stabilized by polar and nonpolar interactions, and by the surrounding aggregate. In particular, the charged termini of neighbor peptides are involved in hydrogen-bonding interactions and their aromatic side chains form “T-shaped” contacts, as in three-dimensional FF crystals. These interactions may assist the FF and FFF self-assembly at the early stage, and may also stabilize the mature nanostructures. The FFF peptides have higher network propensities and increased aggregate stabilities with respect to FF, which can be interpreted energetically. PMID:19527662

Regulation of Mitochondrial Structure and Dynamics by the Cytoskeleton and Mechanical Factors.

PubMed

Bartolák-Suki, Erzsébet; Imsirovic, Jasmin; Nishibori, Yuichiro; Krishnan, Ramaswamy; Suki, Béla

2017-08-21

Mitochondria supply cells with energy in the form of ATP, guide apoptosis, and contribute to calcium buffering and reactive oxygen species production. To support these diverse functions, mitochondria form an extensive network with smaller clusters that are able to move along microtubules aided by motor proteins. Mitochondria are also associated with the actin network, which is involved in cellular responses to various mechanical factors. In this review, we discuss mitochondrial structure and function in relation to the cytoskeleton and various mechanical factors influencing cell functions. We first summarize the morphological features of mitochondria with an emphasis on fission and fusion as well as how network properties govern function. We then review the relationship between the mitochondria and the cytoskeletal structures, including mechanical interactions. We also discuss how stretch and its dynamic pattern affect mitochondrial structure and function. Finally, we present preliminary data on how extracellular matrix stiffness influences mitochondrial morphology and ATP generation. We conclude by discussing the more general role that mitochondria may play in mechanobiology and how the mechanosensitivity of mitochondria may contribute to the development of several diseases and aging.

Regulation of Mitochondrial Structure and Dynamics by the Cytoskeleton and Mechanical Factors

PubMed Central

Bartolák-Suki, Erzsébet; Imsirovic, Jasmin; Nishibori, Yuichiro; Krishnan, Ramaswamy; Suki, Béla

2017-01-01

Mitochondria supply cells with energy in the form of ATP, guide apoptosis, and contribute to calcium buffering and reactive oxygen species production. To support these diverse functions, mitochondria form an extensive network with smaller clusters that are able to move along microtubules aided by motor proteins. Mitochondria are also associated with the actin network, which is involved in cellular responses to various mechanical factors. In this review, we discuss mitochondrial structure and function in relation to the cytoskeleton and various mechanical factors influencing cell functions. We first summarize the morphological features of mitochondria with an emphasis on fission and fusion as well as how network properties govern function. We then review the relationship between the mitochondria and the cytoskeletal structures, including mechanical interactions. We also discuss how stretch and its dynamic pattern affect mitochondrial structure and function. Finally, we present preliminary data on how extracellular matrix stiffness influences mitochondrial morphology and ATP generation. We conclude by discussing the more general role that mitochondria may play in mechanobiology and how the mechanosensitivity of mitochondria may contribute to the development of several diseases and aging. PMID:28825689

Percolation on shopping and cashback electronic commerce networks

NASA Astrophysics Data System (ADS)

Fu, Tao; Chen, Yini; Qin, Zhen; Guo, Liping

2013-06-01

Many realistic networks live in the form of multiple networks, including interacting networks and interdependent networks. Here we study percolation properties of a special kind of interacting networks, namely Shopping and Cashback Electronic Commerce Networks (SCECNs). We investigate two actual SCECNs to extract their structural properties, and develop a mathematical framework based on generating functions for analyzing directed interacting networks. Then we derive the necessary and sufficient condition for the absence of the system-wide giant in- and out- component, and propose arithmetic to calculate the corresponding structural measures in the sub-critical and supercritical regimes. We apply our mathematical framework and arithmetic to those two actual SCECNs to observe its accuracy, and give some explanations on the discrepancies. We show those structural measures based on our mathematical framework and arithmetic are useful to appraise the status of SCECNs. We also find that the supercritical regime of the whole network is maintained mainly by hyperlinks between different kinds of websites, while those hyperlinks between the same kinds of websites can only enlarge the sizes of in-components and out-components.

Connectivity of glass structure. Oxygen number

NASA Astrophysics Data System (ADS)

Medvedev, E. F.; Min'ko, N. I.

2018-03-01

With reference to mathematics, crystal chemistry and chemical technology of synthesis of glass structures in the solution (sol-gel technology), the paper is devoted to the study of the degree of connectivity of a silicon-oxygen backbone (fSi) and the oxygen number (R) [1]. It reveals logical contradictions and uncertainty of mathematical expressions of parameters, since fSi is not similar to the oxygen number. The connectivity of any structure is a result of various types of bonds: ion-covalent, donor-acceptor, hydrogen bonds, etc. Besides, alongside with SiO2, many glass compositions contain other glass-forming elements due to tetrahedral sites thus formed. The connectivity function of a glassy network with any set of glass-forming elements is roughly ensured by connectivity factor Y [2], which has monovalent elements loosening a glassy network. The paper considers the existence of various structural motives in hydrogen-impermeable glasses containing B2O3, Al2O3, PbO, Na2O, K2O and rare-earth elements. Hence, it also describes gradual nucleation, change of crystal forms, and structure consolidation in the process of substance intake from a matrix solution according to sol-gel technology. The crystal form varied from two-dimensional plates to three-dimensional and dendritical ones [3]. Alternative parameters, such as the oxygen number (O) and the structure connectivity factor (Y), were suggested. Functional dependence of Y=f(O) to forecast the generated structures was obtained for two- and multicomponent glass compositions.

Dermoscopy of accessory nipples in authors’ own study

PubMed Central

Szymszal, Jan; Silny, Wojciech

2014-01-01

Introduction The accessory nipple (AN) is characterised by its network-like structures, which may suggest the diagnosis of a melanocytic lesion. The knowledge about additional dermoscopic features of AN may greatly minimise the risk of unnecessary surgical excisions. Aim To analyse and present different clinical and dermoscopic forms, in which the AN may appear. Material and methods Ninety AN with dermoscopic features were evaluated in the study, detected in 14 patients between the years 2008 and 2014. Results The most common dermoscopic features of the AN were central, scar-like areas (15/19) and peripheral network-like structures (12/19). A number of cleft-like appearances (8/19) and central network-like structures (7/19) had also been observed. Moreover, among the dermoscopic features, white cobblestone-like structures (7/19), a central round dimpling with a plug (6/19) and fisheye-like structures resembling comedo-like openings (9/19) have all also been noted. There is a statistical significance in the occurrence of white cobblestone-like structures with central network-like structures (Fisher's exact test p = 0.0449). The presence of peripheral network-like structures with the occurrence of central scar-like areas was statistically highly significant (p = 0.0091). The central round dimpling was never observed alongside any central network-like structures in any of the lesions (p = 0.0436). Conclusions Accessory nipples are most commonly characterised by the occurrence of a peripheral network-like structure accompanied by the presence of a scar-like area. PMID:25097482

Short-range structure and cation bonding in calcium-aluminum metaphosphate glasses.

PubMed

Schneider, J; Oliveira, S L; Nunes, L A O; Bonk, F; Panepucci, H

2005-01-24

Comprehension of short- and medium-range order of phosphate glasses is a topic of interest, due to the close relation between network structure and mechanical, thermal, and optical properties. In this work, the short-range structure of glasses (1 - x)Ca(PO(3))(2).xAl(PO(3))(3) with 0 < or = x < or = 0.47 was studied using solid-state nuclear magnetic resonance spectroscopy, Raman spectroscopy, density measurements, and differential scanning calorimetry. The bonding between a network modifier species, Al, and the network forming phosphate groups was probed using high-resolution nuclear magnetic resonance spectroscopy of (27)Al and (31)P. Changes in the compositional behavior of the density, glass transition temperature, PO(2) symmetric vibrations, and Al coordination number were verified at around x = 0.30. (31)P NMR spectra show the presence of phosphorus in Q(2) sites with nonbridging oxygens (NBOs) coordinated by Ca ions and also Q(2) sites with one NBO coordinated by Al (namely, Q(2)(1Al)). The changes in the properties as a function of x can be understood by considering the mean coordination number measured for Al and the formation of only Q(2) and Q(2)(1Al) species. It is possible to calculate that a network formed only by Q(2)(1Al) phosphates can just exist up to the upper limit of x = 0.48. Above this value, Q(2)(2Al) species should appear, imposing a major reorganization of the network. Above x = 0.30 the network undergoes a progressive reorganization to incorporate Al ions, maintaining the condition that only Q(2)(1Al) species are formed. These observations support the idea that bonding principles for cationic species inferred originally in binary phosphate glasses can also be extended to ternary systems.

NMR study on the network structure of a mixed gel of kappa and iota carrageenans.

PubMed

Hu, Bingjie; Du, Lei; Matsukawa, Shingo

2016-10-05

The temperature dependencies of the (1)H T2 and diffusion coefficient (D) of a mixed solution of kappa-carrageenan and iota-carrageenan were measured by NMR. Rheological and NMR measurements suggested an exponential formation of rigid aggregates of kappa-carrageenan and a gradual formation of fine aggregates of iota-carrageenan during two step increases of G'. The results also suggested that longer carrageenan chains are preferentially involved in aggregation, thus resulting in a decrease in the average Mw of solute carrageenans. The results of diffusion measurements for poly(ethylene oxide) (PEO) suggested that kappa-carrageenan formed thick aggregates that decreased hindrance to PEO diffusion by decreasing the solute kappa-carrageenan concentration in the voids of the aggregated chains, and that iota-carrageenan formed fine aggregates that decreased the solute iota-carrageenan concentration less. DPEO in a mixed solution of kappa-carrageenan and iota-carrageenan suggested two possibilities for the microscopic network structure: an interpenetrating network structure, or micro-phase separation. Copyright © 2016. Published by Elsevier Ltd.

Shape memory polymers

DOEpatents

Wilson, Thomas S.; Bearinger, Jane P.

2017-08-29

New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.

Shape memory polymers

DOEpatents

Wilson, Thomas S.; Bearinger, Jane P.

2015-06-09

New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxyl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.

High performances of dual network PVA hydrogel modified by PVP using borax as the structure-forming accelerator

PubMed Central

Huang, Min; Hou, Yi; Li, Yubao; Wang, Danqing; Zhang, Li

2017-01-01

Abstract A dual network hydrogel made up of polyvinylalcohol (PVA) crosslinked by borax and polyvinylpyrrolidone (PVP) was prepared by means of freezing-thawing circles. Here PVP was incorporated by linking with PVA to form a network structure, while the introduction of borax played the role of crosslinking PVA chains to accelerate the formation of a dual network structure in PVA/PVP composite hydrogel, thus endowing the hydrogel with high mechanical properties. The effects of both PVP and borax on the hydrogels were evaluated by comparing the two systems of PVA/PVP/borax and PVA/borax hydrogels. In the former system, adding 4.0% PVP not only increased the water content and the storage modulus but also enhanced the mechanical strength of the final hydrogel. But an overdose of PVP just as more than 4.0% tended to undermine the structure of hydrogels, and thus deteriorated hydrogels’ properties because of the weakened secondary interaction between PVP and PVA. Likewise, increasing borax could promote the gel crosslinking degree, thus making gels show a decrease in water content and swelling ratio, meanwhile shrinking the pores inside the hydrogels and finally enhancing the mechanical strength of hydrogels prominently. The developed hydrogel with high performances holds great potential for applications in biomedical and industrial fields. PMID:29491822

Assembly, Structure, and Functionality of Metal-Organic Networks and Organic Semiconductor Layers at Surfaces

NASA Astrophysics Data System (ADS)

Tempas, Christopher D.

Self-assembled nanostructures at surfaces show promise for the development of next generation technologies including organic electronic devices and heterogeneous catalysis. In many cases, the functionality of these nanostructures is not well understood. This thesis presents strategies for the structural design of new on-surface metal-organic networks and probes their chemical reactivity. It is shown that creating uniform metal sites greatly increases selectivity when compared to ligand-free metal islands. When O2 reacts with single-site vanadium centers, in redox-active self-assembled coordination networks on the Au(100) surface, it forms one product. When O2 reacts with vanadium metal islands on the same surface, multiple products are formed. Other metal-organic networks described in this thesis include a mixed valence network containing Pt0 and PtII and a network where two Fe centers reside in close proximity. This structure is stable to temperatures >450 °C. These new on-surface assemblies may offer the ability to perform reactions of increasing complexity as future heterogeneous catalysts. The functionalization of organic semiconductor molecules is also shown. When a few molecular layers are grown on the surface, it is seen that the addition of functional groups changes both the film's structure and charge transport properties. This is due to changes in both first layer packing structure and the pi-electron distribution in the functionalized molecules compared to the original molecule. The systems described in this thesis were studied using high-resolution scanning tunneling microscopy, non-contact atomic force microscopy, and X-ray photoelectron spectroscopy. Overall, this work provides strategies for the creation of new, well-defined on-surface nanostructures and adds additional chemical insight into their properties.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

Modeling of polymer networks for application to solid propellant formulating

NASA Technical Reports Server (NTRS)

Marsh, H. E.

1979-01-01

Methods for predicting the network structural characteristics formed by the curing of pourable elastomers were presented; as well as the logic which was applied in the development of mathematical models. A universal approach for modeling was developed and verified by comparison with other methods in application to a complex system. Several applications of network models to practical problems are described.

Controllable two-scale network architecture and enhanced mechanical properties of (Ti5Si3+TiBw)/Ti6Al4V composites.

PubMed

Jiao, Y; Huang, L J; Duan, T B; Wei, S L; Kaveendran, B; Geng, L

2016-09-13

Novel Ti6Al4V alloy matrix composites with a controllable two-scale network architecture were successfully fabricated by reaction hot pressing (RHP). TiB whiskers (TiBw) were in-situ synthesized around the Ti6Al4V matrix particles, and formed the first-scale network structure (FSNS). Ti5Si3 needles (Ti5Si3) precipitated in the β phase around the equiaxed α phase, and formed the secondary-scale network structure (SSNS). This resulted in increased deformation compatibility accompanied with enhanced mechanical properties. Apart from the reinforcement distribution and the volume fraction, the ratio between Ti5Si3 and TiBw fraction were controlled. The prepared (Ti5Si3 + TiBw)/Ti6Al4V composites showed higher tensile strength and ductility than the composites with a one-scale microstructure, and superior wear resistance over the Ti6Al4V alloy under dry sliding wear conditions at room temperature.

What can graph theory tell us about word learning and lexical retrieval?

PubMed

Vitevitch, Michael S

2008-04-01

Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of phonological word-forms. Pajek, a program for large network analysis and visualization (V. Batagelj & A. Mvrar, 1998), was used to examine several characteristics of a network derived from a computerized database of the adult lexicon. Nodes in the network represented words, and a link connected two nodes if the words were phonological neighbors. The average path length and clustering coefficient suggest that the phonological network exhibits small-world characteristics. The degree distribution was fit better by an exponential rather than a power-law function. Finally, the network exhibited assortative mixing by degree. Some of these structural characteristics were also found in graphs that were formed by 2 simple stochastic processes suggesting that similar processes might influence the development of the lexicon. The graph theoretic perspective may provide novel insights about the mental lexicon and lead to future studies that help us better understand language development and processing.

Beyond dark and bright: towards a more holistic understanding of inter-group networks.

PubMed

Hejnova, Petra

2010-01-01

Networks are becoming a popular organizational form for structuring human activities. To date, scholars have addressed networks in a variety of fields, including sociology, economics, public administration, criminology, political science, and international security. However, little has been done so far to systematically examine the similarities, differences, and connections between network forms of organization across different academic disciplines. This has important implications for both theory and practice. The lack of attention paid to organizational similarities and differences prevents the exchange of knowledge developed across fields. In turn, policy-makers cannot take full advantage of existing research, and may miss opportunities to improve the work of some networks and combat that of others. To address this gap in the literature, this paper uses the combination of organizational environments and organizational goals to develop a new typology of inter-group networks, and thus improve our understanding of how human behaviour is coordinated through networks.

NETWORK STRUCTURE, MULTIPLEXITY, AND EVOLUTION AS INFLUENCES ON COMMUNITY-BASED PARTICIPATORY INTERVENTIONS.

PubMed

Wang, Rong; Tanjasiri, Sora Park; Palmer, Paula; Valente, Thomas W

2016-08-01

This study applies an ecological perspective to the context of community-based participatory research (CBPR). Specifically, it examines how endogenous and exogenous factors influence the dynamics of CBPR partnerships, including the tendency toward reciprocity and transitivity, the organizational type, the level of resource sufficiency, the level of organizational influence, and the perceived CBPR effect on organizations. The results demonstrate that network structure is related to the selection and retention of interorganizational networks over time, and organizations of the same type are more likely to form partnerships with each other. It shows that the dynamics of the CBPR initiative presented in this article were driven by the structure of the interorganizational networks rather than their individual organizational attributes. Implications for sustaining CBPR partnerships are drawn from the findings.

NETWORK STRUCTURE, MULTIPLEXITY, AND EVOLUTION AS INFLUENCES ON COMMUNITY-BASED PARTICIPATORY INTERVENTIONS

PubMed Central

Wang, Rong; Tanjasiri, Sora Park; Palmer, Paula; Valente, Thomas W.

2017-01-01

This study applies an ecological perspective to the context of community-based participatory research (CBPR). Specifically, it examines how endogenous and exogenous factors influence the dynamics of CBPR partnerships, including the tendency toward reciprocity and transitivity, the organizational type, the level of resource sufficiency, the level of organizational influence, and the perceived CBPR effect on organizations. The results demonstrate that network structure is related to the selection and retention of interorganizational networks over time, and organizations of the same type are more likely to form partnerships with each other. It shows that the dynamics of the CBPR initiative presented in this article were driven by the structure of the interorganizational networks rather than their individual organizational attributes. Implications for sustaining CBPR partnerships are drawn from the findings. PMID:29430067

Wild cricket social networks show stability across generations.

PubMed

Fisher, David N; Rodríguez-Muñoz, Rolando; Tregenza, Tom

2016-07-27

A central part of an animal's environment is its interactions with conspecifics. There has been growing interest in the potential to capture these interactions in the form of a social network. Such networks can then be used to examine how relationships among individuals affect ecological and evolutionary processes. However, in the context of selection and evolution, the utility of this approach relies on social network structures persisting across generations. This is an assumption that has been difficult to test because networks spanning multiple generations have not been available. We constructed social networks for six annual generations over a period of eight years for a wild population of the cricket Gryllus campestris. Through the use of exponential random graph models (ERGMs), we found that the networks in any given year were able to predict the structure of networks in other years for some network characteristics. The capacity of a network model of any given year to predict the networks of other years did not depend on how far apart those other years were in time. Instead, the capacity of a network model to predict the structure of a network in another year depended on the similarity in population size between those years. Our results indicate that cricket social network structure resists the turnover of individuals and is stable across generations. This would allow evolutionary processes that rely on network structure to take place. The influence of network size may indicate that scaling up findings on social behaviour from small populations to larger ones will be difficult. Our study also illustrates the utility of ERGMs for comparing networks, a task for which an effective approach has been elusive.

A Bayesian Active Learning Experimental Design for Inferring Signaling Networks.

PubMed

Ness, Robert O; Sachs, Karen; Mallick, Parag; Vitek, Olga

2018-06-21

Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity. We describe an active learning strategy for selecting optimal interventions. Our approach takes as inputs pathway databases and historic data sets, expresses them in form of prior probability distributions on network structures, and selects interventions that maximize their expected contribution to structure learning. Evaluations on simulated and real data show that the strategy reduces the detection error of validated edges as compared with an unguided choice of interventions and avoids redundant interventions, thereby increasing the effectiveness of the experiment.

Formation of metallic cation-oxygen network for anomalous thermal expansion coefficients in binary phosphate glass

NASA Astrophysics Data System (ADS)

Onodera, Yohei; Kohara, Shinji; Masai, Hirokazu; Koreeda, Akitoshi; Okamura, Shun; Ohkubo, Takahiro

2017-05-01

Understanding glass structure is still challenging due to the result of disorder, although novel materials design on the basis of atomistic structure has been strongly demanded. Here we report on the atomic structures of the zinc phosphate glass determined by reverse Monte Carlo modelling based on diffraction and spectroscopic data. The zinc-rich glass exhibits the network formed by ZnOx (averaged x<4) polyhedra. Although the elastic modulus, refractive index and glass transition temperature of the zinc phosphate glass monotonically increase with the amount of ZnO, we find for the first time that the thermal expansion coefficient is very sensitive to the substitution of the phosphate chain network by a network consisting of Zn-O units in zinc-rich glass. Our results imply that the control of the structure of intermediate groups may enable new functionalities in the design of oxide glass materials.

Formation of metallic cation-oxygen network for anomalous thermal expansion coefficients in binary phosphate glass.

PubMed

Onodera, Yohei; Kohara, Shinji; Masai, Hirokazu; Koreeda, Akitoshi; Okamura, Shun; Ohkubo, Takahiro

2017-05-31

Understanding glass structure is still challenging due to the result of disorder, although novel materials design on the basis of atomistic structure has been strongly demanded. Here we report on the atomic structures of the zinc phosphate glass determined by reverse Monte Carlo modelling based on diffraction and spectroscopic data. The zinc-rich glass exhibits the network formed by ZnO x (averaged x<4) polyhedra. Although the elastic modulus, refractive index and glass transition temperature of the zinc phosphate glass monotonically increase with the amount of ZnO, we find for the first time that the thermal expansion coefficient is very sensitive to the substitution of the phosphate chain network by a network consisting of Zn-O units in zinc-rich glass. Our results imply that the control of the structure of intermediate groups may enable new functionalities in the design of oxide glass materials.

Structure-topology-property correlations of sodium phosphosilicate glasses.

PubMed

Hermansen, Christian; Guo, Xiaoju; Youngman, Randall E; Mauro, John C; Smedskjaer, Morten M; Yue, Yuanzheng

2015-08-14

In this work, we investigate the correlations among structure, topology, and properties in a series of sodium phosphosilicate glasses with [SiO2]/[SiO2 + P2O5] ranging from 0 to 1. The network structure is characterized by (29)Si and (31)P magic-angle spinning nuclear magnetic resonance and Raman spectroscopy. The results show the formation of six-fold coordinated silicon species in phosphorous-rich glasses. Based on the structural data, we propose a formation mechanism of the six-fold coordinated silicon, which is used to develop a quantitative structural model for predicting the speciation of the network forming units as a function of chemical composition. The structural model is then used to establish a temperature-dependent constraint description of phosphosilicate glass topology that enables prediction of glass transition temperature, liquid fragility, and indentation hardness. The topological constraint model provides insight into structural origin of the mixed network former effect in phosphosilicate glasses.

Self-organization in suspensions of end-functionalized semiflexible polymers under shear flow

NASA Astrophysics Data System (ADS)

Myung, Jin Suk; Winkler, Roland G.; Gompper, Gerhard

2015-12-01

The nonequilibrium dynamical behavior and structure formation of end-functionalized semiflexible polymer suspensions under flow are investigated by mesoscale hydrodynamic simulations. The hybrid simulation approach combines the multiparticle collision dynamics method for the fluid, which accounts for hydrodynamic interactions, with molecular dynamics simulations for the semiflexible polymers. In equilibrium, various kinds of scaffold-like network structures are observed, depending on polymer flexibility and end-attraction strength. We investigate the flow behavior of the polymer networks under shear and analyze their nonequilibrium structural and rheological properties. The scaffold structure breaks up and densified aggregates are formed at low shear rates, while the structural integrity is completely lost at high shear rates. We provide a detailed analysis of the shear- rate-dependent flow-induced structures. The studies provide a deeper understanding of the formation and deformation of network structures in complex materials.

Design of nano- and microfiber combined scaffolds by electrospinning of collagen onto starch-based fiber meshes: a man-made equivalent of natural extracellular matrix.

PubMed

Tuzlakoglu, Kadriye; Santos, Marina I; Neves, Nuno; Reis, Rui L

2011-02-01

Mimicking the structural organization and biologic function of natural extracellular matrix has been one of the main goals of tissue engineering. Nevertheless, the majority of scaffolding materials for bone regeneration highlights biochemical functionality in detriment of mechanical properties. In this work we present a rather innovative construct that combines in the same structure electrospun type I collagen nanofibers with starch-based microfibers. These combined structures were obtained by a two-step methodology and structurally consist in a type I collagen nano-network incorporated on a macro starch-based support. The morphology of the developed structures was assessed by several microscopy techniques and the collagenous nature of the nano-network was confirmed by immunohistochemistry. In addition, and especially regarding the requirements of large bone defects, we also successfully introduced the concept of layer by layer, as a way to produce thicker structures. In an attempt to recreate bone microenvironment, the design and biochemical composition of the combined structures also envisioned bone-forming cells and endothelial cells (ECs). The inclusion of a type I collagen nano-network induced a stretched morphology and improved the metabolic activity of osteoblasts. Regarding ECs, the presence of type I collagen on the combined structures provided adhesive support and obviated the need of precoating with fibronectin. It was also importantly observed that ECs on the nano-network organized into circular structures, a three-dimensional arrangement distinct from that observed for osteoblasts and resembling the microcappillary-like organizations formed during angiogenesis. By providing simultaneously physical and chemical cues for cells, the herein-proposed combined structures hold a great potential in bone regeneration as a man-made equivalent of extracellular matrix.

A bicontinuous tetrahedral structure in a liquid-crystalline lipid

NASA Astrophysics Data System (ADS)

Longley, William; McIntosh, Thomas J.

1983-06-01

The structure of most lipid-water phases can be visualized as an ordered distribution of two liquid media, water and hydrocarbons, separated by a continuous surface covered by the polar groups of the lipid molecules1. In the cubic phases in particular, rod-like elements are linked into three-dimensional networks1,2. Two of these phases (space groups Ia3d and Pn3m) contain two such three-dimensional networks mutually inter-woven and unconnected. Under the constraints of energy minimization3, the interface between the components in certain of these `porous fluids' may well resemble one of the periodic minimal surface structures of the type described mathematically by Schwarz4,5. A structure of this sort has been proposed for the viscous isotropic (cubic) form of glycerol monooleate (GMO) by Larsson et al.6 who suggested that the X-ray diagrams of Lindblom et al.7 indicated a body-centred crystal structure in which lipid bilayers might be arranged as in Schwarz's octahedral surface4. We have now found that at high water contents, a primitive cubic lattice better fits the X-ray evidence with the material in the crystal arranged in a tetrahedral way. The lipid appears to form a single bilayer, continuous in three dimensions, separating two continuous interlinked networks of water. Each of the water networks has the symmetry of the diamond crystal structure and the bilayer lies in the space between them following a surface resembling Schwarz's tetrahedral surface4.

Neural-like growing networks

NASA Astrophysics Data System (ADS)

Yashchenko, Vitaliy A.

2000-03-01

On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

Bribery games on inter-dependent regular networks.

PubMed

Verma, Prateek; Nandi, Anjan K; Sengupta, Supratim

2017-02-16

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen's network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

Comparing species interaction networks along environmental gradients.

PubMed

Pellissier, Loïc; Albouy, Camille; Bascompte, Jordi; Farwig, Nina; Graham, Catherine; Loreau, Michel; Maglianesi, Maria Alejandra; Melián, Carlos J; Pitteloud, Camille; Roslin, Tomas; Rohr, Rudolf; Saavedra, Serguei; Thuiller, Wilfried; Woodward, Guy; Zimmermann, Niklaus E; Gravel, Dominique

2018-05-01

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients. © 2017 Cambridge Philosophical Society.

Relating the large-scale structure of time series and visibility networks.

PubMed

Rodríguez, Miguel A

2017-06-01

The structure of time series is usually characterized by means of correlations. A new proposal based on visibility networks has been considered recently. Visibility networks are complex networks mapped from surfaces or time series using visibility properties. The structures of time series and visibility networks are closely related, as shown by means of fractional time series in recent works. In these works, a simple relationship between the Hurst exponent H of fractional time series and the exponent of the distribution of edges γ of the corresponding visibility network, which exhibits a power law, is shown. To check and generalize these results, in this paper we delve into this idea of connected structures by defining both structures more properly. In addition to the exponents used before, H and γ, which take into account local properties, we consider two more exponents that, as we will show, characterize global properties. These are the exponent α for time series, which gives the scaling of the variance with the size as var∼T^{2α}, and the exponent κ of their corresponding network, which gives the scaling of the averaged maximum of the number of edges, 〈k_{M}〉∼N^{κ}. With this representation, a more precise connection between the structures of general time series and their associated visibility network is achieved. Similarities and differences are more clearly established, and new scaling forms of complex networks appear in agreement with their respective classes of time series.

APINetworks: A general API for the treatment of complex networks in arbitrary computational environments

NASA Astrophysics Data System (ADS)

Niño, Alfonso; Muñoz-Caro, Camelia; Reyes, Sebastián

2015-11-01

The last decade witnessed a great development of the structural and dynamic study of complex systems described as a network of elements. Therefore, systems can be described as a set of, possibly, heterogeneous entities or agents (the network nodes) interacting in, possibly, different ways (defining the network edges). In this context, it is of practical interest to model and handle not only static and homogeneous networks but also dynamic, heterogeneous ones. Depending on the size and type of the problem, these networks may require different computational approaches involving sequential, parallel or distributed systems with or without the use of disk-based data structures. In this work, we develop an Application Programming Interface (APINetworks) for the modeling and treatment of general networks in arbitrary computational environments. To minimize dependency between components, we decouple the network structure from its function using different packages for grouping sets of related tasks. The structural package, the one in charge of building and handling the network structure, is the core element of the system. In this work, we focus in this API structural component. We apply an object-oriented approach that makes use of inheritance and polymorphism. In this way, we can model static and dynamic networks with heterogeneous elements in the nodes and heterogeneous interactions in the edges. In addition, this approach permits a unified treatment of different computational environments. Tests performed on a C++11 version of the structural package show that, on current standard computers, the system can handle, in main memory, directed and undirected linear networks formed by tens of millions of nodes and edges. Our results compare favorably to those of existing tools.

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

The modularity of seed dispersal: differences in structure and robustness between bat- and bird-fruit networks.

PubMed

Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo R; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez

2011-09-01

In networks of plant-animal mutualisms, different animal groups interact preferentially with different plants, thus forming distinct modules responsible for different parts of the service. However, what we currently know about seed dispersal networks is based only on birds. Therefore, we wished to fill this gap by studying bat-fruit networks and testing how they differ from bird-fruit networks. As dietary overlap of Neotropical bats and birds is low, they should form distinct mutualistic modules within local networks. Furthermore, since frugivory evolved only once among Neotropical bats, but several times independently among Neotropical birds, greater dietary overlap is expected among bats, and thus connectance and nestedness should be higher in bat-fruit networks. If bat-fruit networks have higher nestedness and connectance, they should be more robust to extinctions. We analyzed 1 mixed network of both bats and birds and 20 networks that consisted exclusively of either bats (11) or birds (9). As expected, the structure of the mixed network was both modular (M = 0.45) and nested (NODF = 0.31); one module contained only birds and two only bats. In 20 datasets with only one disperser group, bat-fruit networks (NODF = 0.53 ± 0.09, C = 0.30 ± 0.11) were more nested and had a higher connectance than bird-fruit networks (NODF = 0.42 ± 0.07, C = 0.22 ± 0.09). Unexpectedly, robustness to extinction of animal species was higher in bird-fruit networks (R = 0.60 ± 0.13) than in bat-fruit networks (R = 0.54 ± 0.09), and differences were explained mainly by species richness. These findings suggest that a modular structure also occurs in seed dispersal networks, similar to pollination networks. The higher nestedness and connectance observed in bat-fruit networks compared with bird-fruit networks may be explained by the monophyletic evolution of frugivory in Neotropical bats, among which the diets of specialists seem to have evolved from the pool of fruits consumed by generalists.

Why are some plant-pollinator networks more nested than others?

PubMed

Song, Chuliang; Rohr, Rudolf P; Saavedra, Serguei

2017-10-01

Empirical studies have found that the mutualistic interactions forming the structure of plant-pollinator networks are typically more nested than expected by chance alone. Additionally, theoretical studies have shown a positive association between the nested structure of mutualistic networks and community persistence. Yet, it has been shown that some plant-pollinator networks may be more nested than others, raising the interesting question of which factors are responsible for such enhanced nested structure. It has been argued that ordered network structures may increase the persistence of ecological communities under less predictable environments. This suggests that nested structures of plant-pollinator networks could be more advantageous under highly seasonal environments. While several studies have investigated the link between nestedness and various environmental variables, unfortunately, there has been no unified answer to validate these predictions. Here, we move from the problem of describing network structures to the problem of comparing network structures. We develop comparative statistics, and apply them to investigate the association between the nested structure of 59 plant-pollinator networks and the temperature seasonality present in their locations. We demonstrate that higher levels of nestedness are associated with a higher temperature seasonality. We show that the previous lack of agreement came from an extended practice of using standardized measures of nestedness that cannot be compared across different networks. Importantly, our observations complement theory showing that more nested network structures can increase the range of environmental conditions compatible with species coexistence in mutualistic systems, also known as structural stability. This increase in nestedness should be more advantageous and occur more often in locations subject to random environmental perturbations, which could be driven by highly changing or seasonal environments. This synthesis of theory and observations could prove relevant for a better understanding of the ecological processes driving the assembly and persistence of ecological communities. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Implications of Network Structure on Public Health Collaboratives

ERIC Educational Resources Information Center

Retrum, Jessica H.; Chapman, Carrie L.; Varda, Danielle M.

2013-01-01

Interorganizational collaboration is an essential function of public health agencies. These partnerships form social networks that involve diverse types of partners and varying levels of interaction. Such collaborations are widely accepted and encouraged, yet very little comparative research exists on how public health partnerships develop and…

Complex networks with scale-free nature and hierarchical modularity

NASA Astrophysics Data System (ADS)

Shekatkar, Snehal M.; Ambika, G.

2015-09-01

Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many networked systems like biological cell, human society and World Wide Web markedly deviate from that of completely random networks indicating the presence of underlying processes. Often the main process involved in their evolution is the addition of links between existing nodes having a common neighbor. In this context we introduce an important property of the nodes, which we call mediating capacity, that is generic to many networks. This capacity decreases rapidly with increase in degree, making hubs weak mediators of the process. We show that this property of nodes provides an explanation for the simultaneous occurrence of the observed scale-free structure and hierarchical modularity in many networked systems. This also explains the high clustering and small-path length seen in real networks as well as non-zero degree-correlations. Our study also provides insight into the local process which ultimately leads to emergence of preferential attachment and hence is also important in understanding robustness and control of real networks as well as processes happening on real networks.

DNA-nanoparticle assemblies go organic: Macroscopic polymeric materials with nanosized features

PubMed Central

2012-01-01

Background One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Method Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. Results and conclusions One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network. PMID:22646980

Linear induction accelerator and pulse forming networks therefor

DOEpatents

Buttram, Malcolm T.; Ginn, Jerry W.

1989-01-01

A linear induction accelerator includes a plurality of adder cavities arranged in a series and provided in a structure which is evacuated so that a vacuum inductance is provided between each adder cavity and the structure. An energy storage system for the adder cavities includes a pulsed current source and a respective plurality of bipolar converting networks connected thereto. The bipolar high-voltage, high-repetition-rate square pulse train sets and resets the cavities.

The BioPlex Network: A Systematic Exploration of the Human Interactome.

PubMed

Huttlin, Edward L; Ting, Lily; Bruckner, Raphael J; Gebreab, Fana; Gygi, Melanie P; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E; De Camilli, Pietro; Paulo, Joao A; Harper, J Wade; Gygi, Steven P

2015-07-16

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors. Copyright © 2015 Elsevier Inc. All rights reserved.

The BioPlex Network: A Systematic Exploration of the Human Interactome

PubMed Central

Huttlin, Edward L.; Ting, Lily; Bruckner, Raphael J.; Gebreab, Fana; Gygi, Melanie P.; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K.; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A.; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E.; DeCamilli, Pietro; Paulo, Joao A.; Harper, J. Wade; Gygi, Steven P.

2015-01-01

SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors. PMID:26186194

Construction and manipulation of functional three-dimensional droplet networks.

PubMed

Wauer, Tobias; Gerlach, Holger; Mantri, Shiksha; Hill, Jamie; Bayley, Hagan; Sapra, K Tanuj

2014-01-28

Previously, we reported the manual assembly of lipid-coated aqueous droplets in oil to form two-dimensional (2D) networks in which the droplets are connected through single lipid bilayers. Here we assemble lipid-coated droplets in robust, freestanding 3D geometries: for example, a 14-droplet pyramidal assembly. The networks are designed, and each droplet is placed in a designated position. When protein pores are inserted in the bilayers between specific constituent droplets, electrical and chemical communication pathways are generated. We further describe an improved means to construct 3D droplet networks with defined organizations by the manipulation of aqueous droplets containing encapsulated magnetic beads. The droplets are maneuvered in a magnetic field to form simple construction modules, which are then used to form larger 2D and 3D structures including a 10-droplet pyramid. A methodology to construct freestanding, functional 3D droplet networks is an important step toward the programmed and automated manufacture of synthetic minimal tissues.

Ullmann-type coupling of brominated tetrathienoanthracene on copper and silver

NASA Astrophysics Data System (ADS)

Gutzler, Rico; Cardenas, Luis; Lipton-Duffin, Josh; El Garah, Mohamed; Dinca, Laurentiu E.; Szakacs, Csaba E.; Fu, Chaoying; Gallagher, Mark; Vondráček, Martin; Rybachuk, Maksym; Perepichka, Dmitrii F.; Rosei, Federico

2014-02-01

We report the synthesis of extended two-dimensional organic networks on Cu(111), Ag(111), Cu(110), and Ag(110) from thiophene-based molecules. A combination of scanning tunnelling microscopy and X-ray photoemission spectroscopy yields insight into the reaction pathways from single molecules towards the formation of two-dimensional organometallic and polymeric structures via Ullmann reaction dehalogenation and C-C coupling. The thermal stability of the molecular networks is probed by annealing at elevated temperatures of up to 500 °C. On Cu(111) only organometallic structures are formed, while on Ag(111) both organometallic and covalent polymeric networks were found to coexist. The ratio between organometallic and covalent bonds could be controlled by means of the annealing temperature. The thiophene moieties start degrading at 200 °C on the copper surface, whereas on silver the degradation process becomes significant only at 400 °C. Our work reveals how the interplay of a specific surface type and temperature steers the formation of organometallic and polymeric networks and describes how these factors influence the structural integrity of two-dimensional organic networks.We report the synthesis of extended two-dimensional organic networks on Cu(111), Ag(111), Cu(110), and Ag(110) from thiophene-based molecules. A combination of scanning tunnelling microscopy and X-ray photoemission spectroscopy yields insight into the reaction pathways from single molecules towards the formation of two-dimensional organometallic and polymeric structures via Ullmann reaction dehalogenation and C-C coupling. The thermal stability of the molecular networks is probed by annealing at elevated temperatures of up to 500 °C. On Cu(111) only organometallic structures are formed, while on Ag(111) both organometallic and covalent polymeric networks were found to coexist. The ratio between organometallic and covalent bonds could be controlled by means of the annealing temperature. The thiophene moieties start degrading at 200 °C on the copper surface, whereas on silver the degradation process becomes significant only at 400 °C. Our work reveals how the interplay of a specific surface type and temperature steers the formation of organometallic and polymeric networks and describes how these factors influence the structural integrity of two-dimensional organic networks. Electronic supplementary information (ESI) available: Additional STM data and DFT results. See DOI: 10.1039/c3nr05710k

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

The composite hydrogels of polyvinyl alcohol-gellan gum-Ca(2+) with improved network structure and mechanical property.

PubMed

Wang, Fei; Wen, Ying; Bai, Tongchun

2016-12-01

The composite hydrogels of polyvinyl alcohol (PVA) and gellan gum (GG) are of interesting in the biomaterials application. To improve the structure and mechanical property, in this work, Ca(2+) ion was introduced to crosslink the polymer chain, and the PVA-GG-Ca(2+) hydrogel was formed. By analyzing its structure, mechanical properties, swelling and dehydration kinetics, the effect of molecular interaction on hydrogel structure and properties have been observed. Our result indicates that, as GG is added to hydrogel network, the role of Ca(2+) ion is stand out, it reorganizes the network structure, enhances the mechanical properties, and strengthens the electrolytic and hydrogen bonding interactions in PVA-GG-Ca(2+) hydrogels. These observations will benefit the development of hydrogels in biomaterials application. Copyright © 2016. Published by Elsevier B.V.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakai, Osamu, E-mail: sakai.o@e.usp.ac.jp; Nobuto, Kyosuke; Miyagi, Shigeyuki

Chemical reactions of molecular gases like methane are so complicated that a chart of decomposed and/or synthesized species originating from molecules in plasma resembles a weblike network in which we write down species and reactions among them. Here we consider properties of the network structures of chemical reactions in methane plasmas. In the network, atoms/molecules/radical species are assumed to form nodes and chemical reactions correspond to directed edges in the terminology of graph theory. Investigation of the centrality index reveals importance of CH{sub 3} in the global chemical reaction, and difference of an index for each radical species between casesmore » with and without electrons clarifies that the electrons are at an influential position to tighten the network structure.« less

Insensitive dependence of delay-induced oscillation death on complex networks

NASA Astrophysics Data System (ADS)

Zou, Wei; Zheng, Xing; Zhan, Meng

2011-06-01

Oscillation death (also called amplitude death), a phenomenon of coupling induced stabilization of an unstable equilibrium, is studied for an arbitrary symmetric complex network with delay-coupled oscillators, and the critical conditions for its linear stability are explicitly obtained. All cases including one oscillator, a pair of oscillators, regular oscillator networks, and complex oscillator networks with delay feedback coupling, can be treated in a unified form. For an arbitrary symmetric network, we find that the corresponding smallest eigenvalue of the Laplacian λN (0 >λN ≥ -1) completely determines the death island, and as λN is located within the insensitive parameter region for nearly all complex networks, the death island keeps nearly the largest and does not sensitively depend on the complex network structures. This insensitivity effect has been tested for many typical complex networks including Watts-Strogatz (WS) and Newman-Watts (NW) small world networks, general scale-free (SF) networks, Erdos-Renyi (ER) random networks, geographical networks, and networks with community structures and is expected to be helpful for our understanding of dynamics on complex networks.

Real-Time Dynamics of Emerging Actin Networks in Cell-Mimicking Compartments

PubMed Central

Deshpande, Siddharth; Pfohl, Thomas

2015-01-01

Understanding the cytoskeletal functionality and its relation to other cellular components and properties is a prominent question in biophysics. The dynamics of actin cytoskeleton and its polymorphic nature are indispensable for the proper functioning of living cells. Actin bundles are involved in cell motility, environmental exploration, intracellular transport and mechanical stability. Though the viscoelastic properties of actin-based structures have been extensively probed, the underlying microstructure dynamics, especially their disassembly, is not fully understood. In this article, we explore the rich dynamics and emergent properties exhibited by actin bundles within flow-free confinements using a microfluidic set-up and epifluorescence microscopy. After forming entangled actin filaments within cell-sized quasi two-dimensional confinements, we induce their bundling using three different fundamental mechanisms: counterion condensation, depletion interactions and specific protein-protein interactions. Intriguingly, long actin filaments form emerging networks of actin bundles via percolation leading to remarkable properties such as stress generation and spindle-like intermediate structures. Simultaneous sharing of filaments in different links of the network is an important parameter, as short filaments do not form networks but segregated clusters of bundles instead. We encounter a hierarchical process of bundling and its subsequent disassembly. Additionally, our study suggests that such percolated networks are likely to exist within living cells in a dynamic fashion. These observations render a perspective about differential cytoskeletal responses towards numerous stimuli. PMID:25785606

The perceived causal structures of smoking: Smoker and non-smoker comparisons

PubMed Central

Lydon, David M; Howard, Matthew C; Wilson, Stephen J; Geier, Charles F

2015-01-01

Despite the detrimental impact of smoking on health, its prevalence remains high. Empirical research has provided insight into the many causes and effects of smoking, yet lay perceptions of smoking remain relatively understudied. The current study used a form of network analysis to gain insight into the causal attributions for smoking of both smoking and non-smoking college students. The analyses resulted in highly endorsed, complex network diagrams that conveyed the perceived causal structures of smoking. Differences in smoker and non-smoker networks emerged with smokers attributing less negative consequences to smoking behaviors. Implications for intervention are discussed. PMID:25690755

A (very) Simple Model for the Aspect Ratio of High-Order River Basins

NASA Astrophysics Data System (ADS)

Shelef, E.

2017-12-01

The structure of river networks dictates the distribution of elevation, water, and sediments across Earth's surface. Despite its intricate shape, the structure of high-order river networks displays some surprising regularities such as the consistent aspect ratio (i.e., basin's width over length) of river basins along linear mountain fronts. This ratio controls the spacing between high-order channels as well as the spacing between the depositional bodies they form. It is generally independent of tectonic and climatic conditions and is often attributed to the initial topography over which the network was formed. This study shows that a simple, cross-like channel model explains this ratio via a requirement for equal elevation gain between the outlets and drainage-divides of adjacent channels at topographic steady state. This model also explains the dependence of aspect ratio on channel concavity and the location of the widest point on a drainage divide.

Effects of Nb Modification and Cooling Rate on the Microstructure in an Ultrahigh Carbon Steel

NASA Astrophysics Data System (ADS)

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N.

2018-04-01

In this study, two different melting methods were used to investigate effects of Nb modification on microstructure in ultrahigh carbon steel (UHCS). Nb-free and Nb-modified UHCS samples were produced by melting and resolidifying an industrially produced base UHCS with and without addition of Nb powder. Microstructure was characterized using scanning electron microscopy, X-ray diffraction, and electron dispersive spectroscopy. Equilibrium computations of phase fractions and compositions were utilized to help describe microstructural changes caused by the Nb additions. Nb combined with C to form NbC structures before and during austenite solidification, reducing the effective amount of carbon available for the other phases. Cementite network spacing in the Nb-free samples was controlled by the cooling rate during solidification (faster cooling led to a more refined network). Network spacing in the Nb-modified UHCS could be enlarged by NbC structures that formed cooperatively with austenite.

Reconfigurable origami-inspired acoustic waveguides

PubMed Central

Babaee, Sahab; Overvelde, Johannes T. B.; Chen, Elizabeth R.; Tournat, Vincent; Bertoldi, Katia

2016-01-01

We combine numerical simulations and experiments to design a new class of reconfigurable waveguides based on three-dimensional origami-inspired metamaterials. Our strategy builds on the fact that the rigid plates and hinges forming these structures define networks of tubes that can be easily reconfigured. As such, they provide an ideal platform to actively control and redirect the propagation of sound. We design reconfigurable systems that, depending on the externally applied deformation, can act as networks of waveguides oriented along one, two, or three preferential directions. Moreover, we demonstrate that the capability of the structure to guide and radiate acoustic energy along predefined directions can be easily switched on and off, as the networks of tubes are reversibly formed and disrupted. The proposed designs expand the ability of existing acoustic metamaterials and exploit complex waveguiding to enhance control over propagation and radiation of acoustic energy, opening avenues for the design of a new class of tunable acoustic functional systems. PMID:28138527

Effects of Nb Modification and Cooling Rate on the Microstructure in an Ultrahigh Carbon Steel

NASA Astrophysics Data System (ADS)

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N.

2018-06-01

In this study, two different melting methods were used to investigate effects of Nb modification on microstructure in ultrahigh carbon steel (UHCS). Nb-free and Nb-modified UHCS samples were produced by melting and resolidifying an industrially produced base UHCS with and without addition of Nb powder. Microstructure was characterized using scanning electron microscopy, X-ray diffraction, and electron dispersive spectroscopy. Equilibrium computations of phase fractions and compositions were utilized to help describe microstructural changes caused by the Nb additions. Nb combined with C to form NbC structures before and during austenite solidification, reducing the effective amount of carbon available for the other phases. Cementite network spacing in the Nb-free samples was controlled by the cooling rate during solidification (faster cooling led to a more refined network). Network spacing in the Nb-modified UHCS could be enlarged by NbC structures that formed cooperatively with austenite.

Structure of alkali tellurite glasses from neutron diffraction and molecular orbital calculations

NASA Astrophysics Data System (ADS)

Niida, Haruki; Uchino, Takashi; Jin, Jisun; Kim, Sae-Hoon; Fukunaga, Toshiharu; Yoko, Toshinobu

2001-01-01

The structure of pure TeO2 and alkali tellurite glasses has been examined by neutron diffraction and ab initio molecular orbital methods. The experimental radial distribution functions along with the calculated results have demonstrated that the basic structural units in tellurite glasses change from highly strained TeO4 trigonal bipyramids to more regular TeO3 trigonal pyramids with increasing alkali content. It has also been shown that the TeO3 trigonal pyramids do not exist in the form of isolated units in the glass network but interact with each other to form intertrigonal Te⋯O linkages. The present results suggest that nonbridging oxygen (NBO) atoms in tellurite glasses do not exist in their "pure" form; that is, all the NBO atoms in TeO3 trigonal bipyramids will interact with the first- and/or second-neighbor Te atoms, resulting in the three-dimensional continuous random network even in tellurite glasses with over 30 mol % of alkali oxides.

Power and Networks in Worldwide Knowledge Coordination: The Case of Global Science

ERIC Educational Resources Information Center

King, Roger

2011-01-01

The article considers the global governance of knowledge systems, exploring concepts of power, networks, standards (defined as normative practices), and structuration. The focus is on science as a form of predominantly private global governance, particularly the self-regulatory and collaborative processes stretching across time and space. These…

A mixing evolution model for bidirectional microblog user networks

NASA Astrophysics Data System (ADS)

Yuan, Wei-Guo; Liu, Yun

2015-08-01

Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.

Visual analysis and exploration of complex corporate shareholder networks

NASA Astrophysics Data System (ADS)

Tekušová, Tatiana; Kohlhammer, Jörn

2008-01-01

The analysis of large corporate shareholder network structures is an important task in corporate governance, in financing, and in financial investment domains. In a modern economy, large structures of cross-corporation, cross-border shareholder relationships exist, forming complex networks. These networks are often difficult to analyze with traditional approaches. An efficient visualization of the networks helps to reveal the interdependent shareholding formations and the controlling patterns. In this paper, we propose an effective visualization tool that supports the financial analyst in understanding complex shareholding networks. We develop an interactive visual analysis system by combining state-of-the-art visualization technologies with economic analysis methods. Our system is capable to reveal patterns in large corporate shareholder networks, allows the visual identification of the ultimate shareholders, and supports the visual analysis of integrated cash flow and control rights. We apply our system on an extensive real-world database of shareholder relationships, showing its usefulness for effective visual analysis.

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Construction of microscale structures in enclosed microfluidic networks by using a magnetic beads based method.

PubMed

Wang, Zhenyu; Zhang, Xiaojuan; Yang, Jun; Yang, Zhong; Wan, Xiaoping; Hu, Ning; Zheng, Xiaolin

2013-08-20

A large number of microscale structures have been used to elaborate flowing control or complex biological and chemical reaction on microfluidic chips. However, it is still inconvenient to fabricate microstructures with different heights (or depths) on the same substrate. These kinds of microstructures can be fabricated by using the photolithography and wet-etching method step by step, but involves time-consuming design and fabrication process, as well as complicated alignment of different masters. In addition, few existing methods can be used to perform fabrication within enclosed microfluidic networks. It is also difficult to change or remove existing microstructures within these networks. In this study, a magnetic-beads-based approach is presented to build microstructures in enclosed microfluidic networks. Electromagnetic field generated by microfabricated conducting wires (coils) is used to manipulate and trap magnetic beads on the bottom surface of a microchannel. These trapped beads are accumulated to form a microscale pile with desired shape, which can adjust liquid flow, dock cells, modify surface, and do some other things as those fabricated microstructures. Once the electromagnetic field is changed, trapped beads may form new shapes or be removed by a liquid flow. Besides being used in microfabrication, this magnetic-beads-based method can be used for novel microfluidic manipulation. It has been validated by forming microscale dam structure for cell docking and modified surface for cell patterning, as well as guiding the growth of neurons. Copyright © 2013 Elsevier B.V. All rights reserved.

Computational Modeling of Allosteric Regulation in the Hsp90 Chaperones: A Statistical Ensemble Analysis of Protein Structure Networks and Allosteric Communications

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2014-01-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. PMID:24922508

Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications.

PubMed

Blacklock, Kristin; Verkhivker, Gennady M

2014-06-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.

Network formation: neighborhood structures, establishment costs, and distributed learning.

PubMed

Chasparis, Georgios C; Shamma, Jeff S

2013-12-01

We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games.

Tertiary network in mammalian mitochondrial tRNAAsp revealed by solution probing and phylogeny

PubMed Central

Messmer, Marie; Pütz, Joern; Suzuki, Takeo; Suzuki, Tsutomu; Sauter, Claude; Sissler, Marie; Catherine, Florentz

2009-01-01

Primary and secondary structures of mammalian mitochondrial (mt) tRNAs are divergent from canonical tRNA structures due to highly skewed nucleotide content and large size variability of D- and T-loops. The nonconservation of nucleotides involved in the expected network of tertiary interactions calls into question the rules governing a functional L-shaped three-dimensional (3D) structure. Here, we report the solution structure of human mt-tRNAAsp in its native post-transcriptionally modified form and as an in vitro transcript. Probing performed with nuclease S1, ribonuclease V1, dimethylsulfate, diethylpyrocarbonate and lead, revealed several secondary structures for the in vitro transcribed mt-tRNAAsp including predominantly the cloverleaf. On the contrary, the native tRNAAsp folds into a single cloverleaf structure, highlighting the contribution of the four newly identified post-transcriptional modifications to correct folding. Reactivities of nucleotides and phosphodiester bonds in the native tRNA favor existence of a full set of six classical tertiary interactions between the D-domain and the variable region, forming the core of the 3D structure. Reactivities of D- and T-loop nucleotides support an absence of interactions between these domains. According to multiple sequence alignments and search for conservation of Leontis–Westhof interactions, the tertiary network core building rules apply to all tRNAAsp from mammalian mitochondria. PMID:19767615

Crystal Structure Prediction via Deep Learning.

PubMed

Ryan, Kevin; Lengyel, Jeff; Shatruk, Michael

2018-06-06

We demonstrate the application of deep neural networks as a machine-learning tool for the analysis of a large collection of crystallographic data contained in the crystal structure repositories. Using input data in the form of multi-perspective atomic fingerprints, which describe coordination topology around unique crystallographic sites, we show that the neural-network model can be trained to effectively distinguish chemical elements based on the topology of their crystallographic environment. The model also identifies structurally similar atomic sites in the entire dataset of ~50000 crystal structures, essentially uncovering trends that reflect the periodic table of elements. The trained model was used to analyze templates derived from the known binary and ternary crystal structures in order to predict the likelihood to form new compounds that could be generated by placing elements into these structural templates in combinatorial fashion. Statistical analysis of predictive performance of the neural-network model, which was applied to a test set of structures never seen by the model during training, indicates its ability to predict known elemental compositions with a high likelihood of success. In ~30% of cases, the known compositions were found among top-10 most likely candidates proposed by the model. These results suggest that the approach developed in this work can be used to effectively guide the synthetic efforts in the discovery of new materials, especially in the case of systems composed of 3 or more chemical elements.

Cycle oxidation behavior and anti-oxidation mechanism of hot-dipped aluminum coating on TiBw/Ti6Al4V composites with network microstructure.

PubMed

Li, X T; Huang, L J; Wei, S L; An, Q; Cui, X P; Geng, L

2018-04-10

Controlled and compacted TiAl 3 coating was successfully fabricated on the network structured TiBw/Ti6Al4V composites by hot-dipping aluminum and subsequent interdiffusion treatment. The network structure of the composites was inherited to the TiAl 3 coating, which effectively reduces the thermal stress and avoids the cracks appeared in the coating. Moreover, TiB reinforcements could pin the TiAl 3 coating which can effectively improve the bonding strength between the coating and composite substrate. The cycle oxidation behavior of the network structured coating on 873 K, 973 K and 1073 K for 100 h were investigated. The results showed the coating can remarkably improve the high temperature oxidation resistance of the TiBw/Ti6Al4V composites. The network structure was also inherited to the Al 2 O 3 oxide scale, which effectively decreases the tendency of cracking even spalling about the oxide scale. Certainly, no crack was observed in the coating after long-term oxidation due to the division effect of network structured coating and pinning effect of TiB reinforcements. Interfacial reaction between the coating and the composite substrate occurred and a bilayer structure of TiAl/TiAl 2 formed next to the substrate after oxidation at 973 K and 1073 K. The anti-oxidation mechanism of the network structured coating was also discussed.

Research on key technology of planning and design for AC/DC hybrid distribution network

NASA Astrophysics Data System (ADS)

Shen, Yu; Wu, Guilian; Zheng, Huan; Deng, Junpeng; Shi, Pengjia

2018-04-01

With the increasing demand of DC generation and DC load, the development of DC technology, AC and DC distribution network integrating will become an important form of future distribution network. In this paper, the key technology of planning and design for AC/DC hybrid distribution network is proposed, including the selection of AC and DC voltage series, the design of typical grid structure and the comprehensive evaluation method of planning scheme. The research results provide some ideas and directions for the future development of AC/DC hybrid distribution network.

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

Structural and Functional Alterations in Neocortical Circuits after Mild Traumatic Brain Injury

NASA Astrophysics Data System (ADS)

Vascak, Michal

National concern over traumatic brain injury (TBI) is growing rapidly. Recent focus is on mild TBI (mTBI), which is the most prevalent injury level in both civilian and military demographics. A preeminent sequelae of mTBI is cognitive network disruption. Advanced neuroimaging of mTBI victims supports this premise, revealing alterations in activation and structure-function of excitatory and inhibitory neuronal systems, which are essential for network processing. However, clinical neuroimaging cannot resolve the cellular and molecular substrates underlying such changes. Therefore, to understand the full scope of mTBI-induced alterations it is necessary to study cortical networks on the microscopic level, where neurons form local networks that are the fundamental computational modules supporting cognition. Recently, in a well-controlled animal model of mTBI, we demonstrated in the excitatory pyramidal neuron system, isolated diffuse axonal injury (DAI), in concert with electrophysiological abnormalities in nearby intact (non-DAI) neurons. These findings were consistent with altered axon initial segment (AIS) intrinsic activity functionally associated with structural plasticity, and/or disturbances in extrinsic systems related to parvalbumin (PV)-expressing interneurons that form GABAergic synapses along the pyramidal neuron perisomatic/AIS domains. The AIS and perisomatic GABAergic synapses are domains critical for regulating neuronal activity and E-I balance. In this dissertation, we focus on the neocortical excitatory pyramidal neuron/inhibitory PV+ interneuron local network following mTBI. Our central hypothesis is that mTBI disrupts neuronal network structure and function causing imbalance of excitatory and inhibitory systems. To address this hypothesis we exploited transgenic and cre/lox mouse models of mTBI, employing approaches that couple state-of-the-art bioimaging with electrophysiology to determine the structuralfunctional alterations of excitatory and inhibitory systems in the neocortex.

Road networks as collections of minimum cost paths

NASA Astrophysics Data System (ADS)

Wegner, Jan Dirk; Montoya-Zegarra, Javier Alexander; Schindler, Konrad

2015-10-01

We present a probabilistic representation of network structures in images. Our target application is the extraction of urban roads from aerial images. Roads appear as thin, elongated, partially curved structures forming a loopy graph, and this complex layout requires a prior that goes beyond standard smoothness and co-occurrence assumptions. In the proposed model the network is represented as a union of 1D paths connecting distant (super-)pixels. A large set of putative candidate paths is constructed in such a way that they include the true network as much as possible, by searching for minimum cost paths in the foreground (road) likelihood. Selecting the optimal subset of candidate paths is posed as MAP inference in a higher-order conditional random field. Each path forms a higher-order clique with a type of clique potential, which attracts the member nodes of cliques with high cumulative road evidence to the foreground label. That formulation induces a robust PN -Potts model, for which a global MAP solution can be found efficiently with graph cuts. Experiments with two road data sets show that the proposed model significantly improves per-pixel accuracies as well as the overall topological network quality with respect to several baselines.

Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

NASA Astrophysics Data System (ADS)

Poirot, Olivier; Timsit, Youri

2016-05-01

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing.

Social Networks and High Healthcare Utilization: Building Resilience Through Analysis

DTIC Science & Technology

2016-09-01

of Social Network Analysis Patients Developing targeted intervention programs based on the individual’s needs may potentially help improve the...network structure is found in the patterns of interconnection that develop between nodes. It is this linking through common nodes, “the AB link shares...transitivity is responsible for the clustering of nodes that form “communities” of people based on geography, common interests, or other group

What Can Graph Theory Tell Us About Word Learning and Lexical Retrieval?

PubMed Central

Vitevitch, Michael S.

2008-01-01

Purpose Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of phonological word-forms. Method Pajek, a program for large network analysis and visualization (V. Batagelj & A. Mvrar, 1998), was used to examine several characteristics of a network derived from a computerized database of the adult lexicon. Nodes in the network represented words, and a link connected two nodes if the words were phonological neighbors. Results The average path length and clustering coefficient suggest that the phonological network exhibits small-world characteristics. The degree distribution was fit better by an exponential rather than a power-law function. Finally, the network exhibited assortative mixing by degree. Some of these structural characteristics were also found in graphs that were formed by 2 simple stochastic processes suggesting that similar processes might influence the development of the lexicon. Conclusions The graph theoretic perspective may provide novel insights about the mental lexicon and lead to future studies that help us better understand language development and processing. PMID:18367686

Effect of pH on the rheological and structural properties of gels of water-washed chicken-breast muscle at physiological ionic strength.

PubMed

Feng, Y; Hultin, H O

2001-08-01

Adjustment of pH from 6.4 to neutrality improved gelling ability and water-holding capacity of twice water-washed, minced chicken-breast muscle significantly at physiological ionic strength, at which the majority of the myofibrillar proteins, including myosin, are not soluble. A strain value of 2.2 was obtained at neutral pH. Myofibrils were the main components of the gel network at both pH 6.4 and 7.0; however, the myofibrillar distribution varied with the pH value. At pH 6.4, myofibrils formed a network of localized aggregates leaving large voids between, whereas at neutral pH, an evenly distributed network of myofibrils was formed. In addition, at neutral pH, a network of fine strands was found within the network of myofibrils. The network was much less developed at pH 6.4. The thin and thick filaments within each myofibrillar structure were disorganized at both pH values. The intramyofibrillar spaces were larger at neutral pH than at pH 6.4. It was proposed that adjustment of pH to neutrality increased electrostatic repulsion leading to a more even distribution of the myofibrillar proteins, a key factor responsible for the improved gel strength and water-holding capacity.

Structure and properties of semi-interpenetrating network hydrogel based on starch.

PubMed

Zhu, Baodong; Ma, Dongzhuo; Wang, Jian; Zhang, Shuang

2015-11-20

Starch-g-P(acrylic acid-co-acrylamide)/PVA semi-interpenetrating network (semi-IPN) hydrogels were prepared by aqueous solution polymerization method. Starch grafting copolymerization reaction, semi-IPN structure and crystal morphology were characterized by Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The PVA in the form of partial crystallization distributing in the gel matrix uniformly were observed by Field emission scanning electron microscope (FESEM). The space network structure, finer microstructure and pore size in the interior of hydrogel were presented by biomicroscope. The results demonstrated that absorption ratio of water and salt generated different degree changes with the effect of PVA. In addition, the mechanical strength of hydrogel was improved. Copyright © 2015 Elsevier Ltd. All rights reserved.

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data.

PubMed

Cho, Kwang-Hyun; Choo, Sang-Mok; Wellstead, Peter; Wolkenhauer, Olaf

2005-08-15

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.

Social capital calculations in economic systems: Experimental study

NASA Astrophysics Data System (ADS)

Chepurov, E. G.; Berg, D. B.; Zvereva, O. M.; Nazarova, Yu. Yu.; Chekmarev, I. V.

2017-11-01

The paper describes the social capital study for a system where actors are engaged in an economic activity. The focus is on the analysis of communications structural parameters (transactions) between the actors. Comparison between transaction network graph structure and the structure of a random Bernoulli graph of the same dimension and density allows revealing specific structural features of the economic system under study. Structural analysis is based on SNA-methodology (SNA - Social Network Analysis). It is shown that structural parameter values of the graph formed by agent relationship links may well characterize different aspects of the social capital structure. The research advocates that it is useful to distinguish the difference between each agent social capital and the whole system social capital.

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Novel self-sensing carbon nanotube-based composites for rehabilitation of structural steel members

NASA Astrophysics Data System (ADS)

Ahmed, Shafique; Doshi, Sagar; Schumacher, Thomas; Thostenson, Erik T.; McConnell, Jennifer

2016-02-01

Fatigue and fracture are among the most critical forms of damage in metal structures. Fatigue damage can initiate from microscopic defects (e.g., surface scratches, voids in welds, and internal defects) and initiate a crack. Under cyclic loading, these cracks can grow and reach a critical level to trigger fracture of the member which leads to compromised structural integrity and, in some cases, catastrophic failure of the entire structure. In our research, we are investigating a solution using carbon nanotube-based sensing composites, which have the potential to simultaneously rehabilitate and monitor fatigue-cracked structural members. These composites consist of a fiber-reinforced polymer (FRP) layer and a carbon nanotube-based sensing layer, which are integrated to form a novel structural self-sensing material. The sensing layer is composed of a non-woven aramid fabric that is coated with carbon nanotubes (CNT) to form an electrically conductive network that is extremely sensitive to detecting deformation as well as damage accumulation via changes in the resistance of the CNT network. In this paper, we introduce the sensing concept, describe the manufacturing of a model sensing prototype, and discuss a set of small-scale laboratory experiments to examine the load-carrying capacity and damage sensing response.

Extracellular matrix structure.

PubMed

Theocharis, Achilleas D; Skandalis, Spyros S; Gialeli, Chrysostomi; Karamanos, Nikos K

2016-02-01

Extracellular matrix (ECM) is a non-cellular three-dimensional macromolecular network composed of collagens, proteoglycans/glycosaminoglycans, elastin, fibronectin, laminins, and several other glycoproteins. Matrix components bind each other as well as cell adhesion receptors forming a complex network into which cells reside in all tissues and organs. Cell surface receptors transduce signals into cells from ECM, which regulate diverse cellular functions, such as survival, growth, migration, and differentiation, and are vital for maintaining normal homeostasis. ECM is a highly dynamic structural network that continuously undergoes remodeling mediated by several matrix-degrading enzymes during normal and pathological conditions. Deregulation of ECM composition and structure is associated with the development and progression of several pathologic conditions. This article emphasizes in the complex ECM structure as to provide a better understanding of its dynamic structural and functional multipotency. Where relevant, the implication of the various families of ECM macromolecules in health and disease is also presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Self-organization in multilayer network with adaptation mechanisms based on competition

NASA Astrophysics Data System (ADS)

Pitsik, Elena N.; Makarov, Vladimir V.; Nedaivozov, Vladimir O.; Kirsanov, Daniil V.; Goremyko, Mikhail V.

2018-04-01

The paper considers the phenomena of competition in multiplex network whose structure evolves corresponding to dynamics of it's elements, forming closed loop of self-learning with the aim to reach the optimal topology. Numerical analysis of proposed model shows that it is possible to obtain scale-invariant structures for corresponding parameters as well as the structures with homogeneous distribution of connections in the layers. Revealed phenomena emerges as the consequence of the self-organization processes related to structure-dynamical selflearning based on homeostasis and homophily, as well as the result of the competition between the network's layers for optimal topology. It was shown that in the mode of partial and cluster synchronization the network reaches scale-free topology of complex nature that is different from layer to layer. However, in the mode of global synchronization the homogeneous topologies on all layer of the network are observed. This phenomenon is tightly connected with the competitive processes that represent themselves as the natural mechanism of reaching the optimal topology of the links in variety of real-world systems.

Strategic tradeoffs in competitor dynamics on adaptive networks.

PubMed

Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

2017-08-08

Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.

Stress reduction in phase-separated, cross-linked networks: influence of phase structure and kinetics of reaction

PubMed Central

Szczepanski, Caroline R.; Stansbury, Jeffrey W.

2014-01-01

A mechanism for polymerization shrinkage and stress reduction was developed for heterogeneous networks formed via ambient, photo-initiated polymerization-induced phase separation (PIPS). The material system used consists of a bulk homopolymer matrix of triethylene glycol dimethacrylate (TEGDMA) modified with one of three non-reactive, linear prepolymers (poly-methyl, ethyl and butyl methacrylate). At higher prepolymer loading levels (10–20 wt%) an enhanced reduction in both shrinkage and polymerization stress is observed. The onset of gelation in these materials is delayed to a higher degree of methacrylate conversion (~15–25%), providing more time for phase structure evolution by thermodynamically driven monomer diffusion between immiscible phases prior to network macro-gelation. The resulting phase structure was probed by introducing a fluorescently tagged prepolymer into the matrix. The phase structure evolves from a dispersion of prepolymer at low loading levels to a fully co-continuous heterogeneous network at higher loadings. The bulk modulus in phase separated networks is equivalent or greater than that of poly(TEGDMA), despite a reduced polymerization rate and cross-link density in the prepolymer-rich domains. PMID:25418999

Financial networks based on Granger causality: A case study

NASA Astrophysics Data System (ADS)

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-09-01

Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among the international stock indexes and portray the links of the resulting networks, by the presence of direct couplings between variables exploiting all available information. However, their differences are assessed due to the presence of nonlinearity. The weighted networks formed with respect to the causality measures are transformed to binary ones using a significance test. The financial networks are formed on sliding windows in order to examine the network characteristics and trace changes in the connectivity structure. Subsequently, two statistical network quantities are calculated; the average degree and the average shortest path length. The empirical findings reveal interesting time-varying properties of the constructed network, which are clearly dependent on the nature of the financial cycle.

Leveraging disjoint communities for detecting overlapping community structure

NASA Astrophysics Data System (ADS)

Chakraborty, Tanmoy

2015-05-01

Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overlapping communities from the network. In this paper, we present PVOC (Permanence based Vertex-replication algorithm for Overlapping Community detection), a two-stage framework to detect overlapping community structure. We build on a novel observation that non-overlapping community structure detected by a standard disjoint community detection algorithm from a network has high resemblance with its actual overlapping community structure, except the overlapping part. Based on this observation, we posit that there is perhaps no need of building yet another overlapping community finding algorithm; but one can efficiently manipulate the output of any existing disjoint community finding algorithm to obtain the required overlapping structure. We propose a new post-processing technique that by combining with any existing disjoint community detection algorithm, can suitably process each vertex using a new vertex-based metric, called permanence, and thereby finds out overlapping candidates with their community memberships. Experimental results on both synthetic and large real-world networks show that PVOC significantly outperforms six state-of-the-art overlapping community detection algorithms in terms of high similarity of the output with the ground-truth structure. Thus our framework not only finds meaningful overlapping communities from the network, but also allows us to put an end to the constant effort of building yet another overlapping community detection algorithm.

Seeking Social Capital and Expertise in a Newly-Formed Research Community: A Co-Author Analysis

ERIC Educational Resources Information Center

Forte, Christine E.

2017-01-01

This exploratory study applies social network analysis techniques to existing, publicly available data to understand collaboration patterns within the co-author network of a federally-funded, interdisciplinary research program. The central questions asked: What underlying social capital structures can be determined about a group of researchers…

Bribery games on inter-dependent regular networks

NASA Astrophysics Data System (ADS)

Verma, Prateek; Nandi, Anjan K.; Sengupta, Supratim

2017-02-01

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen’s network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

Bribery games on inter-dependent regular networks

PubMed Central

Verma, Prateek; Nandi, Anjan K.; Sengupta, Supratim

2017-01-01

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen’s network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games. PMID:28205644

Controllable two-scale network architecture and enhanced mechanical properties of (Ti5Si3+TiBw)/Ti6Al4V composites

PubMed Central

Jiao, Y.; Huang, L. J.; Duan, T. B.; Wei, S. L.; Kaveendran, B.; Geng, L.

2016-01-01

Novel Ti6Al4V alloy matrix composites with a controllable two-scale network architecture were successfully fabricated by reaction hot pressing (RHP). TiB whiskers (TiBw) were in-situ synthesized around the Ti6Al4V matrix particles, and formed the first-scale network structure (FSNS). Ti5Si3 needles (Ti5Si3) precipitated in the β phase around the equiaxed α phase, and formed the secondary-scale network structure (SSNS). This resulted in increased deformation compatibility accompanied with enhanced mechanical properties. Apart from the reinforcement distribution and the volume fraction, the ratio between Ti5Si3 and TiBw fraction were controlled. The prepared (Ti5Si3 + TiBw)/Ti6Al4V composites showed higher tensile strength and ductility than the composites with a one-scale microstructure, and superior wear resistance over the Ti6Al4V alloy under dry sliding wear conditions at room temperature. PMID:27622992

Cortical network architecture for context processing in primate brain

PubMed Central

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

2015-01-01

Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

PubMed

Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

2011-02-01

Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

Crystal structure and physicochemical characterization of ambazone monohydrate, anhydrous, and acetate salt solvate.

PubMed

Muresan-Pop, Marieta; Braga, Dario; Pop, Mihaela M; Borodi, Gheorghe; Kacso, Irina; Maini, Lucia

2014-11-01

The crystal structures of the monohydrate and anhydrous forms of ambazone were determined by single-crystal X-ray diffraction (SC-XRD). Ambazone monohydrate is characterized by an infinite three-dimensional network involving the water molecules, whereas anhydrous ambazone forms a two-dimensional network via hydrogen bonds. The reversible transformation between the monohydrate and anhydrous forms of ambazone was evidenced by thermal analysis, temperature-dependent X-ray powder diffraction and accelerated stability at elevated temperature, and relative humidity (RH). Additionally, a novel ambazone acetate salt solvate form was obtained and its nature was elucidated by SC-XRD. Powder dissolution measurements revealed a substantial solubility and dissolution rate improvement of acetate salt solvated form in water and physiological media compared with ambazone forms. Also, the acetate salt solvate displayed good thermal and solution stability but it transformed to the monohydrate on storage at elevated temperature and RH. Our study shows that despite the requirement for controlled storage conditions, the acetate salt solvated form could be an alternative to ambazone when solubility and bioavailability improvement is critical for the clinical efficacy of the drug product. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Effect of dilution in asymmetric recurrent neural networks.

PubMed

Folli, Viola; Gosti, Giorgio; Leonetti, Marco; Ruocco, Giancarlo

2018-04-16

We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measures the fraction of neuron couples that are connected, and the network asymmetry measures to what extent the underlying connectivity matrix is asymmetric. For each given neural network, we study the dynamical evolution of all the different initial conditions, thus characterizing the full dynamical landscape without imposing any learning rule. Because of the deterministic dynamics, each trajectory converges to an attractor, that can be either a fixed point or a limit cycle. These attractors form the set of all the possible limit behaviors of the neural network. For each network we then determine the convergence times, the limit cycles' length, the number of attractors, and the sizes of the attractors' basin. We show that there are two network structures that maximize the number of possible limit behaviors. The first optimal network structure is fully-connected and symmetric. On the contrary, the second optimal network structure is highly sparse and asymmetric. The latter optimal is similar to what observed in different biological neuronal circuits. These observations lead us to hypothesize that independently from any given learning model, an efficient and effective biologic network that stores a number of limit behaviors close to its maximum capacity tends to develop a connectivity structure similar to one of the optimal networks we found. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Network structure control of binary mixed langmuir monolayers of homo-PS and PS-b-P2VP.

PubMed

Wen, Gangyao

2010-03-25

Our recent work showed there existed a composition window for mixed Langmuir monolayers of homopolystyrene (h-PS) and a symmetric diblock copolymer polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP) to form necklace-network structures at the air/water interface. In order to study further the possible mechanism and control the network structure (i.e., surface coverage and nanoaggregate diameter), effects of spreading solution concentration and volume, subphase temperature, and transfer pressure on the network structure were studied by the Langmuir monolayer technique and tapping mode atomic force microscopy. With the increase of transfer pressure, there existed a novel nonlinear behavior for the nanoaggregate diameter first to increase, then to decrease, and finally to increase again, while the surface coverage tended to increase step by step. Moreover, with the elevation of temperature, chain motion between the adjoining nanoaggregates tended to be improved and thus the nanoaggregate diameter tended to be more uniform.

On the assessments of arabinoxylan localization and enzymatic modifications for enhanced protein networking and its structural impact on rye dough and bread.

PubMed

Döring, Clemens; Hussein, Mohamed A; Jekle, Mario; Becker, Thomas

2017-08-15

For rye dough structure, it is hypothesised that the presence of arabinoxylan hinders the proteins from forming a coherent network. This hypothesis was investigated using fluorescent-stained antibodies that bind to the arabinoxylan chains. Image analysis proves that the arabinoxylan surrounds the proteins, negatively affecting protein networking. Further, it is hypothesised that the dosing of xylanase and transglutaminase has a positive impact on rye dough and bread characteristics; the findings in this study evidenced that this increases the protein network by up to 38% accompanied by a higher volume rise of 10.67%, compared to standard rye dough. These outcomes combine a product-oriented and physiochemical design of a recipe, targeting structural and functional relationships, and demonstrate a successful methodology for enhancing rye bread quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

A system of IAC neural networks as the basis for self-organization in a sociological dynamical system simulation.

PubMed

Duong, D V; Reilly, K D

1995-10-01

This sociological simulation uses the ideas of semiotics and symbolic interactionism to demonstrate how an appropriately developed associative memory in the minds of individuals on the microlevel can self-organize into macrolevel dissipative structures of societies such as racial cultural/economic classes, status symbols and fads. The associative memory used is based on an extension of the IAC neural network (the Interactive Activation and Competition network). Several IAC networks act together to form a society by virtue of their human-like properties of intuition and creativity. These properties give them the ability to create and understand signs, which lead to the macrolevel structures of society. This system is implemented in hierarchical object oriented container classes which facilitate change in deep structure. Graphs of general trends and an historical account of a simulation run of this dynamical system are presented.

Uncovering the spatial structure of mobility networks

NASA Astrophysics Data System (ADS)

Louail, Thomas; Lenormand, Maxime; Picornell, Miguel; García Cantú, Oliva; Herranz, Ricardo; Frias-Martinez, Enrique; Ramasco, José J.; Barthelemy, Marc

2015-01-01

The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has relevance for many applications. An important example is seen in origin-destination matrices, which contain the complete information on commuting flows, but are difficult to analyze and compare. We propose here a versatile method, which extracts a coarse-grained signature of mobility networks, under the form of a 2 × 2 matrix that separates the flows into four categories. We apply this method to origin-destination matrices extracted from mobile phone data recorded in 31 Spanish cities. We show that these cities essentially differ by their proportion of two types of flows: integrated (between residential and employment hotspots) and random flows, whose importance increases with city size. Finally, the method allows the determination of categories of networks, and in the mobility case, the classification of cities according to their commuting structure.

Three-dimensional Organization of Layered Apical Cytoskeletal Networks Associated with Mouse Airway Tissue Development

NASA Astrophysics Data System (ADS)

Tateishi, Kazuhiro; Nishida, Tomoki; Inoue, Kanako; Tsukita, Sachiko

2017-03-01

The cytoskeleton is an essential cellular component that enables various sophisticated functions of epithelial cells by forming specialized subcellular compartments. However, the functional and structural roles of cytoskeletons in subcellular compartmentalization are still not fully understood. Here we identified a novel network structure consisting of actin filaments, intermediate filaments, and microtubules directly beneath the apical membrane in mouse airway multiciliated cells and in cultured epithelial cells. Three-dimensional imaging by ultra-high voltage electron microscopy and immunofluorescence revealed that the morphological features of each network depended on the cell type and were spatiotemporally integrated in association with tissue development. Detailed analyses using Odf2 mutant mice, which lack ciliary basal feet and apical microtubules, suggested a novel contribution of the intermediate filaments to coordinated ciliary beating. These findings provide a new perspective for viewing epithelial cell differentiation and tissue morphogenesis through the structure and function of apical cytoskeletal networks.

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

The Role of Hexon Protein as a Molecular Mold in Patterning the Protein IX Organization in Human Adenoviruses.

PubMed

Reddy, Vijay S

2017-09-01

Adenoviruses are respiratory, ocular and enteric pathogens that form complex capsids, which are assembled from seven different structural proteins and composed of several core proteins that closely interact with the packaged dsDNA genome. The recent near-atomic resolution structures revealed that the interlacing continuous hexagonal network formed by the protein IX molecules is conserved among different human adenoviruses (HAdVs), but not in non-HAdVs. In this report, we propose a distinct role for the hexon protein as a "molecular mold" in enabling the formation of such hexagonal protein IX network that has been shown to preserve the stability and infectivity of HAdVs. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Advances in studies on the structure of farmland shelterbelt ecosystem].

PubMed

Li, Chunping; Guan, Wenbin; Fan, Zhiping; Su, Fanxin; Wang, Xilin

2003-11-01

The ecological function of farmland shelterbelt system is determined by its structure. The spatio-temporal structure is a key aspect in related researches, which is very necessary to study the integrity, stability and durability of shelterbelt modules. In this article, the researches on the structure of farmland shelterbelt ecosystem were reviewed from the four scales of tree structure, shelterbelt structure, shelterbelts network and landscape structure. The principles, methods and productions of each scale were summarized, and the prospects were also discussed. Dynamic simulation of tree growth process in shelterbelts could be conducted by the theory of form and quality structure of tree and by fractal graphics, which were helpful to study the mechanism of individual trees and belts based on photosynthetic and transpiration mechanism of individual trees. The mechanism model of shelterbelt porosity should be conducted, so that, the sustainable yield model of shelterbelt management could be established, and the optimized model of shelterbelt networks with multi-special and multi-hierarchical structure could also be formed. Evaluating the reasonability, stability and durability of shelterbelt landscape based on the theories and methods of landscape ecology was an important task in the future studies.

The Network of Global Corporate Control

PubMed Central

Vitali, Stefania; Glattfelder, James B.; Battiston, Stefano

2011-01-01

The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international ownership network, along with the computation of the control held by each global player. We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. This core can be seen as an economic “super-entity” that raises new important issues both for researchers and policy makers. PMID:22046252

Optical Properties and Radiation-Enhanced Evaporation of Nanofluid Fuels Containing Carbon-Based Nanostructures

DTIC Science & Technology

2012-05-29

of the large aspect ratio, the SWCNTs tend to entangle with one another and form network structures. Single and isolated SWCNTs are fewer. The...separated and show much fewer network structures because of entanglement . Also, the length of the MWCNTs is about 100 nm, significantly shorter than that...processed by a self-developed MATLAB code to derive the droplet evaporation rate. A type K thermocouple with a thickness of 76 μm was used to suspend the

Structural and magnetic properties of two- and three-dimensional molecule-based magnets (cat) +[M IIM III(C 2O 4) 3] -

NASA Astrophysics Data System (ADS)

Ovanesyan, Nikolai S.; Shilov, Gena V.; Pyalling, Alex A.; Train, Cyrille; Gredin, Patrick; Gruselle, Michel; Kiss, László F.; Bottyán, László

2004-05-01

We discuss the different structural arrangements of NBu 4[Fe IICr III(C 2O 4) 3] layered compounds in their racemic and enantiomeric forms and related magnetic properties. For [Mn IIFe III(C 2O 4) 3] networks of dimensionalities 2 and 3 Mössbauer spectroscopy was applied to study the Fe III sublattice magnetization. Unusual magnetic relaxation phenomena below TN were observed for both 2D and 3D networks.

Ectoparasites and endoparasites of fish form networks with different structures.

PubMed

Bellay, S; DE Oliveira, E F; Almeida-Neto, M; Mello, M A R; Takemoto, R M; Luque, J L

2015-06-01

Hosts and parasites interact with each other in a variety of ways, and this diversity of interactions is reflected in the networks they form. To test for differences in interaction patterns of ecto- and endoparasites we analysed subnetworks formed by each kind of parasites and their host fish species in fish-parasite networks for 22 localities. We assessed the proportion of parasite species per host species, the relationship between parasite fauna composition and host taxonomy, connectance, nestedness and modularity of each subnetwork (n = 44). Furthermore, we evaluated the similarity in host species composition among modules in ecto- and endoparasite subnetworks. We found several differences between subnetworks of fish ecto- and endoparasites. The association with a higher number of host species observed among endoparasites resulted in higher connectance and nestedness, and lower values of modularity in their subnetworks than in those of ectoparasites. Taxonomically related host species tended to share ecto- or endoparasites with the same interaction intensity, but the species composition of hosts tended to differ between modules formed by ecto- and endoparasites. Our results suggest that different evolutionary and ecological processes are responsible for organizing the networks formed by ecto- and endoparasites and fish.

Structural Bridges through Fold Space.

PubMed

Edwards, Hannah; Deane, Charlotte M

2015-09-01

Several protein structure classification schemes exist that partition the protein universe into structural units called folds. Yet these schemes do not discuss how these units sit relative to each other in a global structure space. In this paper we construct networks that describe such global relationships between folds in the form of structural bridges. We generate these networks using four different structural alignment methods across multiple score thresholds. The networks constructed using the different methods remain a similar distance apart regardless of the probability threshold defining a structural bridge. This suggests that at least some structural bridges are method specific and that any attempt to build a picture of structural space should not be reliant on a single structural superposition method. Despite these differences all representations agree on an organisation of fold space into five principal community structures: all-α, all-β sandwiches, all-β barrels, α/β and α + β. We project estimated fold ages onto the networks and find that not only are the pairings of unconnected folds associated with higher age differences than bridged folds, but this difference increases with the number of networks displaying an edge. We also examine different centrality measures for folds within the networks and how these relate to fold age. While these measures interpret the central core of fold space in varied ways they all identify the disposition of ancestral folds to fall within this core and that of the more recently evolved structures to provide the peripheral landscape. These findings suggest that evolutionary information is encoded along these structural bridges. Finally, we identify four highly central pivotal folds representing dominant topological features which act as key attractors within our landscapes.

Three key residues form a critical contact network in a protein folding transition state

NASA Astrophysics Data System (ADS)

Vendruscolo, Michele; Paci, Emanuele; Dobson, Christopher M.; Karplus, Martin

2001-02-01

Determining how a protein folds is a central problem in structural biology. The rate of folding of many proteins is determined by the transition state, so that a knowledge of its structure is essential for understanding the protein folding reaction. Here we use mutation measurements-which determine the role of individual residues in stabilizing the transition state-as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures that make up the transition state. We apply this approach to the experimental data for the 98-residue protein acylphosphatase, and obtain a transition-state ensemble with the native-state topology and an average root-mean-square deviation of 6Å from the native structure. Although about 20 residues with small positional fluctuations form the structural core of this transition state, the native-like contact network of only three of these residues is sufficient to determine the overall fold of the protein. This result reveals how a nucleation mechanism involving a small number of key residues can lead to folding of a polypeptide chain to its unique native-state structure.

Neural network based chemical structure indexing.

PubMed

Rughooputh, S D; Rughooputh, H C

2001-01-01

Searches on chemical databases are presently dominated by the text-based content of a paper which can be indexed into a keyword searchable form. Such traditional searches can prove to be very time-consuming and discouraging to the less frequent scientist. We report a simple chemical indexing based on the molecular structure alone. The method used is based on a one-to-one correspondence between the chemical structure presented as an image to a neural network and the corresponding binary output. The method is direct and less cumbersome (compared with traditional methods) and proves to be robust, elegant, and very versatile.

Fragmented Romanian sociology: growth and structure of the collaboration network.

PubMed

Hâncean, Marian-Gabriel; Perc, Matjaž; Vlăsceanu, Lazăr

2014-01-01

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common.

Fragmented Romanian Sociology: Growth and Structure of the Collaboration Network

PubMed Central

Hâncean, Marian-Gabriel; Perc, Matjaž; Vlăsceanu, Lazăr

2014-01-01

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common. PMID:25409180

A method for exploring implicit concept relatedness in biomedical knowledge network.

PubMed

Bai, Tian; Gong, Leiguang; Wang, Ye; Wang, Yan; Kulikowski, Casimir A; Huang, Lan

2016-07-19

Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community. In this study, a hybrid biomedical knowledge network is constructed by linking concepts across multiple biomedical ontologies as well as non-structural biomedical knowledge sources. To discover implicit relatedness between concepts in ontologies for which potentially valuable relationships (implicit knowledge) may exist, we developed a Multi-Ontology Relatedness Model (MORM) within the knowledge network, for which a relatedness network (RN) is defined and computed across multiple ontologies using a formal inference mechanism of set-theoretic operations. Semantic constraints are designed and implemented to prune the search space of the relatedness network. Experiments to test examples of several biomedical applications have been carried out, and the evaluation of the results showed an encouraging potential of the proposed approach to biomedical knowledge discovery.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Data Requirements to Assess Department of Defense (DOD) Investments in Law Enforcement in Southwest Asia

DTIC Science & Technology

2011-09-01

form similar organizational structures—loosely-connected webs of small, specialized cells, etc.28 Illicit networks form organizational structures...Activities SIMCI Sistema Integrado de Monitoreo de Cultivos Ilícitos (Integrated Crops Monitoring System) STRIDE System To Retrieve Information from Drug

Causality: Physics and Philosophy

ERIC Educational Resources Information Center

Chatterjee, Atanu

2013-01-01

Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…

Liking and hyperlinking: Community detection in online child sexual exploitation networks.

PubMed

Westlake, Bryce G; Bouchard, Martin

2016-09-01

The online sexual exploitation of children is facilitated by websites that form virtual communities, via hyperlinks, to distribute images, videos, and other material. However, how these communities form, are structured, and evolve over time is unknown. Collected using a custom-designed webcrawler, we begin from known child sexual exploitation (CE) seed websites and follow hyperlinks to connected, related, websites. Using a repeated measure design we analyze 10 networks of 300 + websites each - over 4.8 million unique webpages in total, over a period of 60 weeks. Community detection techniques reveal that CE-related networks were dominated by two large communities hosting varied material -not necessarily matching the seed website. Community stability, over 60 weeks, varied across networks. Reciprocity in hyperlinking between community members was substantially higher than within the full network, however, websites were not more likely to connect to homogeneous-content websites. Copyright © 2016 Elsevier Inc. All rights reserved.

Building a Community of Practice for Researchers: The International Network for Simulation-Based Pediatric Innovation, Research and Education.

PubMed

Cheng, Adam; Auerbach, Marc; Calhoun, Aaron; Mackinnon, Ralph; Chang, Todd P; Nadkarni, Vinay; Hunt, Elizabeth A; Duval-Arnould, Jordan; Peiris, Nicola; Kessler, David

2018-06-01

The scope and breadth of simulation-based research is growing rapidly; however, few mechanisms exist for conducting multicenter, collaborative research. Failure to foster collaborative research efforts is a critical gap that lies in the path of advancing healthcare simulation. The 2017 Research Summit hosted by the Society for Simulation in Healthcare highlighted how simulation-based research networks can produce studies that positively impact the delivery of healthcare. In 2011, the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE) was formed to facilitate multicenter, collaborative simulation-based research with the aim of developing a community of practice for simulation researchers. Since its formation, the network has successfully completed and published numerous collaborative research projects. In this article, we describe INSPIRE's history, structure, and internal processes with the goal of highlighting the community of practice model for other groups seeking to form a simulation-based research network.

[Establishment of sprouting embryoid body model mimicking early embryonic vasculogenesis in human embryo].

PubMed

Jiang, Hua; Feng, You-Ji; Xie, Yi; Han, Jin-Lan; Wang, Zack; Chen, Tong

2008-10-14

To establish a sprouting embryoid body model mimicking early embryonic vasculogenesis in human embryo. Human embryonic stem were (hESCs) were cultured on the mouse embryo fibroblasts and then were induced to differentiate to form three-dimensional EB. The hEBs were cultured in media containing various angiogenesis-related factors: vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), endostatin, angiostatin, and platelet factor (PF)-4 of different concentrations for 3 days to observe the sprouting of the hEBs. 3, 3, 3', 3'-tetramethylindo-carbocyanine perchlorate labeled acetylated low density lipoprotein (Dil-AcLDL) was added onto the hEBs foe 4 h Immunofluorescence assay was used to observe if Dil-AcLDL was absorbed and if CD31 was expressed so as to determine the existence of embryonic endothelial cells in the sprouting structures. The ideal culturing condition was analyzed. The differentiated EBs formed sprouting structures in the collagen I matrix containing VEGF and FGF. The sprouts among individual EBs were able to link to each other and form vascular network-like structures. In the presence of VEGF and FGF, the sprouts branching from the EBs assimilated Dil-AcLDL, expressed CD31 and formed a 3-dimensional cylindrical organization. The concentrations of growth factors ideally stimulating sprouting growth were 100 ng/ml of VEGF and 50 ng/ml of FGF. The networks among the EBs were abolished by the angiostatin, endostatin, and PF4. The sprouting from hEBs accumulates embryonic endothelial cells and the sprouting network-like structures are indeed endothelial in nature. Inducing of sprouting EBs is an ideal model that mimics early embryonic vasculogenesis in humans.

Battery structures, self-organizing structures, and related methods

DOEpatents

Chiang, Yet-Ming; Moorehead, William Douglas

2013-11-19

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling forve on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionicaily conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Battery Structures, self-organizing structures, and related methods

DOEpatents

Chiang, Yet-Ming; Moorehead, William Douglas

2013-11-12

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling force on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionically conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Battery structures, self-organizing structures and related methods

DOEpatents

Chiang, Yet-Ming [Framingham, MA; Moorehead, William Douglas [Virginia Beach, VA

2012-06-26

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling force on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionically conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Battery structures, self-organizing structures and related methods

DOEpatents

Chiang, Yet Ming [Framingham, MA; Moorehead, William Douglas [Virginia Beach, VA; Gozdz, Antoni S [Marlborough, MA; Holman, Richard K [Belmont, MA; Loxley, Andrew [Somerville, MA; Riley, Jr., Gilbert N.; Viola, Michael S [Burlington, MA

2009-08-25

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling force on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionically conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Battery structures, self-organizing structures and related methods

DOEpatents

Chiang, Yet-Ming [Framingham, MA; Moorehead, William D [Virginia Beach, VA; Gozdz, Antoni S [Marlborough, MA; Holman, Richard K [Belmont, MA; Loxley, Andrew L [Roslindale, MA; Riley, Jr., Gilbert N.; Viola, Michael S [Burlington, MA

2012-05-01

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling force on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionically conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Battery structures, self-organizing structures and related methods

DOEpatents

Chiang, Yet-Ming [Framingham, MA; Moorehead, William D [Virginia Beach, VA; Gozdz, Antoni S [Marlborough, MA; Holman, Richard K [Belmont, MA; Loxley, Andrew L [Roslindale, MA; Riley, Jr., Gilbert N.; Viola, Michael S [Burlington, MA

2011-08-02

An energy storage device includes a first electrode comprising a first material and a second electrode comprising a second material, at least a portion of the first and second materials forming an interpenetrating network when dispersed in an electrolyte, the electrolyte, the first material and the second material are selected so that the first and second materials exert a repelling force on each other when combined. An electrochemical device, includes a first electrode in electrical communication with a first current collector; a second electrode in electrical communication with a second current collector; and an ionically conductive medium in ionic contact with said first and second electrodes, wherein at least a portion of the first and second electrodes form an interpenetrating network and wherein at least one of the first and second electrodes comprises an electrode structure providing two or more pathways to its current collector.

Cooperative Tertiary Interaction Network Guides RNA Folding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behrouzi, Reza; Roh, Joon Ho; Kilburn, Duncan

2013-04-08

Noncoding RNAs form unique 3D structures, which perform many regulatory functions. To understand how RNAs fold uniquely despite a small number of tertiary interaction motifs, we mutated the major tertiary interactions in a group I ribozyme by single-base substitutions. The resulting perturbations to the folding energy landscape were measured using SAXS, ribozyme activity, hydroxyl radical footprinting, and native PAGE. Double- and triple-mutant cycles show that most tertiary interactions have a small effect on the stability of the native state. Instead, the formation of core and peripheral structural motifs is cooperatively linked in near-native folding intermediates, and this cooperativity depends onmore » the native helix orientation. The emergence of a cooperative interaction network at an early stage of folding suppresses nonnative structures and guides the search for the native state. We suggest that cooperativity in noncoding RNAs arose from natural selection of architectures conducive to forming a unique, stable fold.« less

Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

PubMed

Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

2017-10-15

Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

Active vision and image/video understanding with decision structures based on the network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2003-08-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

Shear Stress Induced Reorganization of the Keratin Intermediate Filament Network Requires Phosphorylation by Protein Kinase C ζ

PubMed Central

Sivaramakrishnan, Sivaraj; Schneider, Jaime L.; Sitikov, Albert; Goldman, Robert D.

2009-01-01

Keratin intermediate filaments (KIFs) form a fibrous polymer network that helps epithelial cells withstand external mechanical forces. Recently, we established a correlation between the structure of the KIF network and its local mechanical properties in alveolar epithelial cells. Shear stress applied across the cell surface resulted in the structural remodeling of KIF and a substantial increase in the elastic modulus of the network. This study examines the mechanosignaling that regulates the structural remodeling of the KIF network. We report that the shear stress–mediated remodeling of the KIF network is facilitated by a twofold increase in the dynamic exchange rate of KIF subunits, which is regulated in a PKC ζ and 14-3-3–dependent manner. PKC ζ phosphorylates K18pSer33, and this is required for the structural reorganization because the KIF network in A549 cells transfected with a dominant negative PKC ζ, or expressing the K18Ser33Ala mutation, is unchanged. Blocking the shear stress–mediated reorganization results in reduced cellular viability and increased apoptotic levels. These data suggest that shear stress mediates the phosphorylation of K18pSer33, which is required for the reorganization of the KIF network, resulting in changes in mechanical properties of the cell that help maintain the integrity of alveolar epithelial cells. PMID:19357195

Do governance choices matter in health care networks?: an exploratory configuration study of health care networks.

PubMed

Willem, Annick; Gemmel, Paul

2013-06-24

Health care networks are widely used and accepted as an organizational form that enables integrated care as well as dealing with complex matters in health care. However, research on the governance of health care networks lags behind. The research aim of our study is to explore the type and importance of governance structure and governance mechanisms for network effectiveness. The study has a multiple case study design and covers 22 health care networks. Using a configuration view, combinations of network governance and other network characteristics were studied on the level of the network. Based on interview and questionnaire data, network characteristics were identified and patterns in the data looked for. Neither a dominant (or optimal) governance structure or mechanism nor a perfect fit among governance and other characteristics were revealed, but a number of characteristics that need further study might be related to effective networks such as the role of governmental agencies, legitimacy, and relational, hierarchical, and contractual governance mechanisms as complementary factors. Although the results emphasize the situational character of network governance and effectiveness, they give practitioners in the health care sector indications of which factors might be more or less crucial for network effectiveness.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

NASA Astrophysics Data System (ADS)

Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-05-01

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

Cd (II) and holodirected lead (II) 3D-supramolecular coordination polymers based on nicotinic acid: Structure, fluorescence property and photocatalytic activity

NASA Astrophysics Data System (ADS)

Etaiw, Safaa El-din H.; Abd El-Aziz, Dina M.; Marie, Hassan; Ali, Elham

2018-05-01

Two new supramolecular coordination polymers namely {[Cd(NA)2(H2O)]}, SCP 1 and {[Pb(NA)2]}, SCP 2, (NA = nicotinate ligand) were synthesized by self-assembly method and structurally characterized by different analytical and spectroscopic methods. Single-crystal X-ray diffraction showed that SCP 1 extend in three dimensions containing bore structure where the 3D- network is constructed via interweaving zigzag chains. The Cd atom coordinates to (O4N2) atoms forming distorted-octahedral configuration. The structure of SCP 2 extend down the projection of the b-axis creating parallel zigzag 1D-chains connected by μ2-O2 atoms and H-bonds forming a holodirected lead (II) hexagonal bi-pyramid configuration. SCP 2 extend to 3D-network via coordinate and hydrogen bonds. The thermal stability, photoluminescence properties, photocatalytic activity for the degradation of methylene blue dye (MB) under UV-irradiation and sunlight irradiation were also studied.

Resilient networks of ant-plant mutualists in Amazonian forest fragments.

PubMed

Passmore, Heather A; Bruna, Emilio M; Heredia, Sylvia M; Vasconcelos, Heraldo L

2012-01-01

The organization of networks of interacting species, such as plants and animals engaged in mutualisms, strongly influences the ecology and evolution of partner communities. Habitat fragmentation is a globally pervasive form of spatial heterogeneity that could profoundly impact the structure of mutualist networks. This is particularly true for biodiversity-rich tropical ecosystems, where the majority of plant species depend on mutualisms with animals and it is thought that changes in the structure of mutualist networks could lead to cascades of extinctions. We evaluated effects of fragmentation on mutualistic networks by calculating metrics of network structure for ant-plant networks in continuous Amazonian forests with those in forest fragments. We hypothesized that networks in fragments would have fewer species and higher connectance, but equal nestedness and resilience compared to forest networks. Only one of the nine metrics we compared differed between continuous forest and forest fragments, indicating that networks were resistant to the biotic and abiotic changes that accompany fragmentation. This is partially the result of the loss of only specialist species with one connection that were lost in forest fragments. We found that the networks of ant-plant mutualists in twenty-five year old fragments are similar to those in continuous forest, suggesting these interactions are resistant to the detrimental changes associated with habitat fragmentation, at least in landscapes that are a mosaic of fragments, regenerating forests, and pastures. However, ant-plant mutualistic networks may have several properties that may promote their persistence in fragmented landscapes. Proactive identification of key mutualist partners may be necessary to focus conservation efforts on the interactions that insure the integrity of network structure and the ecosystems services networks provide.

Natural language acquisition in large scale neural semantic networks

NASA Astrophysics Data System (ADS)

Ealey, Douglas

This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

A rare polyglycine type II-like helix motif in naturally occurring proteins.

PubMed

Warkentin, Eberhard; Weidenweber, Sina; Schühle, Karola; Demmer, Ulrike; Heider, Johann; Ermler, Ulrich

2017-11-01

Common structural elements in proteins such as α-helices or β-sheets are characterized by uniformly repeating, energetically favorable main chain conformations which additionally exhibit a completely saturated hydrogen-bonding network of the main chain NH and CO groups. Although polyproline or polyglycine type II helices (PP II or PG II ) are frequently found in proteins, they are not considered as equivalent secondary structure elements because they do not form a similar self-contained hydrogen-bonding network of the main chain atoms. In this context our finding of an unusual motif of glycine-rich PG II -like helices in the structure of the acetophenone carboxylase core complex is of relevance. These PG II -like helices form hexagonal bundles which appear to fulfill the criterion of a (largely) saturated hydrogen-bonding network of the main-chain groups and therefore may be regarded in this sense as a new secondary structure element. It consists of a central PG II -like helix surrounded by six nearly parallel PG II -like helices in a hexagonal array, plus an additional PG II -like helix extending the array outwards. Very related structural elements have previously been found in synthetic polyglycine fibers. In both cases, all main chain NH and CO groups of the central PG II -helix are saturated by either intra- or intermolecular hydrogen-bonds, resulting in a self-contained hydrogen-bonding network. Similar, but incomplete PG II -helix patterns were also previously identified in a GTP-binding protein and an antifreeze protein. © 2017 Wiley Periodicals, Inc.

Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

Application of nonlinear rheology to assess the effect of secondary nanofiller on network structure of hybrid polymer nanocomposites

NASA Astrophysics Data System (ADS)

Kamkar, Milad; Aliabadian, Ehsan; Shayesteh Zeraati, Ali; Sundararaj, Uttandaraman

2018-02-01

Carbon nanotube (CNT)/polymer nanocomposites exhibit excellent electrical properties by forming a percolated network. Adding a secondary filler can significantly affect the CNTs' network, resulting in changing the electrical properties. In this work, we investigated the effect of adding manganese dioxide nanowires (MnO2NWs) as a secondary nanofiller on the CNTs' network structure inside a poly(vinylidene fluoride) (PVDF) matrix. Incorporating MnO2NWs to PVDF/CNT samples produced a better state of dispersion of CNTs, as corroborated by light microscopy and transmission electron microscopy. The steady shear and oscillatory shear flows were employed to obtain a better insight into the nanofiller structure and viscoelastic behavior of the nanocomposites. The transient response under steady shear flow revealed that the stress overshoot of hybrid nanocomposites (two-fillers), PVDF/CNT/MnO2NWs, increased dramatically in comparison to binary nanocomposites (single-filler), PVDF/CNT and PVDF/MnO2NWs. This can be attributed to microstructural changes. Large amplitude oscillatory shear characterization was also performed to further investigate the effect of the secondary nanofiller on the nonlinear viscoelastic behavior of the samples. The nonlinear rheological observations were explained using quantitative nonlinear parameters [strain-stiffening ratio (S) and shear-thickening ratio (T)] and Lissajous-Bowditch plots. Results indicated that a more rigid nanofiller network was formed for the hybrid nanocomposites due to the better dispersion state of CNTs and this led to a more nonlinear viscoelastic behavior.

Formation mechanism of photo-induced nested wrinkles on siloxane-photomonomer hybrid film

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suzuki, Kazumasa; International Laboratory of Materials Science and Nanotechnology; Laboratorio di Scienz

Nested wrinkle structures, hierarchical surface wrinkles of different periodicities of sub-μm and tens-μm, have been fabricated on a siloxane-photomonomer hybrid film via a photo-induced surface polymerization of acrylamide. The formation mechanism of the nested wrinkle structures is examined based on a time-dependent structure observation and chemical composition analyses. In-situ observation of the evolving surface structure showed that sub-μm scale wrinkles first formed, subsequently the tens-μm scale ones did. In-situ FT-IR analysis indicated that the nested wrinkles formation took place along with the development of siloxane network of under layer. A cross sectional observation of the film revealed that the filmmore » was composed of three layers. FT-IR spectra of the film revealed that the surface and interior layers were polyacrylamide rich layer and siloxane-polymer rich layer, respectively. The intermediate layer formed as a diffusion layer by migration of acrylamide from interior to the surface. These three layers have different chemical compositions and therefore different mechanical characteristics, which allows the wrinkle formation. Shrinkage of siloxane-polymer interior layers, as a result of polycondensation of siloxane network, induced mechanical instabilities at interlayers, to form the nested wrinkle structures.« less

Three-dimensional Aerographite-GaN hybrid networks: Single step fabrication of porous and mechanically flexible materials for multifunctional applications

PubMed Central

Schuchardt, Arnim; Braniste, Tudor; Mishra, Yogendra K.; Deng, Mao; Mecklenburg, Matthias; Stevens-Kalceff, Marion A.; Raevschi, Simion; Schulte, Karl; Kienle, Lorenz; Adelung, Rainer; Tiginyanu, Ion

2015-01-01

Three dimensional (3D) elastic hybrid networks built from interconnected nano- and microstructure building units, in the form of semiconducting-carbonaceous materials, are potential candidates for advanced technological applications. However, fabrication of these 3D hybrid networks by simple and versatile methods is a challenging task due to the involvement of complex and multiple synthesis processes. In this paper, we demonstrate the growth of Aerographite-GaN 3D hybrid networks using ultralight and extremely porous carbon based Aerographite material as templates by a single step hydride vapor phase epitaxy process. The GaN nano- and microstructures grow on the surface of Aerographite tubes and follow the network architecture of the Aerographite template without agglomeration. The synthesized 3D networks are integrated with the properties from both, i.e., nanoscale GaN structures and Aerographite in the form of flexible and semiconducting composites which could be exploited as next generation materials for electronic, photonic, and sensors applications. PMID:25744694

Secure remote synchronization and secure key distribution in electro-optic networks revealed by symmetries

NASA Astrophysics Data System (ADS)

Xu, Mingfeng; Pan, Wei; Zhang, Liyue

2018-07-01

Despite the intuition that synchronization of different nodes in coupled oscillator networks results from information exchange between them, it has recently been shown that remote nodes could be partially synchronous even when they are separated by intermediately unsynchronized nodes. Here based on electro-optic system, we report on a more stronger form of such synchronization pattern that is termed as secure remote synchronization, in which two remotely separated nodes could have identically synchronized dynamical behaviors while the rest of the network are both statistically and information-theoretically incoherent relative to the two synchronized nodes. The generalized form of mirror symmetry in the network structure is identified to be a key mechanism allowing for secure remote synchronization. Moreover, this synchronization mode is robust against a wild range of system parameters and noise perturbing the intermediary dynamics. The lack of information about the synchronized dynamics in the rest of the network suggests that our results could potentially lead to network-based solutions for secure key distribution and secure communication.

Social networks and cooperation in hunter-gatherers.

PubMed

Apicella, Coren L; Marlowe, Frank W; Fowler, James H; Christakis, Nicholas A

2012-01-25

Social networks show striking structural regularities, and both theory and evidence suggest that networks may have facilitated the development of large-scale cooperation in humans. Here, we characterize the social networks of the Hadza, a population of hunter-gatherers in Tanzania. We show that Hadza networks have important properties also seen in modernized social networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay and homophily. We demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history. Also, early humans may have formed ties with both kin and non-kin, based in part on their tendency to cooperate. Social networks may thus have contributed to the emergence of cooperation.

Confinement properties of 2D porous molecular networks on metal surfaces

NASA Astrophysics Data System (ADS)

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-01

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

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

PubMed

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-20

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

The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing

PubMed Central

Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan

2017-01-01

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014

Pleasure attainment or self-realization: the balance between two forms of well-beings are encoded in default mode network.

PubMed

Luo, Yangmei; Qi, Senqing; Chen, Xuhai; You, Xuqun; Huang, Xiting; Yang, Zhen

2017-10-01

What is a good life and how it can be achieved is one of the fundamental issues. When considering a good life, there is a division between hedonic (pleasure attainment) and eudaimonic well-being (meaning pursuing and self-realization). However, an integrated approach that can compare the brain functional and structural differences of these two forms of well-being is lacking. Here, we investigated how the individual tendency to eudaimonic well-being relative to hedonic well-being, measured using eudaimonic and hedonic balance (EHB) index, is reflected in the functional and structural features of a key network of well-being-the default mode network (DMN). We found that EHB was positively correlated with functional connectivity of bilateral ventral medial prefrontal cortex within anterior DMN and bilateral precuneus within posterior DMN. Brain morphometric analysis showed that EHB was also positively correlated with gray matter volume in left precuneus. These results demonstrated that the relative dominance of one form of well-being to the other is reflected in the morphometric characteristics and intrinsic functions of DMN. © The Author (2017). Published by Oxford University Press.

Nonequilibrium stabilization of an RNA/protein droplet emulsion by nuclear actin

NASA Astrophysics Data System (ADS)

Brangwynne, Clifford

2013-03-01

Actin plays a structural role in the cytoplasm. However, actin takes on new functions and structures in the nucleus that are poorly understood. The nuclei of the large oocytes of the frog X. laevisspecifically accumulate actin to reach high concentrations; however, it remains unclear if this actin polymerizes into a network, and what, if any, structural role such an actin network might play. Here, we use microrheological and confocal imaging techniques to probe the local architecture and mechanics of the nucleus. Our data show that actin forms a weak network that spatially organizes the nucleus by kinetically stabilizing embedded liquid-like RNA/protein bodies which are important for cell growth. In actin-disrupted nuclei this RNA/protein droplet emulsion is destabilized leading to homotypic coalescence into single large droplets. Our data provide intriguing new insights into why large cell nuclei require an actin-based structural scaffold.

Site-Mutation of Hydrophobic Core Residues Synchronically Poise Super Interleukin 2 for Signaling: Identifying Distant Structural Effects through Affordable Computations.

PubMed

Mei, Longcan; Zhou, Yanping; Zhu, Lizhe; Liu, Changlin; Wu, Zhuo; Wang, Fangkui; Hao, Gefei; Yu, Di; Yuan, Hong; Cui, Yanfang

2018-03-20

A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with which to get insight about how to utilize allosteric effect to achieve desirable protein functions. By examining the dynamic network and the allosteric pathways related to those mutated residues using various computational approaches, we found that nanosecond time scale all-atom molecular dynamics simulations can identify the dynamic network as efficient as an ensemble algorithm. The differentiated pathways for the six core residues form a dynamic network that outlines the area of structure alteration. The results offer potentials of using affordable computing power to predict allosteric structure of mutants in knowledge-based mutagenesis.

Reason for high strength and good ductility in dual phase steels composed of soft ferrite and hard martensite

NASA Astrophysics Data System (ADS)

Terada, Daisuke; Ikeda, Gosuke; Park, Myeong-heom; Shibata, Akinobu; Tsuji, Nobuhiro

2017-07-01

Dual phase (DP) steels in which the microstructures are composed of a soft ferrite phase and a hard martensite phase are known to show good strain-hardening, high strength and large elongation, but reasons for their superior mechanical properties are still unclear. In the present study, two types of DP structures, having either networked martensite or isolated martensite were fabricated in a low-carbon steel by different heat treatment routes, and their tensile deformation behavior was analyzed using the digital image correlation (DIC) technique. It was revealed that the DP specimens having networked martensite microstructures showed a better strength-ductility balance than the DP specimens with isolated martensite structures. The microscopic DIC analysis of identical areas showed that the strain distribution within the DP microstructures was not uniform and the plastic strain was localized in soft ferrite grains. The strain localized regions tended to detour around hard martensite but eventually propagated across the martensite. It was found also from the DIC analysis that the degree of strain partitioning between ferrite and martensite in the networked DP structure was lower than that in the isolated DP structure. The deformation became more homogeneous when the hard phase (martensite) was connected to form a network structure, which could be one of the reasons for the better strength-ductility balance in the networked DP structure compared to that in the isolated DP structure.

New Insights into Structure-Property Relationships in Thermosetting Polymers from Studies of Co-Cured Polycyanurate Networks (Preprint)

DTIC Science & Technology

2011-12-19

have shown through positron annihilation studies that a substantial amount of free volume develops during the final stages of cyanate ester cure...Polymers from 5b. GRANT NUMBER Studies of Co-Cured Polycyanurate Networks (preprint) 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Andrew J. Guenthner...Macromolecules. 14. ABSTRACT Studies of the physical properties of the co-cured networks formed from three similar dicyanate ester monomers revealed a

Graphs for information security control in software defined networks

NASA Astrophysics Data System (ADS)

Grusho, Alexander A.; Abaev, Pavel O.; Shorgin, Sergey Ya.; Timonina, Elena E.

2017-07-01

Information security control in software defined networks (SDN) is connected with execution of the security policy rules regulating information accesses and protection against distribution of the malicious code and harmful influences. The paper offers a representation of a security policy in the form of hierarchical structure which in case of distribution of resources for the solution of tasks defines graphs of admissible interactions in a networks. These graphs define commutation tables of switches via the SDN controller.

Network analysis of Bogotá's Ciclovía Recreativa, a self-organized multisectorial community program to promote physical activity in a middle-income country.

PubMed

Meisel, Jose D; Sarmiento, Olga L; Montes, Felipe; Martinez, Edwin O; Lemoine, Pablo D; Valdivia, Juan A; Brownson, Ross C; Zarama, Roberto

2014-01-01

Conduct a social network analysis of the health and non-health related organizations that participate in Bogotá's Ciclovía Recreativa (Ciclovía). Cross-sectional study. Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and physical activity. Twenty-five organizations that participate in the Ciclovía. Seven variables were examined by using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Analysis shows that the most central organizations in the network were outside of the Health sector and include Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central.

Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

NASA Astrophysics Data System (ADS)

Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

2017-05-01

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

Hydrogels constructed via self-assembly of beta-hairpin molecules

NASA Astrophysics Data System (ADS)

Ozbas, Bulent

There is a recent and growing interest in hydrogel materials that are formed via peptide self-assembly for tissue engineering applications. Peptide based materials are excellent candidates for diverse applications in biomedical field due to their responsive behavior and complex self-assembled structures. However, there is very limited information on the self-assembly and resultant network and mechanical properties of these types of hydrogels. The main goal of this dissertation is to investigate the self-assembly mechanism and viscoelastic properties of hydrogels that can be altered by changing solution conditions as well as the primary structure of the peptide. These hydrogels are formed via intramolecular folding and consequent self-assembly of 20 amino acid long beta-hairpin peptide molecules (Max1). The peptide molecules are locally amphiphilic with two linear strands of alternating hydrophobic valine and hydrophilic lysine amino acids connected with a Dproline-LProline turn sequence. Circular dichroism and FTIR spectroscopy show that at physiological conditions peptides are unfolded in the absence of salt. By raising the ionic strength of the solution electrostatic interactions between charged lysines are screened and the peptide arms are forced into a beta-sheet secondary structure stabilized by the turn sequence. These folded molecules intermolecularly assemble via hydrophobic collapse and hydrogen bonding into a three dimensional network. Folding and self-assembly of these molecules can also be triggered by increasing temperature and/or pH of the peptide solution. In addition, the random-coil to beta-sheet transition of the beta-hairpin peptides is pH and, with proper changes in the peptide sequence, thermally reversible. Rheological measurements demonstrate that the resultant supramolecular structure forms an elastic material, whose structure, and thus modulus, can be tuned by magnitude of the stimulus. Hydrogels recover their initial viscoelastic properties after cessation of high magnitude of strain due to the physically crosslinked network structure and strong inter-fibrillar interactions. These interactions can be turned off by either condensing anions or covalently attaching PEG chains on lysine-decorated fibrillar surfaces. TEM, SANS, and rheological data reveal that the elasticity arises from a network consisting of semiflexible fibrillar assemblies that are monodisperse in width. The experimental results are compared with scaling relationships developed for permanently crosslinked semiflexible biopolymer networks. (Abstract shortened by UMI.)

The ER in 3D: a multifunctional dynamic membrane network.

PubMed

Friedman, Jonathan R; Voeltz, Gia K

2011-12-01

The endoplasmic reticulum (ER) is a large, singular, membrane-bound organelle that has an elaborate 3D structure with a diversity of structural domains. It contains regions that are flat and cisternal, ones that are highly curved and tubular, and others adapted to form contacts with nearly every other organelle and with the plasma membrane. The 3D structure of the ER is determined by both integral ER membrane proteins and by interactions with the cytoskeleton. In this review, we describe some of the factors that are known to regulate ER structure and discuss how this structural organization and the dynamic nature of the ER membrane network allow it to perform its many different functions. Copyright © 2011 Elsevier Ltd. All rights reserved.

The apoptotic microtubule network preserves plasma membrane integrity during the execution phase of apoptosis.

PubMed

Sánchez-Alcázar, José A; Rodríguez-Hernández, Angeles; Cordero, Mario D; Fernández-Ayala, Daniel J M; Brea-Calvo, Gloria; Garcia, Katherina; Navas, Plácido

2007-07-01

It has recently been shown that the microtubule cytoskeleton is reformed during the execution phase of apoptosis. We demonstrate that this microtubule reformation occurs in many cell types and under different apoptotic stimuli. We confirm that the apoptotic microtubule network possesses a novel organization, whose nucleation appears independent of conventional gamma-tubulin ring complex containing structures. Our analysis suggests that microtubules are closely associated with the plasma membrane, forming a cortical ring or cellular "cocoon". Concomitantly other components of the cytoskeleton, such as actin and cytokeratins disassemble. We found that colchicine-mediated disruption of apoptotic microtubule network results in enhanced plasma membrane permeability and secondary necrosis, suggesting that the reformation of a microtubule cytoskeleton plays an important role in preserving plasma membrane integrity during apoptosis. Significantly, cells induced to enter apoptosis in the presence of the pan-caspase inhibitor z-VAD, nevertheless form microtubule-like structures suggesting that microtubule formation is not dependent on caspase activation. In contrast we found that treatment with EGTA-AM, an intracellular calcium chelator, prevents apoptotic microtubule network formation, suggesting that intracellular calcium may play an essential role in the microtubule reformation. We propose that apoptotic microtubule network is required to maintain plasma membrane integrity during the execution phase of apoptosis.

Low-Dimensional Network Formation in Molten Sodium Carbonate

PubMed Central

Wilding, Martin C.; Wilson, Mark; Alderman, Oliver L. G.; Benmore, Chris; Weber, J. K. R.; Parise, John B.; Tamalonis, Anthony; Skinner, Lawrie

2016-01-01

Molten carbonates are highly inviscid liquids characterized by low melting points and high solubility of rare earth elements and volatile molecules. An understanding of the structure and related properties of these intriguing liquids has been limited to date. We report the results of a study of molten sodium carbonate (Na2CO3) which combines high energy X-ray diffraction, containerless techniques and computer simulation to provide insight into the liquid structure. Total structure factors (Fx(Q)) are collected on the laser-heated carbonate spheres suspended in flowing gases of varying composition in an aerodynamic levitation furnace. The respective partial structure factor contributions to Fx(Q) are obtained by performing molecular dynamics simulations treating the carbonate anions as flexible entities. The carbonate liquid structure is found to be heavily temperature-dependent. At low temperatures a low-dimensional carbonate chain network forms, at T = 1100 K for example ~55% of the C atoms form part of a chain. The mean chain lengths decrease as temperature is increased and as the chains become shorter the rotation of the carbonate anions becomes more rapid enhancing the diffusion of Na+ ions. PMID:27080401

A Simulator for the Respiratory Tree in Healthy Subjects Derived from Continued Fractions Expansions

NASA Astrophysics Data System (ADS)

Muntean, Ionuţ; Ionescu, Clara; Naşcu, Ioan

2009-04-01

Taking into account the self-similar recurrent geometrical structure of the human respiratory tree, the total respiratory impedance can be represented using an electrical equivalent of a ladder network model. In this paper, the parameters of the respiratory tree are employed in simulation, based on clinical insight and morphology. Once the transfer function of the total input impedance model is calculated, it is further interpreted in its continued fraction expansion form. The purpose is to compare the ladder network structure with the continuous fraction expansion form of the impedance. The results are supporting the theory of fractional-order impedance appearance (also known as constant-phase behaviour) and help understanding the mathematical and morphological basis for constructing a physiology-based simulator of the human lungs.

Online graphic symbol recognition using neural network and ARG matching

NASA Astrophysics Data System (ADS)

Yang, Bing; Li, Changhua; Xie, Weixing

2001-09-01

This paper proposes a novel method for on-line recognition of line-based graphic symbol. The input strokes are usually warped into a cursive form due to the sundry drawing style, and classifying them is very difficult. To deal with this, an ART-2 neural network is used to classify the input strokes. It has the advantages of high recognition rate, less recognition time and forming classes in a self-organized manner. The symbol recognition is achieved by an Attribute Relational Graph (ARG) matching algorithm. The ARG is very efficient for representing complex objects, but computation cost is very high. To over come this, we suggest a fast graph matching algorithm using symbol structure information. The experimental results show that the proposed method is effective for recognition of symbols with hierarchical structure.

Elements of an algorithm for optimizing a parameter-structural neural network

NASA Astrophysics Data System (ADS)

Mrówczyńska, Maria

2016-06-01

The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.

Communication, opponents, and clan performance in online games: a social network approach.

PubMed

Lee, Hong Joo; Choi, Jaewon; Kim, Jong Woo; Park, Sung Joo; Gloor, Peter

2013-12-01

Online gamers form clans voluntarily to play together and to discuss their real and virtual lives. Although these clans have diverse goals, they seek to increase their rank in the game community by winning more battles. Communications among clan members and battles with other clans may influence the performance of a clan. In this study, we compared the effects of communication structure inside a clan, and battle networks among clans, with the performance of the clans. We collected battle histories, posts, and comments on clan pages from a Korean online game, and measured social network indices for communication and battle networks. Communication structures in terms of density and group degree centralization index had no significant association with clan performance. However, the centrality of clans in the battle network was positively related to the performance of the clan. If a clan had many battle opponents, the performance of the clan improved.

Communication, Opponents, and Clan Performance in Online Games: A Social Network Approach

PubMed Central

Lee, Hong Joo; Choi, Jaewon; Park, Sung Joo; Gloor, Peter

2013-01-01

Abstract Online gamers form clans voluntarily to play together and to discuss their real and virtual lives. Although these clans have diverse goals, they seek to increase their rank in the game community by winning more battles. Communications among clan members and battles with other clans may influence the performance of a clan. In this study, we compared the effects of communication structure inside a clan, and battle networks among clans, with the performance of the clans. We collected battle histories, posts, and comments on clan pages from a Korean online game, and measured social network indices for communication and battle networks. Communication structures in terms of density and group degree centralization index had no significant association with clan performance. However, the centrality of clans in the battle network was positively related to the performance of the clan. If a clan had many battle opponents, the performance of the clan improved. PMID:23745617

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

Social barriers to Type 2 diabetes self-management: the role of capital.

PubMed

Henderson, Julie; Wilson, Christine; Roberts, Louise; Munt, Rebecca; Crotty, Mikaila

2014-12-01

Approaches to self-management traditionally focus upon individual capacity to make behavioural change. In this paper, we use Bourdieu's concepts of habitus and capital to demonstrate the impact of structural inequalities upon chronic illness self-management through exploring findings from 28 semi-structured interviews conducted with people from a lower socioeconomic region of Adelaide, South Australia who have type 2 diabetes. The data suggests that access to capital is a significant barrier to type 2 diabetes self-management. While many participants described having sufficient cultural capital to access and assess health information, they often lacked economic capital and social capital in the form of support networks who promote health. Participants were often involved in social networks in which activities which are contrary to self-management have symbolic value. As a consequence, they entered relationships with health professionals at a disadvantage. We conclude that structural barriers to self-management arising from habitus resulting in the performance of health behaviours rooted in cultural and class background and limited access to capital in the form of economic resources, social networks, health knowledge and prestige may have a negative impact on capacity for type 2 diabetes self-management. © 2014 John Wiley & Sons Ltd.

Social Network Theory in Engineering Education

NASA Astrophysics Data System (ADS)

Simon, Peter A.

Collaborative groups are important both in the learning environment of engineering education and, in the real world, the business of engineering design. Selecting appropriate individuals to form an effective group and monitoring a group's progress are important aspects of successful task performance. This exploratory study looked at using the concepts of cognitive social structures, structural balance, and centrality from social network analysis as well as the measures of emotional intelligence. The concepts were used to analyze potential team members to examine if an individual's ability to perceive emotion in others and the self and to use, understand, and manage those emotions are a factor in a group's performance. The students from a capstone design course in computer engineering were used as volunteer subjects. They were formed into groups and assigned a design exercise to determine whether and which of the above-mentioned tools would be effective in both selecting teams and predicting the quality of the resultant design. The results were inconclusive with the exception of an individual's ability to accurately perceive emotions. The instruments that were successful were the Self-Monitoring scale and the accuracy scores derived from cognitive social structures and Level IV of network levels of analysis.

Reduced structural connectivity within a prefrontal-motor-subcortical network in amyotrophic lateral sclerosis.

PubMed

Buchanan, Colin R; Pettit, Lewis D; Storkey, Amos J; Abrahams, Sharon; Bastin, Mark E

2015-05-01

To investigate white matter structural connectivity changes associated with amyotrophic lateral sclerosis (ALS) using network analysis and compare the results with those obtained using standard voxel-based methods, specifically Tract-based Spatial Statistics (TBSS). MRI data were acquired from 30 patients with ALS and 30 age-matched healthy controls. For each subject, 85 grey matter regions (network nodes) were identified from high resolution structural MRI, and network connections formed from the white matter tracts generated by diffusion MRI and probabilistic tractography. Whole-brain networks were constructed using strong constraints on anatomical plausibility and a weighting reflecting tract-averaged fractional anisotropy (FA). Analysis using Network-based Statistics (NBS), without a priori selected regions, identified an impaired motor-frontal-subcortical subnetwork (10 nodes and 12 bidirectional connections), consistent with upper motor neuron pathology, in the ALS group compared with the controls (P = 0.020). Reduced FA in three of the impaired network connections, which involved fibers of the corticospinal tract, correlated with rate of disease progression (P ≤ 0.024). A novel network-tract comparison revealed that the connections involved in the affected network had a strong correspondence (mean overlap of 86.2%) with white matter tracts identified as having reduced FA compared with the control group using TBSS. These findings suggest that white matter degeneration in ALS is strongly linked to the motor cortex, and that impaired structural networks identified using NBS have a strong correspondence to affected white matter tracts identified using more conventional voxel-based methods. © 2014 Wiley Periodicals, Inc.

Evolution of network architecture in a granular material under compression

NASA Astrophysics Data System (ADS)

Bassett, Danielle

As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. However, capturing and characterizing the dynamic nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. Here, we utilize multilayer networks as a framework for directly quantifying the evolution of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and inter-particle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the reconfiguration and evolution of this structure throughout the compression process. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be done by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than consideration of the local inter-particle forces alone. The results discussed throughout this study suggest that these novel network science techniques may provide a direct way to compare and classify data from systems under different external conditions or with different physical makeup. National Science Foundation (BCS-1441502, PHY-1554488, and BCS-1631550).

Graph analysis of cell clusters forming vascular networks

NASA Astrophysics Data System (ADS)

Alves, A. P.; Mesquita, O. N.; Gómez-Gardeñes, J.; Agero, U.

2018-03-01

This manuscript describes the experimental observation of vasculogenesis in chick embryos by means of network analysis. The formation of the vascular network was observed in the area opaca of embryos from 40 to 55 h of development. In the area opaca endothelial cell clusters self-organize as a primitive and approximately regular network of capillaries. The process was observed by bright-field microscopy in control embryos and in embryos treated with Bevacizumab (Avastin), an antibody that inhibits the signalling of the vascular endothelial growth factor (VEGF). The sequence of images of the vascular growth were thresholded, and used to quantify the forming network in control and Avastin-treated embryos. This characterization is made by measuring vessels density, number of cell clusters and the largest cluster density. From the original images, the topology of the vascular network was extracted and characterized by means of the usual network metrics such as: the degree distribution, average clustering coefficient, average short path length and assortativity, among others. This analysis allows to monitor how the largest connected cluster of the vascular network evolves in time and provides with quantitative evidence of the disruptive effects that Avastin has on the tree structure of vascular networks.

Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer’s disease

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Villalon-Reina, Julio E.; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Joshi, Aditi; Barsuglia, Joseph; Thompson, Paul M.

2015-01-01

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants – 15 patients with behavioral variant frontotemporal (bvFTD) dementia, 19 with early-onset Alzheimer’s disease (EOAD), and 30 healthy elderly controls. Based on whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We examined how bvFTD and EOAD disrupt the weighted ‘rich club’ – a network property where high-degree network nodes are more interconnected than expected by chance. bvFTD disrupts both the nodal and global organization of the network in both low- and high-degree regions of the brain. EOAD targets the global connectivity of the brain, mainly affecting the fiber density of high-degree (highly connected) regions that form the rich club network. These rich club analyses suggest distinct patterns of disruptions among different forms of dementia. PMID:26161050

Optimized multi-step NMR-crystallography approach for structural characterization of a stable quercetin solvate.

PubMed

Filip, Xenia; Miclaus, Maria; Martin, Flavia; Filip, Claudiu; Grosu, Ioana Georgeta

2017-05-10

Herein we report the preparation and solid state structural investigation of the 1,4-dioxane-quercetin solvate. NMR crystallography methods were employed for crystal structure determination of the solvate from microcrystalline powder. The stability of the compound relative to other reported quercetin solvates is discussed and found to be in perfect agreement with the hydrogen bonding networks/supra-molecular architectures formed in each case. It is also clearly shown that NMR crystallography represents an ideal analytical tool in such cases when hydrogen-bonding networks are required to be constrained at a high accuracy level. Copyright © 2017 Elsevier B.V. All rights reserved.

Integration of colloids into a semi-flexible network of fibrin.

PubMed

Bharadwaj, N Ashwin K; Kang, Jin Gu; Hatzell, Marta C; Schweizer, Kenneth S; Braun, Paul V; Ewoldt, Randy H

2017-02-15

Typical colloid-polymer composites have particle diameters much larger than the polymer mesh size, but successful integration of smaller colloids into a large-mesh network could allow for the realization of new colloidal states of spatial organization and faster colloid motion which can allow the possibility of switchable re-configuration of colloids or more dramatic stimuli-responsive property changes. Experimental realization of such composites requires solving non-trivial materials selection and fabrication challenges; key questions include composition regime maps of successful composites, the resulting structure and colloidal contact network, and the mechanical properties, in particular the ability to form a network and retain strain stiffening in the presence of colloids. Here, we study these fundamental questions by formulating composites with fluorescent (though not stimuli-responsive) carboxylate modified polystyrene/latex (CML) colloidal particles (diameters 200 nm and 1000 nm) in bovine fibrin networks (a semi-flexible biopolymer network with mesh size 1-5 μm). We describe and characterize two methods of composite preparation: adding colloids before fibrinogen polymerization (Method I), and electrophoretically driving colloids into a network already formed by fibrinogen polymerization (Method II). We directly image the morphology of colloidal and fibrous components with two-color fluorescent confocal microscopy under wet conditions and SEM of fixed dry samples. Mechanical properties are studied with shear and extensional rheology. Both fabrication methods are successful, though with trade-offs. Method I retains the nonlinear strain-stiffening and extensibility of the native fibrin network, but some colloid clustering is observed and fibrin network integrity is lost above a critical colloid concentration that depends on fibrinogen and thrombin concentration. Larger colloids can be included at higher volume fractions before massive aggregation occurs, indicating surface interactions as a limiting factor. Method II results in a loss of measurable strain-stiffening, but colloids are well dispersed and template along the fibrous scaffold. The results here, with insight into both structure and rheology, form a foundational understanding for the integration of other colloids, e.g. with stimuli-responsive functionalities, into semi-flexible networks.

Covalent adaptable networks: smart, reconfigurable and responsive network systems.

PubMed

Kloxin, Christopher J; Bowman, Christopher N

2013-09-07

Covalently crosslinked materials, classically referred to as thermosets, represent a broad class of elastic materials that readily retain their shape and molecular architecture through covalent bonds that are ubiquitous throughout the network structure. These materials, in particular in their swollen gel state, have been widely used as stimuli responsive materials with their ability to change volume in response to changes in temperature, pH, or other solvent conditions and have also been used in shape memory applications. However, the existence of a permanent, unalterable shape and structure dictated by the covalently crosslinked structure has dramatically limited their abilities in this and many other areas. These materials are not generally reconfigurable, recyclable, reprocessable, and have limited ability to alter permanently their stress state, topography, topology, or structure. Recently, a new paradigm has been explored in crosslinked polymers - that of covalent adaptable networks (CANs) in which covalently crosslinked networks are formed such that triggerable, reversible chemical structures persist throughout the network. These reversible covalent bonds can be triggered through molecular triggers, light or other incident radiation, or temperature changes. Upon application of this stimulus, rather than causing a temporary shape change, the CAN structure responds by permanently adjusting its structure through either reversible addition/condensation or through reversible bond exchange mechanisms, either of which allow the material to essentially reequilibrate to its new state and condition. Here, we provide a tutorial review on these materials and their responsiveness to applied stimuli. In particular, we review the broad classification of these materials, the nature of the chemical bonds that enable the adaptable structure, how the properties of these materials depend on the reversible structure, and how the application of a stimulus causes these materials to alter their shape, topography, and properties.

Investigating brain community structure abnormalities in bipolar disorder using path length associated community estimation.

PubMed

Gadelkarim, Johnson J; Ajilore, Olusola; Schonfeld, Dan; Zhan, Liang; Thompson, Paul M; Feusner, Jamie D; Kumar, Anand; Altshuler, Lori L; Leow, Alex D

2014-05-01

In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. Copyright © 2013 Wiley Periodicals, Inc.

Impulsivity and the Modular Organization of Resting-State Neural Networks

PubMed Central

Davis, F. Caroline; Knodt, Annchen R.; Sporns, Olaf; Lahey, Benjamin B.; Zald, David H.; Brigidi, Bart D.; Hariri, Ahmad R.

2013-01-01

Impulsivity is a complex trait associated with a range of maladaptive behaviors, including many forms of psychopathology. Previous research has implicated multiple neural circuits and neurotransmitter systems in impulsive behavior, but the relationship between impulsivity and organization of whole-brain networks has not yet been explored. Using graph theory analyses, we characterized the relationship between impulsivity and the functional segregation (“modularity”) of the whole-brain network architecture derived from resting-state functional magnetic resonance imaging (fMRI) data. These analyses revealed remarkable differences in network organization across the impulsivity spectrum. Specifically, in highly impulsive individuals, regulatory structures including medial and lateral regions of the prefrontal cortex were isolated from subcortical structures associated with appetitive drive, whereas these brain areas clustered together within the same module in less impulsive individuals. Further exploration of the modular organization of whole-brain networks revealed novel shifts in the functional connectivity between visual, sensorimotor, cortical, and subcortical structures across the impulsivity spectrum. The current findings highlight the utility of graph theory analyses of resting-state fMRI data in furthering our understanding of the neurobiological architecture of complex behaviors. PMID:22645253

Construction of monomer-free, highly crosslinked, water-compatible polymers.

PubMed

Dailing, E A; Lewis, S H; Barros, M D; Stansbury, J W

2014-12-01

Polymeric dental adhesives require the formation of densely crosslinked network structures to best ensure mechanical strength and durability in clinical service. Monomeric precursors to these materials typically consist of mixtures of hydrophilic and hydrophobic components that potentially undergo phase separation in the presence of low concentrations of water, which is detrimental to material performance and has motivated significant investigation into formulations that reduce this effect. We have investigated an approach to network formation based on nanogels that are dispersed in inert solvent and directly polymerized into crosslinked polymers. Monomers of various hydrophilic or hydrophobic characteristics were copolymerized into particulate nanogels bearing internal and external polymerizable functionality. Nanogel dispersions were stable at high concentrations in acetone or, with some exceptions, in water and produced networks with a wide range of mechanical properties. Networks formed rapidly upon light activation and reached high conversion with extremely low volumetric shrinkage. Prepolymerizing monomers into reactive nanostructures significantly changes how hydrophobic materials respond to water compared with networks obtained from polymerizations involving free monomer. The modulus of fully hydrated networks formed solely from nanogels was shown to equal or exceed the modulus in the dry state for networks based on nanogels containing a hydrophobic dimethacrylate and hydrophilic monomethacrylate, a result that was not observed in a hydroxyethyl methacrylate (HEMA) homopolymer or in networks formed from nanogels copolymerized with HEMA. These results highlight the unique approach to network development from nanoscale precursors and properties that have direct implications in functional dental materials. © International & American Associations for Dental Research.

Correlated network of networks enhances robustness against catastrophic failures.

PubMed

Min, Byungjoon; Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

Correlated network of networks enhances robustness against catastrophic failures

PubMed Central

Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule. PMID:29668730

Influence maximization in complex networks through optimal percolation

NASA Astrophysics Data System (ADS)

Morone, Flaviano; Makse, Hernan; CUNY Collaboration; CUNY Collaboration

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. Reference: F. Morone, H. A. Makse, Nature 524,65-68 (2015)

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles

PubMed Central

Azulay, Aharon; Zaslaver, Alon

2016-01-01

A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available. PMID:27606684

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Code System to Calculate Tornado-Induced Flow Material Transport.

DOE Office of Scientific and Technical Information (OSTI.GOV)

ANDRAE, R. W.

1999-11-18

Version: 00 TORAC models tornado-induced flows, pressures, and material transport within structures. Its use is directed toward nuclear fuel cycle facilities and their primary release pathway, the ventilation system. However, it is applicable to other structures and can model other airflow pathways within a facility. In a nuclear facility, this network system could include process cells, canyons, laboratory offices, corridors, and offgas systems. TORAC predicts flow through a network system that also includes ventilation system components such as filters, dampers, ducts, and blowers. These ventilation system components are connected to the rooms and corridors of the facility to form amore » complete network for moving air through the structure and, perhaps, maintaining pressure levels in certain areas. The material transport capability in TORAC is very basic and includes convection, depletion, entrainment, and filtration of material.« less

Phase structure within a fracture network beneath a surface pond: Field experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

GLASS JR.,ROBERT J.; NICHOLL,M.J.

2000-05-09

The authors performed a simple experiment to elucidate phase structure within a pervasively fractured welded tuff. Dyed water was infiltrated from a surface pond over a 36 minute period while a geophysical array monitored the wetted region within vertical planes directly beneath. They then excavated the rock mass to a depth of {approximately}5 m and mapped the fracture network and extent of dye staining in a series of horizontal pavements. Near the pond the network was fully stained. Below, the phase structure immediately expanded and with depth, the structure became fragmented and complicated exhibiting evidence of preferential flow, fingers, irregularmore » wetting patterns, and varied behavior at fracture intersections. Limited transient geophysical data suggested that strong vertical pathways form first followed by increased horizontal expansion and connection within the network. These rapid pathways are also the first to drain. Estimates also suggest that the excavation captured from {approximately}10% to 1% or less of the volume of rock interrogated by the infiltration slug and thus the penetration depth could have been quite large.« less

Enhancing response coordination through the assessment of response network structural dynamics.

PubMed

Abbasi, Alireza; Sadeghi-Niaraki, Abolghasem; Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks' and participants' structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant's brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy.

Flux Quantization in Aperiodic and Periodic Networks

NASA Astrophysics Data System (ADS)

Behrooz, Angelika

The normal - superconducting phase boundary, T_{c}(H), of a periodic wire network shows periodic oscillations with period H _{o} = phi_ {o}/A due to flux quantization around the individual plaquettes (of area A) of the network. The magnetic flux quantum is phi_{o } = hc/2e. The phase boundary also shows fine structure at fields H = (p/q)H_{o} (p,q integers), where the flux vortices can form commensurate superlattices on the periodic substrate. We have studied the phase boundary of quasicrystalline, quasiperiodic and random networks. We have found that if a network is composed of two different tiles, whose areas are relatively irrational then the T_ {c}(H) curve shows large scale structure at fields that approximate flux quantization around the tiles, i.e. when the ratio of fluxoids contained in the large tiles to those in the small tiles is a rational approximant to the irrational area ratio. The phase boundaries of quasicrystalline and quasiperiodic networks show fine structure indicating the existence of commensurate vortex superlattices on these networks. No such fine structure is found on the random array. For a quasicrystal whose quasiperiodic long-range order is characterized by the irrational number tau the commensurate vortex lattices are all found at H = H_{o}| n + mtau| (n,m integers). We have found that the commensurate superlattices on quasicrystalline as well as on crystalline networks are related to the inflation symmetry. We propose a general definition of commensurability.

Friendship Concept and Community Network Structure among Elementary School and University Students.

PubMed

Hernández-Hernández, Ana María; Viga-de Alva, Dolores; Huerta-Quintanilla, Rodrigo; Canto-Lugo, Efrain; Laviada-Molina, Hugo; Molina-Segui, Fernanda

2016-01-01

We use complex network theory to study the differences between the friendship concepts in elementary school and university students. Four friendship networks were identified from surveys. Three of these networks are from elementary schools; two are located in the rural area of Yucatán and the other is in the urban area of Mérida, Yucatán. We analyzed the structure and the communities of these friendship networks and found significant differences among those at the elementary schools compared with those at the university. In elementary schools, the students make friends mainly in the same classroom, but there are also links among different classrooms because of the presence of siblings and relatives in the schools. These kinds of links (sibling-friend or relative-friend) are called, in this work, "mixed links". The classification of the communities is based on their similarity with the classroom composition. If the community is composed principally of students in different classrooms, the community is classified as heterogeneous. These kinds of communities appear in the elementary school friendship networks mainly because of the presence of relatives and siblings. Once the links between siblings and relatives are removed, the communities resembled the classroom composition. On the other hand, the university students are more selective in choosing friends and therefore, even when they have friends in the same classroom, those communities are quite different to the classroom composition. Also, in the university network, we found heterogeneous communities even when the presence of sibling and relatives is negligible. These differences made up a topological structure quite different at different academic levels. We also found differences in the network characteristics. Once these differences are understood, the topological structure of the friendship network and the communities shaped in an elementary school could be predicted if we know the total number of students and the ties between siblings and relatives. However, at the university, we cannot do the same. This discovery implies that friendship is a dynamic concept that produces several changes in the friendship network structure and the way that people make groups of friends; it provides the opportunity to give analytic support to observational studies. Communities were also studied by gender and we found that when the links among relatives and siblings were removed, the number of communities formed by one gender alone increased. At the university, many communities formed by students of the same gender were also found.

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Role of graph architecture in controlling dynamical networks with applications to neural systems

NASA Astrophysics Data System (ADS)

Kim, Jason Z.; Soffer, Jonathan M.; Kahn, Ari E.; Vettel, Jean M.; Pasqualetti, Fabio; Bassett, Danielle S.

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Vibration reduction for smart periodic structures via periodic piezoelectric arrays with nonlinear interleaved-switched electronic networks

NASA Astrophysics Data System (ADS)

Bao, Bin; Guyomar, Daniel; Lallart, Mickaël

2017-01-01

Smart periodic structures covered by periodically distributed piezoelectric patches have drawn more and more attention in recent years for wave propagation attenuation and corresponding structural vibration suppression. Since piezoelectric materials are special type of energy conversion materials that link mechanical characteristics with electrical characteristics, shunt circuits coupled with such materials play a key role in the wave propagation and/or vibration control performance in smart periodic structures. Conventional shunt circuit designs utilize resistive shunt (R-shunt) and resonant shunt (RL-shunt). More recently, semi-passive nonlinear approaches have also been developed for efficiently controlling the vibrations of such structures. In this paper, an innovative smart periodic beam structure with nonlinear interleaved-switched electric networks based on synchronized switching damping on inductor (SSDI) is proposed and investigated for vibration reduction and wave propagation attenuation. Different from locally resonant band gap mechanism forming narrow band gaps around the desired resonant frequencies, the proposed interleaved electrical networks can induce new broadly low-frequency stop bands and broaden primitive Bragg stop bands by virtue of unique interleaved electrical configurations and the SSDI technique which has the unique feature of realizing automatic impedance adaptation with a small inductance. Finite element modeling of a Timoshenko electromechanical beam structure is also presented for validating dispersion properties of the structure. Both theoretical and experimental results demonstrate that the proposed beam structure not only shows better vibration and wave propagation attenuation than the smart beam structure with independent switched networks, but also has technical simplicity of requiring only half of the number of switches than the independent switched network needs.

The circadian rhythm induced by the heterogeneous network structure of the suprachiasmatic nucleus

NASA Astrophysics Data System (ADS)

Gu, Changgui; Yang, Huijie

2016-05-01

In mammals, the master clock is located in the suprachiasmatic nucleus (SCN), which is composed of about 20 000 nonidentical neuronal oscillators expressing different intrinsic periods. These neurons are coupled through neurotransmitters to form a network consisting of two subgroups, i.e., a ventrolateral (VL) subgroup and a dorsomedial (DM) subgroup. The VL contains about 25% SCN neurons that receive photic input from the retina, and the DM comprises the remaining 75% SCN neurons which are coupled to the VL. The synapses from the VL to the DM are evidently denser than that from the DM to the VL, in which the VL dominates the DM. Therefore, the SCN is a heterogeneous network where the neurons of the VL are linked with a large number of SCN neurons. In the present study, we mimicked the SCN network based on Goodwin model considering four types of networks including an all-to-all network, a Newman-Watts (NW) small world network, an Erdös-Rényi (ER) random network, and a Barabási-Albert (BA) scale free network. We found that the circadian rhythm was induced in the BA, ER, and NW networks, while the circadian rhythm was absent in the all-to-all network with weak cellular coupling, where the amplitude of the circadian rhythm is largest in the BA network which is most heterogeneous in the network structure. Our finding provides an alternative explanation for the induction or enhancement of circadian rhythm by the heterogeneity of the network structure.

The Gaussian Graphical Model in Cross-Sectional and Time-Series Data.

PubMed

Epskamp, Sacha; Waldorp, Lourens J; Mõttus, René; Borsboom, Denny

2018-04-16

We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential causal relationships between observed variables. We describe the utility in three kinds of psychological data sets: data sets in which consecutive cases are assumed independent (e.g., cross-sectional data), temporally ordered data sets (e.g., n = 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In time-series analysis, the GGM can be used to model the residual structure of a vector-autoregression analysis (VAR), also termed graphical VAR. Two network models can then be obtained: a temporal network and a contemporaneous network. When analyzing data from multiple subjects, a GGM can also be formed on the covariance structure of stationary means-the between-subjects network. We discuss the interpretation of these models and propose estimation methods to obtain these networks, which we implement in the R packages graphicalVAR and mlVAR. The methods are showcased in two empirical examples, and simulation studies on these methods are included in the supplementary materials.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Grassroots inter-professional networks: the case of organizing care for older cancer patients.

PubMed

Bagayogo, Fatou Farima; Lepage, Annick; Denis, Jean-Louis; Lamothe, Lise; Lapointe, Liette; Vedel, Isabelle

2016-09-19

Purpose The purpose of this paper of inter-professional networks is to analyze the evolution of relationships between professional groups enacting new forms of collaboration to address clinical imperatives. Design/methodology/approach This paper uses a case study based on semi-structured interviews with physicians and nurses, document analysis and informal discussions. Findings This study documents how two inter-professional networks were developed through professional agency. The findings show that the means by which networks are developed influence the form of collaboration therein. One of the networks developed from day-to-day, immediately relevant, exchange, for patient care. The other one developed from more formal and infrequent research and training exchanges that were seen as less decisive in facilitating patient care. The latter resulted in a loosely knit network based on a small number of ad hoc referrals while the other resulted in a tightly knit network based on frequent referrals and advice seeking. Practical implications Developing inter-professional networks likely require a sustained phase of interpersonal contacts characterized by persuasion, knowledge sharing, skill demonstration and trust building from less powerful professional groups to obtain buy-in from more powerful professional groups. The nature of the collaboration in any resulting network depends largely on the nature of these initial contacts. Originality/value The literature on inter-professional healthcare networks focusses on mandated networks such as NHS managed care networks. There is a lack of research on inter-professional networks that emerged from the bottom up at the initiative of healthcare professionals in response to clinical imperatives. This study looks at some forms of collaboration that these "grass-root" initiatives engender and how they are consolidated.

Do governance choices matter in health care networks?: an exploratory configuration study of health care networks

PubMed Central

2013-01-01

Background Health care networks are widely used and accepted as an organizational form that enables integrated care as well as dealing with complex matters in health care. However, research on the governance of health care networks lags behind. The research aim of our study is to explore the type and importance of governance structure and governance mechanisms for network effectiveness. Methods The study has a multiple case study design and covers 22 health care networks. Using a configuration view, combinations of network governance and other network characteristics were studied on the level of the network. Based on interview and questionnaire data, network characteristics were identified and patterns in the data looked for. Results Neither a dominant (or optimal) governance structure or mechanism nor a perfect fit among governance and other characteristics were revealed, but a number of characteristics that need further study might be related to effective networks such as the role of governmental agencies, legitimacy, and relational, hierarchical, and contractual governance mechanisms as complementary factors. Conclusions Although the results emphasize the situational character of network governance and effectiveness, they give practitioners in the health care sector indications of which factors might be more or less crucial for network effectiveness. PMID:23800334

Nonlinear channel equalization for QAM signal constellation using artificial neural networks.

PubMed

Patra, J C; Pal, R N; Baliarsingh, R; Panda, G

1999-01-01

Application of artificial neural networks (ANN's) to adaptive channel equalization in a digital communication system with 4-QAM signal constellation is reported in this paper. A novel computationally efficient single layer functional link ANN (FLANN) is proposed for this purpose. This network has a simple structure in which the nonlinearity is introduced by functional expansion of the input pattern by trigonometric polynomials. Because of input pattern enhancement, the FLANN is capable of forming arbitrarily nonlinear decision boundaries and can perform complex pattern classification tasks. Considering channel equalization as a nonlinear classification problem, the FLANN has been utilized for nonlinear channel equalization. The performance of the FLANN is compared with two other ANN structures [a multilayer perceptron (MLP) and a polynomial perceptron network (PPN)] along with a conventional linear LMS-based equalizer for different linear and nonlinear channel models. The effect of eigenvalue ratio (EVR) of input correlation matrix on the equalizer performance has been studied. The comparison of computational complexity involved for the three ANN structures is also provided.

Pattern Storage, Bifurcations, and Groupwise Correlation Structure of an Exactly Solvable Asymmetric Neural Network Model.

PubMed

Fasoli, Diego; Cattani, Anna; Panzeri, Stefano

2018-05-01

Despite their biological plausibility, neural network models with asymmetric weights are rarely solved analytically, and closed-form solutions are available only in some limiting cases or in some mean-field approximations. We found exact analytical solutions of an asymmetric spin model of neural networks with arbitrary size without resorting to any approximation, and we comprehensively studied its dynamical and statistical properties. The network had discrete time evolution equations and binary firing rates, and it could be driven by noise with any distribution. We found analytical expressions of the conditional and stationary joint probability distributions of the membrane potentials and the firing rates. By manipulating the conditional probability distribution of the firing rates, we extend to stochastic networks the associating learning rule previously introduced by Personnaz and coworkers. The new learning rule allowed the safe storage, under the presence of noise, of point and cyclic attractors, with useful implications for content-addressable memories. Furthermore, we studied the bifurcation structure of the network dynamics in the zero-noise limit. We analytically derived examples of the codimension 1 and codimension 2 bifurcation diagrams of the network, which describe how the neuronal dynamics changes with the external stimuli. This showed that the network may undergo transitions among multistable regimes, oscillatory behavior elicited by asymmetric synaptic connections, and various forms of spontaneous symmetry breaking. We also calculated analytically groupwise correlations of neural activity in the network in the stationary regime. This revealed neuronal regimes where, statistically, the membrane potentials and the firing rates are either synchronous or asynchronous. Our results are valid for networks with any number of neurons, although our equations can be realistically solved only for small networks. For completeness, we also derived the network equations in the thermodynamic limit of infinite network size and we analytically studied their local bifurcations. All the analytical results were extensively validated by numerical simulations.

Organogel formation rationalized by Hansen solubility parameters: influence of gelator structure.

PubMed

Bonnet, Julien; Suissa, Gad; Raynal, Matthieu; Bouteiller, Laurent

2015-03-21

Some organic compounds form gels in liquids by forming a network of anisotropic fibres. Based on extensive solubility tests of four gelators of similar structures, and on Hansen solubility parameter formalism, we have probed the quantitative effect of a structural variation of the gelator structure on its gel formation ability. Increasing the length of an alkyl group of the gelator obviously reduces its polarity, which leads to a gradual shift of its solubility sphere towards lower δp and δh values. At the same time, its gelation sphere is shifted - to a much stronger extent - towards larger δp and δh values.

A diffusion perspective on temporal networks: A case study on a supermarket

NASA Astrophysics Data System (ADS)

Deng, Shiguo; Qiu, Lu; Yang, Yue; Yang, Huijie

2016-01-01

From a large amount of records, one can extract behavioral characteristics of a social system at different scales. Theoretically, it can help us to know how the global behavior of a social system is formed from individual activities. Practically, it can be used to optimize and even to control the social system. Complicated relationships between the individuals form a network, which evolves with time. The behavior of the system can be accordingly understood in the framework of temporal network. In the present paper, instead of focusing on microscopic structures, we develop a framework to investigate temporal networks from the viewpoint of diffusion process, in which each snapshot network is divided into groups and the ID number of the group a node belongs to is used to measure its state. By this way trajectories of the nodes form an ensemble of realizations of a stochastic process. As an illustration, we investigate the diffusion behavior of a supermarket. One can find that with the increase of time the customers cluster and separate into different groups. Meanwhile, the system evolves in a significant order way, instead of a complete random one.

From social integration to health: Durkheim in the new millennium.

PubMed

Berkman, L F; Glass, T; Brissette, I; Seeman, T E

2000-09-01

It is widely recognized that social relationships and affiliation have powerful effects on physical and mental health. When investigators write about the impact of social relationships on health, many terms are used loosely and interchangeably including social networks, social ties and social integration. The aim of this paper is to clarify these terms using a single framework. We discuss: (1) theoretical orientations from diverse disciplines which we believe are fundamental to advancing research in this area; (2) a set of definitions accompanied by major assessment tools; and (3) an overarching model which integrates multilevel phenomena. Theoretical orientations that we draw upon were developed by Durkheim whose work on social integration and suicide are seminal and John Bowlby, a psychiatrist who developed attachment theory in relation to child development and contemporary social network theorists. We present a conceptual model of how social networks impact health. We envision a cascading causal process beginning with the macro-social to psychobiological processes that are dynamically linked together to form the processes by which social integration effects health. We start by embedding social networks in a larger social and cultural context in which upstream forces are seen to condition network structure. Serious consideration of the larger macro-social context in which networks form and are sustained has been lacking in all but a small number of studies and is almost completely absent in studies of social network influences on health. We then move downstream to understand the influences network structure and function have on social and interpersonal behavior. We argue that networks operate at the behavioral level through four primary pathways: (1) provision of social support; (2) social influence; (3) on social engagement and attachment; and (4) access to resources and material goods.

The discovery of structural form

PubMed Central

Kemp, Charles; Tenenbaum, Joshua B.

2008-01-01

Algorithms for finding structure in data have become increasingly important both as tools for scientific data analysis and as models of human learning, yet they suffer from a critical limitation. Scientists discover qualitatively new forms of structure in observed data: For instance, Linnaeus recognized the hierarchical organization of biological species, and Mendeleev recognized the periodic structure of the chemical elements. Analogous insights play a pivotal role in cognitive development: Children discover that object category labels can be organized into hierarchies, friendship networks are organized into cliques, and comparative relations (e.g., “bigger than” or “better than”) respect a transitive order. Standard algorithms, however, can only learn structures of a single form that must be specified in advance: For instance, algorithms for hierarchical clustering create tree structures, whereas algorithms for dimensionality-reduction create low-dimensional spaces. Here, we present a computational model that learns structures of many different forms and that discovers which form is best for a given dataset. The model makes probabilistic inferences over a space of graph grammars representing trees, linear orders, multidimensional spaces, rings, dominance hierarchies, cliques, and other forms and successfully discovers the underlying structure of a variety of physical, biological, and social domains. Our approach brings structure learning methods closer to human abilities and may lead to a deeper computational understanding of cognitive development. PMID:18669663

Chemically programmed self-sorting of gelator networks.

PubMed

Morris, Kyle L; Chen, Lin; Raeburn, Jaclyn; Sellick, Owen R; Cotanda, Pepa; Paul, Alison; Griffiths, Peter C; King, Stephen M; O'Reilly, Rachel K; Serpell, Louise C; Adams, Dave J

2013-01-01

Controlling the order and spatial distribution of self-assembly in multicomponent supramolecular systems could underpin exciting new functional materials, but it is extremely challenging. When a solution of different components self-assembles, the molecules can either coassemble, or self-sort, where a preference for like-like intermolecular interactions results in coexisting, homomolecular assemblies. A challenge is to produce generic and controlled 'one-pot' fabrication methods to form separate ordered assemblies from 'cocktails' of two or more self-assembling species, which might have relatively similar molecular structures and chemistry. Self-sorting in supramolecular gel phases is hence rare. Here we report the first example of the pH-controlled self-sorting of gelators to form self-assembled networks in water. Uniquely, the order of assembly can be predefined. The assembly of each component is preprogrammed by the pK(a) of the gelator. This pH-programming method will enable higher level, complex structures to be formed that cannot be accessed by simple thermal gelation.

Novel transformation-based response prediction of shear building using interval neural network

NASA Astrophysics Data System (ADS)

Chakraverty, S.; Sahoo, Deepti Moyi

2017-04-01

Present paper uses powerful technique of interval neural network (INN) to simulate and estimate structural response of multi-storey shear buildings subject to earthquake motion. The INN is first trained for a real earthquake data, viz., the ground acceleration as input and the numerically generated responses of different floors of multi-storey buildings as output. Till date, no model exists to handle positive and negative data in the INN. As such here, the bipolar data in [ -1, 1] are converted first to unipolar form, i.e., to [0, 1] by means of a novel transformation for the first time to handle the above training patterns in normalized form. Once the training is done, again the unipolar data are converted back to its bipolar form by using the inverse transformation. The trained INN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by INN model are good for practical purposes.

Resolving Structural Variability in Network Models and the Brain

PubMed Central

Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

2014-01-01

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data. PMID:24675546

Microstructural properties and evolution of nanoclusters in liquid Si during a rapid cooling process

NASA Astrophysics Data System (ADS)

Gao, T.; Hu, X.; Li, Y.; Tian, Z.; Xie, Q.; Chen, Q.; Liang, Y.; Luo, X.; Ren, L.; Luo, J.

2017-11-01

The formation of amorphous structures in Si during the rapid quenching process was studied based on molecular dynamics simulation by using the Stillinger-Weber potential. The evolution characteristics of nanoclusters during the solidification were analyzed by several structural analysis methods. The amorphous Si has been formed with many tetrahedral clusters and few nanoclusters. During the solidification, tetrahedral polyhedrons affect the local structures by their different positions and connection modes. The main kinds of polyhedrons randomly linked with one another to form an amorphous network structures in the system. The structural evolution of crystal nanocluster demonstrates that the nanocluster has difficulty to growth because of the high cooling rate of 1012 K/s.

Structure-Based Network Analysis of Activation Mechanisms in the ErbB Family of Receptor Tyrosine Kinases: The Regulatory Spine Residues Are Global Mediators of Structural Stability and Allosteric Interactions

PubMed Central

James, Kevin A.; Verkhivker, Gennady M.

2014-01-01

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues. PMID:25427151

A scaling law for random walks on networks

PubMed Central

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-01-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics. PMID:25311870

A scaling law for random walks on networks

NASA Astrophysics Data System (ADS)

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

A scaling law for random walks on networks.

PubMed

Perkins, Theodore J; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-14

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

Organization and hierarchy of the human functional brain network lead to a chain-like core.

PubMed

Mastrandrea, Rossana; Gabrielli, Andrea; Piras, Fabrizio; Spalletta, Gianfranco; Caldarelli, Guido; Gili, Tommaso

2017-07-07

The brain is a paradigmatic example of a complex system: its functionality emerges as a global property of local mesoscopic and microscopic interactions. Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise. Here we present the analysis of functional magnetic resonance imaging data from forty healthy humans at rest for the investigation of the basal scaffold of the functional brain network organization. We show how brain regions tend to coordinate by forming a highly hierarchical chain-like structure of homogeneously clustered anatomical areas. A maximum spanning tree approach revealed the centrality of the occipital cortex and the peculiar aggregation of cerebellar regions to form a closed core. We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.

Stimulation-Based Control of Dynamic Brain Networks

PubMed Central

Pasqualetti, Fabio; Gu, Shi; Cieslak, Matthew

2016-01-01

The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement. PMID:27611328

Growing multiplex networks with arbitrary number of layers

NASA Astrophysics Data System (ADS)

Momeni, Naghmeh; Fotouhi, Babak

2015-12-01

This paper focuses on the problem of growing multiplex networks. Currently, the results on the joint degree distribution of growing multiplex networks present in the literature pertain to the case of two layers and are confined to the special case of homogeneous growth and are limited to the state state (that is, the limit of infinite size). In the present paper, we first obtain closed-form solutions for the joint degree distribution of heterogeneously growing multiplex networks with arbitrary number of layers in the steady state. Heterogeneous growth means that each incoming node establishes different numbers of links in different layers. We consider both uniform and preferential growth. We then extend the analysis of the uniform growth mechanism to arbitrary times. We obtain a closed-form solution for the time-dependent joint degree distribution of a growing multiplex network with arbitrary initial conditions. Throughout, theoretical findings are corroborated with Monte Carlo simulations. The results shed light on the effects of the initial network on the transient dynamics of growing multiplex networks and takes a step towards characterizing the temporal variations of the connectivity of growing multiplex networks, as well as predicting their future structural properties.

Nano-engineered intrapores in nanoparticles of PtNi networks for increased oxygen reduction reaction activity

NASA Astrophysics Data System (ADS)

Ding, Jieting; Ji, Shan; Wang, Hui; Key, Julian; Brett, Dan J. L.; Wang, Rongfang

2018-01-01

Network-like metallic alloys of solid nanoparticles have been frequently reported as promising electrocatalysts for fuel cells. The three-dimensional structure of such networks is rich in pores in the form of voids between nanoparticles, which collectively expose a large surface area for catalytic activity. Herein, we present a novel solution to this problem using a precursor comprising a flocculent core-shell PtNi@Ni to produce PtNi network catalysts with nanoparticle intraporosity after carefully controlled electrochemical dealloying. Physical characterization shows a hierarchical level of nanoporosity (intrapores within nanoparticles and pores between them) evolves during the controlled electrochemical dealloying, and that a Pt-rich surface also forms after 22 cycles of Ni leaching. In ORR cycling, the PtNi networks gain 4-fold activity in both jECSA and jmass over a state of the art Pt/C electrocatalyst, and also significantly exceed previously reported PtNi networks. In ORR degradation tests, the PtNi networks also proved stable, dropping by 30.4% and 62.6% in jECSA and jmass respectively. The enhanced performance of the catalyst is evident, and we also propose that the presented synthesis procedure can be generally applied to developing other metallic networks.

Establishing and sustaining a biorepository network in Israel: challenges and progress.

PubMed

Cohen, Yehudit; Almog, Ronit; Onn, Amir; Itzhaki-Alfia, Ayelet; Meir, Karen

2013-12-01

Over the past 5 years, using European and North American biobanks as models, the grass-roots establishment of independently operating biobanks has occurred virtually simultaneously in large Israeli teaching hospitals. The process of establishing a national biorepository network in Israel has progressed slowly, sustained mainly by a few proponents working together on a personal level. Slow progress has been due to limited funding and the lack of a legal framework specific to biobanking activities. Recently, due to increasing pressure from the scientific community, the government has earmarked funds for a national biorepository network, and the structure is now being established. In forming a network, Israel's biobanks face certain difficulties, particularly lack of support. Additional challenges include harmonization of standard operating procedures, database centralization, and use of a common informed consent form. In this article, we highlight some of the issues faced by Israel's biobank managers in establishing and sustaining a functional biobank network, information that could provide guidance for other small countries with limited resources.

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors

PubMed Central

Lee, Dongwook; Seo, Jiwon

2014-01-01

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance. PMID:25492227

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors

NASA Astrophysics Data System (ADS)

Lee, Dongwook; Seo, Jiwon

2014-12-01

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance.

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors.

PubMed

Lee, Dongwook; Seo, Jiwon

2014-12-10

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance.

Theoretical predictions of a bucky-diamond SiC cluster.

PubMed

Yu, Ming; Jayanthi, C S; Wu, S Y

2012-06-15

A study of structural relaxations of Si(n)C(m) clusters corresponding to different compositions, different relative arrangements of Si/C atoms, and different types of initial structure, reveals that the Si(n)C(m) bucky-diamond structure can be obtained for an initial network structure constructed from a truncated bulk 3C-SiC for a magic composition corresponding to n = 68 and m = 79. This study was performed using a semi-empirical Hamiltonian (SCED-LCAO) since it allowed an extensive search of different types of initial structures. However, the bucky-diamond structure predicted by this method was also confirmed by a more accurate density functional theory (DFT) based method. The bucky-diamond structure exhibited by a SiC-based system represents an interesting paradigm where a Si atom can form three-coordinated as well as four-coordinated networks with carbon atoms and vice versa and with both types of network co-existing in the same structure. Specifically, the bucky-diamond structure of the Si(68)C(79) cluster consists of a 35-atom diamond-like inner core (four-atom coordinations) suspended inside a 112-atom fullerene-like shell (three-atom coordinations).

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

PubMed

Pancaldi, Vera; Carrillo-de-Santa-Pau, Enrique; Javierre, Biola Maria; Juan, David; Fraser, Peter; Spivakov, Mikhail; Valencia, Alfonso; Rico, Daniel

2016-07-08

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

Metallic carbon materials

DOEpatents

Cohen, Marvin Lou; Crespi, Vincent Henry; Louie, Steven Gwon Sheng; Zettl, Alexander Karlwalter

1999-01-01

Novel metallic forms of planar carbon are described, as well as methods of designing and making them. Nonhexagonal arrangements of carbon are introduced into a graphite carbon network essentially without destroying the planar structure. Specifically a form of carbon comprising primarily pentagons and heptagons, and having a large density of states at the Fermi level is described. Other arrangements of pentagons and heptagons that include some hexagons, and structures incorporating squares and octagons are additionally disclosed. Reducing the bond angle symmetry associated with a hexagonal arrangement of carbons increases the likelihood that the carbon material will have a metallic electron structure.

The structural and electronic properties of amorphous HgCdTe from first-principles calculations

NASA Astrophysics Data System (ADS)

Zhao, Huxian; Chen, Xiaoshuang; Lu, Jianping; Shu, Haibo; Lu, Wei

2014-01-01

Amorphous mercury cadmium telluride (a-MCT) model structures, with x being 0.125 and 0.25, are obtained from first-principles calculations. We generate initial structures by computation alchemy method. It is found that most atoms in the network of amorphous structures tend to be fourfold and form tetrahedral structures, implying that the chemical ordered continuous random network with some coordination defects is the ideal structure for a-MCT. The electronic structure is also concerned. The gap is found to be 0.30 and 0.26 eV for a-Hg0.875Cd0.125Te and a-Hg0.75Cd0.25Te model structures, independent of the composition. By comparing with the properties of crystalline MCT with the same composition, we observe a blue-shift of energy band gap. The localization of tail states and its atomic origin are also discussed.

Carbon atom clusters in random covalent networks: PAHs as an integral component of interstellar HAC

NASA Astrophysics Data System (ADS)

Jones, A. P.

1990-11-01

Using a random covalent network (RCN) model for the structure of hydrogenated amorphorous carbon (HAC) and the available laboratory data, it is shown that aromatic species are a natural consequence of the structure of amorphous carbons formed in the laboratory. Amorphous carbons in the interstellar medium are therefore likely to contain a significant fraction of Polycyclic aromatic hydrocarbons (PAH) species within the 'amorphous' matrix making up these materials. This aromatic component can be produced in situ during the accretion of gas phase carbon species on to grains in the interstellar medium under hydrogen-poor conditions, or subsequent to deposition as a result of photolysis (photodarkening). The fraction of interstellar carbon present in HAC in the form of PAHs, based upon a RCN model, is consistent with the observed Unidentified infrared (UIR) emission features.

Spectroscopic study of uracil, 1-methyluracil and 1-methyl-4-thiouracil: Hydrogen bond interactions in crystals and ab-initio molecular dynamics

NASA Astrophysics Data System (ADS)

Brela, Mateusz Z.; Boczar, Marek; Malec, Leszek M.; Wójcik, Marek J.; Nakajima, Takahito

2018-05-01

Hydrogen bond networks in uracil, 1-methyluracil and 1-methyl-4-thiouracil were studied by ab initio molecular dynamics as well as analysis of the orbital interactions. The power spectra calculated by ab initio molecular dynamics for atoms involved in hydrogen bonds were analyzed. We calculated spectra by using anharmonic approximation based on the autocorrelation function of the atom positions obtained from the Born-Oppenheimer simulations. Our results show the differences between hydrogen bond networks in uracil and its methylated derivatives. The studied methylated derivatives, 1-methyluracil as well as 1-methyl-4-thiouracil, form dimeric structures in the crystal phase, while uracil does not form that kind of structures. The presence of sulfur atom instead oxygen atom reflects weakness of the hydrogen bonds that build dimers.

Cardiac myocyte diversity and a fibroblast network in the junctional region of the zebrafish heart revealed by transmission and serial block-face scanning electron microscopy.

PubMed

Lafontant, Pascal J; Behzad, Ali R; Brown, Evelyn; Landry, Paul; Hu, Norman; Burns, Alan R

2013-01-01

The zebrafish has emerged as an important model of heart development and regeneration. While the structural characteristics of the developing and adult zebrafish ventricle have been previously studied, little attention has been paid to the nature of the interface between the compact and spongy myocardium. Here we describe how these two distinct layers are structurally and functionally integrated. We demonstrate by transmission electron microscopy that this interface is complex and composed primarily of a junctional region occupied by collagen, as well as a population of fibroblasts that form a highly complex network. We also describe a continuum of uniquely flattened transitional cardiac myocytes that form a circumferential plate upon which the radially-oriented luminal trabeculae are anchored. In addition, we have uncovered within the transitional ring a subpopulation of markedly electron dense cardiac myocytes. At discrete intervals the transitional cardiac myocytes form contact bridges across the junctional space that are stabilized through localized desmosomes and fascia adherentes junctions with adjacent compact cardiac myocytes. Finally using serial block-face scanning electron microscopy, segmentation and volume reconstruction, we confirm the three-dimensional nature of the junctional region as well as the presence of the sheet-like fibroblast network. These ultrastructural studies demonstrate the previously unrecognized complexity with which the compact and spongy layers are structurally integrated, and provide a new basis for understanding development and regeneration in the zebrafish heart.

Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

PubMed

Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

2016-11-30

Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

Network topology for the formation of solvated electrons in binary CaO–Al2O3 composition glasses

PubMed Central

Akola, Jaakko; Kohara, Shinji; Ohara, Koji; Fujiwara, Akihiko; Watanabe, Yasuhiro; Masuno, Atsunobu; Usuki, Takeshi; Kubo, Takashi; Nakahira, Atsushi; Nitta, Kiyofumi; Uruga, Tomoya; Weber, J. K. Richard; Benmore, Chris J.

2013-01-01

Glass formation in the CaO–Al2O3 system represents an important phenomenon because it does not contain typical network-forming cations. We have produced structural models of CaO–Al2O3 glasses using combined density functional theory–reverse Monte Carlo simulations and obtained structures that reproduce experiments (X-ray and neutron diffraction, extended X-ray absorption fine structure) and result in cohesive energies close to the crystalline ground states. The O–Ca and O–Al coordination numbers are similar in the eutectic 64 mol % CaO (64CaO) glass [comparable to 12CaO·7Al2O3 (C12A7)], and the glass structure comprises a topologically disordered cage network with large-sized rings. This topologically disordered network is the signature of the high glass-forming ability of 64CaO glass and high viscosity in the melt. Analysis of the electronic structure reveals that the atomic charges for Al are comparable to those for Ca, and the bond strength of Al–O is stronger than that of Ca–O, indicating that oxygen is more weakly bound by cations in CaO-rich glass. The analysis shows that the lowest unoccupied molecular orbitals occurs in cavity sites, suggesting that the C12A7 electride glass [Kim SW, Shimoyama T, Hosono H (2011) Science 333(6038):71–74] synthesized from a strongly reduced high-temperature melt can host solvated electrons and bipolarons. Calculations of 64CaO glass structures with few subtracted oxygen atoms (additional electrons) confirm this observation. The comparable atomic charges and coordination of the cations promote more efficient elemental mixing, and this is the origin of the extended cage structure and hosted solvated (trapped) electrons in the C12A7 glass. PMID:23723350

Network topology for the formation of solvated electrons in binary CaO-Al2O3 composition glasses.

PubMed

Akola, Jaakko; Kohara, Shinji; Ohara, Koji; Fujiwara, Akihiko; Watanabe, Yasuhiro; Masuno, Atsunobu; Usuki, Takeshi; Kubo, Takashi; Nakahira, Atsushi; Nitta, Kiyofumi; Uruga, Tomoya; Weber, J K Richard; Benmore, Chris J

2013-06-18

Glass formation in the CaO-Al2O3 system represents an important phenomenon because it does not contain typical network-forming cations. We have produced structural models of CaO-Al2O3 glasses using combined density functional theory-reverse Monte Carlo simulations and obtained structures that reproduce experiments (X-ray and neutron diffraction, extended X-ray absorption fine structure) and result in cohesive energies close to the crystalline ground states. The O-Ca and O-Al coordination numbers are similar in the eutectic 64 mol % CaO (64CaO) glass [comparable to 12CaO·7Al2O3 (C12A7)], and the glass structure comprises a topologically disordered cage network with large-sized rings. This topologically disordered network is the signature of the high glass-forming ability of 64CaO glass and high viscosity in the melt. Analysis of the electronic structure reveals that the atomic charges for Al are comparable to those for Ca, and the bond strength of Al-O is stronger than that of Ca-O, indicating that oxygen is more weakly bound by cations in CaO-rich glass. The analysis shows that the lowest unoccupied molecular orbitals occurs in cavity sites, suggesting that the C12A7 electride glass [Kim SW, Shimoyama T, Hosono H (2011) Science 333(6038):71-74] synthesized from a strongly reduced high-temperature melt can host solvated electrons and bipolarons. Calculations of 64CaO glass structures with few subtracted oxygen atoms (additional electrons) confirm this observation. The comparable atomic charges and coordination of the cations promote more efficient elemental mixing, and this is the origin of the extended cage structure and hosted solvated (trapped) electrons in the C12A7 glass.

USSR Report: Machine Tools and Metalworking Equipment.

DTIC Science & Technology

1986-01-23

between satellite stop and the camshaft of the programer unit. The line has 23 positions including 12 automatic ones. Specification of line Number...technological, processes, automated research, etc.) are as follows.: a monochannel based on a shared trunk line, ring, star and tree (polychannel...line or ring networks based on decentralized control of data exchange between subscribers are very robust. A tree -form network has star structure

A Dialogic Action Perspective on Open Collective Inquiry in Online Forums

ERIC Educational Resources Information Center

Jung, Yusun

2012-01-01

In today's networked environment, online forums emerge as a popular form of social structures that have greater opportunities for learning in various organizational contexts. A plethora of studies have investigated the phenomenon to identify antecedent of its success, such as individual characteristics and organizational structure. However,…

Evolution of network architecture in a granular material under compression

NASA Astrophysics Data System (ADS)

Papadopoulos, Lia; Puckett, James G.; Daniels, Karen E.; Bassett, Danielle S.

2016-09-01

As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. Force chains are a prime example of such structures, and are thought to constrain bulk properties such as mechanical stability and acoustic transmission. However, capturing and characterizing the evolving nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. A growing body of work has shown that graph theoretic approaches may provide a useful foundation for tackling these problems. Here, we extend the current approaches by utilizing multilayer networks as a framework for directly quantifying the progression of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and interparticle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the changes in this structure throughout the compression process. We separately consider the network of normal and tangential forces, and find that they display a different progression throughout compression. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be achieved by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than a purely local measure of interparticle forces alone. The results discussed throughout this study suggest that these network science techniques may provide a direct way to compare and classify data from systems under different external conditions or with different physical makeup.

How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure

NASA Astrophysics Data System (ADS)

Bettinardi, R. G.; Deco, G.; Karlaftis, V. M.; Van Hartevelt, T. J.; Fernandes, H. M.; Kourtzi, Z.; Kringelbach, M. L.; Zamora-López, G.

2017-04-01

Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.

Nanocarbon networks for advanced rechargeable lithium batteries.

PubMed

Xin, Sen; Guo, Yu-Guo; Wan, Li-Jun

2012-10-16

Carbon is one of the essential elements in energy storage. In rechargeable lithium batteries, researchers have considered many types of nanostructured carbons, such as carbon nanoparticles, carbon nanotubes, graphene, and nanoporous carbon, as anode materials and, especially, as key components for building advanced composite electrode materials. Nanocarbons can form efficient three-dimensional conducting networks that improve the performance of electrode materials suffering from the limited kinetics of lithium storage. Although the porous structure guarantees a fast migration of Li ions, the nanocarbon network can serve as an effective matrix for dispersing the active materials to prevent them from agglomerating. The nanocarbon network also affords an efficient electron pathway to provide better electrical contacts. Because of their structural stability and flexibility, nanocarbon networks can alleviate the stress and volume changes that occur in active materials during the Li insertion/extraction process. Through the elegant design of hierarchical electrode materials with nanocarbon networks, researchers can improve both the kinetic performance and the structural stability of the electrode material, which leads to optimal battery capacity, cycling stability, and rate capability. This Account summarizes recent progress in the structural design, chemical synthesis, and characterization of the electrochemical properties of nanocarbon networks for Li-ion batteries. In such systems, storage occurs primarily in the non-carbon components, while carbon acts as the conductor and as the structural buffer. We emphasize representative nanocarbon networks including those that use carbon nanotubes and graphene. We discuss the role of carbon in enhancing the performance of various electrode materials in areas such as Li storage, Li ion and electron transport, and structural stability during cycling. We especially highlight the use of graphene to construct the carbon conducting network for alloy anodes, such as Si and Ge, to accelerate electron transport, alleviate volume change, and prevent the agglomeration of active nanoparticles. Finally, we describe the power of nanocarbon networks for the next generation rechargeable lithium batteries, including Li-S, Li-O(2), and Li-organic batteries, and provide insights into the design of ideal nanocarbon networks for these devices. In addition, we address the ways in which nanocarbon networks can expand the applications of rechargeable lithium batteries into the emerging fields of stationary energy storage and transportation.

Network analysis of Bogotá’s Ciclovía Recreativa, a self-organized multisectoral community program to promote physical activity in a middle-income country

PubMed Central

Meisel, Jose D; Sarmiento, Olga; Montes, Felipe; Martinez, Edwin O.; Lemoine, Pablo D; Valdivia, Juan A; Brownson, RC; Zarama, Robert

2016-01-01

Purpose Conduct a social network analysis of the health and non-health related organizations that participate in the Bogotá’s Ciclovía Recreativa (Ciclovía). Design Cross sectional study. Setting Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and PA. Subjects 25 organizations that participate in the Ciclovía. Measures Seven variables were examined using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). Analysis The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Results Analysis shows that the most central organizations in the network were outside of the health sector and includes Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Conclusion Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central. PMID:23971523

Formation of porous crystals via viscoelastic phase separation

NASA Astrophysics Data System (ADS)

Tsurusawa, Hideyo; Russo, John; Leocmach, Mathieu; Tanaka, Hajime

2017-10-01

Viscoelastic phase separation of colloidal suspensions can be interrupted to form gels either by glass transition or by crystallization. With a new confocal microscopy protocol, we follow the entire kinetics of phase separation, from homogeneous phase to different arrested states. For the first time in experiments, our results unveil a novel crystallization pathway to sponge-like porous crystal structures. In the early stages, we show that nucleation requires a structural reorganization of the liquid phase, called stress-driven ageing. Once nucleation starts, we observe that crystallization follows three different routes: direct crystallization of the liquid phase, the Bergeron process, and Ostwald ripening. Nucleation starts inside the reorganized network, but crystals grow past it by direct condensation of the gas phase on their surface, driving liquid evaporation, and producing a network structure different from the original phase separation pattern. We argue that similar crystal-gel states can be formed in monatomic and molecular systems if the liquid phase is slow enough to induce viscoelastic phase separation, but fast enough to prevent immediate vitrification. This provides a novel pathway to form nanoporous crystals of metals and semiconductors without dealloying, which may be important for catalytic, optical, sensing, and filtration applications.

Neural network pattern recognition of thermal-signature spectra for chemical defense

NASA Astrophysics Data System (ADS)

Carrieri, Arthur H.; Lim, Pascal I.

1995-05-01

We treat infrared patterns of absorption or emission by nerve and blister agent compounds (and simulants of this chemical group) as features for the training of neural networks to detect the compounds' liquid layers on the ground or their vapor plumes during evaporation by external heating. Training of a four-layer network architecture is composed of a backward-error-propagation algorithm and a gradient-descent paradigm. We conduct testing by feed-forwarding preprocessed spectra through the network in a scaled format consistent with the structure of the training-data-set representation. The best-performance weight matrix (spectral filter) evolved from final network training and testing with software simulation trials is electronically transferred to a set of eight artificial intelligence integrated circuits (ICs') in specific modular form (splitting of weight matrices). This form makes full use of all input-output IC nodes. This neural network computer serves an important real-time detection function when it is integrated into pre-and postprocessing data-handling units of a tactical prototype thermoluminescence sensor now under development at the Edgewood Research, Development, and Engineering Center.

Construction of single-crystalline supramolecular networks of perchlorinated hexa-peri-hexabenzocoronene on Au(111)

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhang, Yanfang; Li, Geng; Lu, Jianchen; Lin, Xiao; Tan, Yuanzhi; Feng, Xinliang; Du, Shixuan; Müllen, Klaus; Gao, Hong-Jun

2015-03-01

The self-assembly of the perchlorinated hexa-peri-hexabenzocoronene (PCHBC) molecules on Au(111) has been studied by a low temperature scanning tunneling microscopy (STM) combining with density functional theory based first principle calculations. Highly ordered supramolecular networks with single domains limited by the terraces are formed on Au(111) substrate. High resolution images of the PCHBC molecules, confirmed by first principle simulations, are obtained. It reveals the close-packed arrangement of the PCHBC molecules on Au(111). The calculated charge distribution of PCHBC molecules shows the existence of attractive halogen-halogen interaction between neighboring molecules. Compared with the disordered adsorption of hexa-peri-hexabenzocoronene on Au(111), we conclude that the formation of attractive ClCl interactions between neighbors is the key factor to form the highly ordered, close-packed networks. Due to the steric hindrance resulted from the peripheral chlorine atoms, the PCHBC molecule is contorted and forms the doubly concave conformation, which is different from the hexa-peri-hexabenzocoronene with a planar structure. By using this supramolecular network as a template, we deposited C60 molecules on it at room temperature with low coverage. The STM images taken at low temperature show that the C60 molecules are mono-dispersed on the networks and adsorb on top of the PCHBC molecules, forming a typical concave-convex host-guest system.

Water at silica/liquid water interfaces investigated by DFT-MD simulations

NASA Astrophysics Data System (ADS)

Gaigeot, Marie-Pierre

This talk is dedicated to probing the microscopic structural organization of water at silica/liquid water interfaces including electrolytes by first principles DFT-based molecular dynamics simulations (DFT-MD). We will present our very recent DFT-MD simulations of electrolytic (KCl, NaCl, NaI) silica/liquid water interfaces in order to unravel the intertwined structural properties of water and electrolytes at the crystalline quartz/liquid water and amorphous silica/liquid water interfaces. DFT-MD simulations provide direct knowledge of the structural organization of water and the H-Bond network formed between the water molecules within the different water layers above the silica surface. One can furthermore extract vibrational signatures of the water molecules within the interfacial layers from the DFT-MD simulations, especially non-linear SFG (Sum Frequency generation) signatures that are active at solid/liquid interfaces. The strength of the simulated spectra is that a detailed analysis of the signatures in terms of the water/water H-Bond networks formed within the interfacial water layers and in terms of the water/silica or water/electrolytes H-Bond networks can be given. Comparisons of SFG spectra between quartz/water/electrolytes and amorphous silica/water/electrolytes interfaces allow us to definitely conclude on how the structural arrangements of liquid water at these electrolytic interfaces modulate the final spectroscopic signatures. Invited speaker.

On the Shortcomings of Our Organisational Forms: With Implications for Educational Change and School Improvement

ERIC Educational Resources Information Center

Waite, Duncan

2010-01-01

This article informs school improvement and educational change from a radically different perspective. Building upon work done recently in neural psychology, primatology and ethology, the article examines four common and general types of organisational form: the cell, the silo, the pyramidal, and the network types of organisational structures.…

Topological Structure of the Space of Phenotypes: The Case of RNA Neutral Networks

PubMed Central

Aguirre, Jacobo; Buldú, Javier M.; Stich, Michael; Manrubia, Susanna C.

2011-01-01

The evolution and adaptation of molecular populations is constrained by the diversity accessible through mutational processes. RNA is a paradigmatic example of biopolymer where genotype (sequence) and phenotype (approximated by the secondary structure fold) are identified in a single molecule. The extreme redundancy of the genotype-phenotype map leads to large ensembles of RNA sequences that fold into the same secondary structure and can be connected through single-point mutations. These ensembles define neutral networks of phenotypes in sequence space. Here we analyze the topological properties of neutral networks formed by 12-nucleotides RNA sequences, obtained through the exhaustive folding of sequence space. A total of 412 sequences fragments into 645 subnetworks that correspond to 57 different secondary structures. The topological analysis reveals that each subnetwork is far from being random: it has a degree distribution with a well-defined average and a small dispersion, a high clustering coefficient, and an average shortest path between nodes close to its minimum possible value, i.e. the Hamming distance between sequences. RNA neutral networks are assortative due to the correlation in the composition of neighboring sequences, a feature that together with the symmetries inherent to the folding process explains the existence of communities. Several topological relationships can be analytically derived attending to structural restrictions and generic properties of the folding process. The average degree of these phenotypic networks grows logarithmically with their size, such that abundant phenotypes have the additional advantage of being more robust to mutations. This property prevents fragmentation of neutral networks and thus enhances the navigability of sequence space. In summary, RNA neutral networks show unique topological properties, unknown to other networks previously described. PMID:22028856

Food-web structure and network theory: The role of connectance and size

PubMed Central

Dunne, Jennifer A.; Williams, Richard J.; Martinez, Neo D.

2002-01-01

Networks from a wide range of physical, biological, and social systems have been recently described as “small-world” and “scale-free.” However, studies disagree whether ecological networks called food webs possess the characteristic path lengths, clustering coefficients, and degree distributions required for membership in these classes of networks. Our analysis suggests that the disagreements are based on selective use of relatively few food webs, as well as analytical decisions that obscure important variability in the data. We analyze a broad range of 16 high-quality food webs, with 25–172 nodes, from a variety of aquatic and terrestrial ecosystems. Food webs generally have much higher complexity, measured as connectance (the fraction of all possible links that are realized in a network), and much smaller size than other networks studied, which have important implications for network topology. Our results resolve prior conflicts by demonstrating that although some food webs have small-world and scale-free structure, most do not if they exceed a relatively low level of connectance. Although food-web degree distributions do not display a universal functional form, observed distributions are systematically related to network connectance and size. Also, although food webs often lack small-world structure because of low clustering, we identify a continuum of real-world networks including food webs whose ratios of observed to random clustering coefficients increase as a power–law function of network size over 7 orders of magnitude. Although food webs are generally not small-world, scale-free networks, food-web topology is consistent with patterns found within those classes of networks. PMID:12235364

Effect of crystals and fibrous network polymer additives on cellular morphology of microcellular foams

NASA Astrophysics Data System (ADS)

Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro

2015-05-01

In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.

Mixed-method Exploration of Social Network Links to Participation

PubMed Central

Kreider, Consuelo M.; Bendixen, Roxanna M.; Mann, William C.; Young, Mary Ellen; McCarty, Christopher

2015-01-01

The people who regularly interact with an adolescent form that youth's social network, which may impact participation. We investigated the relationship of social networks to participation using personal network analysis and individual interviews. The sample included 36 youth, age 11 – 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least one measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within social networks. Findings contribute to understanding the ways social networks are linked to youth participation and suggest the potential of social network factors for predicting rehabilitation outcomes. PMID:26594737

Creating wi-fi bluetooth mesh network for crisis management applications

NASA Astrophysics Data System (ADS)

Al-Tekreeti, Safa; Adams, Christopher; Al-Jawad, Naseer

2010-04-01

This paper proposes a wireless mesh network implementation consisting of both Wi-Fi Ad-Hoc networks as well as Bluetooth Piconet/Scatternet networks, organised in an energy and throughput efficient structure. This type of networks can be easily constructed for Crises management applications, for example in an Earthquake disaster. The motivation of this research is to form mesh network from the mass availability of WiFi and Bluetooth enabled electronic devices such as mobile phones and PC's that are normally present in most regions were major crises occurs. The target of this study is to achieve an effective solution that will enable Wi-Fi and/or Bluetooth nodes to seamlessly configure themselves to act as a bridge between their own network and that of the other network to achieve continuous routing for our proposed mesh networks.

Empirical analysis of online social networks in the age of Web 2.0

NASA Astrophysics Data System (ADS)

Fu, Feng; Liu, Lianghuan; Wang, Long

2008-01-01

Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

SH3 interactome conserves general function over specific form

PubMed Central

Xin, Xiaofeng; Gfeller, David; Cheng, Jackie; Tonikian, Raffi; Sun, Lin; Guo, Ailan; Lopez, Lianet; Pavlenco, Alevtina; Akintobi, Adenrele; Zhang, Yingnan; Rual, Jean-François; Currell, Bridget; Seshagiri, Somasekar; Hao, Tong; Yang, Xinping; Shen, Yun A; Salehi-Ashtiani, Kourosh; Li, Jingjing; Cheng, Aaron T; Bouamalay, Dryden; Lugari, Adrien; Hill, David E; Grimes, Mark L; Drubin, David G; Grant, Barth D; Vidal, Marc; Boone, Charles; Sidhu, Sachdev S; Bader, Gary D

2013-01-01

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form. PMID:23549480

Enhancing response coordination through the assessment of response network structural dynamics

PubMed Central

Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks’ and participants’ structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant’s brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy. PMID:29447192

Distinct roles of a tyrosine-associated hydrogen-bond network in fine-tuning the structure and function of heme proteins: two cases designed for myoglobin.

PubMed

Liao, Fei; Yuan, Hong; Du, Ke-Jie; You, Yong; Gao, Shu-Qin; Wen, Ge-Bo; Lin, Ying-Wu; Tan, Xiangshi

2016-10-20

A hydrogen-bond (H-bond) network, specifically a Tyr-associated H-bond network, plays key roles in regulating the structure and function of proteins, as exemplified by abundant heme proteins in nature. To explore an approach for fine-tuning the structure and function of artificial heme proteins, we herein used myoglobin (Mb) as a model protein and introduced a Tyr residue in the secondary sphere of the heme active site at two different positions (107 and 138). We performed X-ray crystallography, UV-Vis spectroscopy, stopped-flow kinetics, and electron paramagnetic resonance (EPR) studies for the two single mutants, I107Y Mb and F138Y Mb, and compared to that of wild-type Mb under the same conditions. The results showed that both Tyr107 and Tyr138 form a distinct H-bond network involving water molecules and neighboring residues, which fine-tunes ligand binding to the heme iron and enhances the protein stability, respectively. Moreover, the Tyr107-associated H-bond network was shown to fine-tune both H2O2 binding and activation. With two cases demonstrated for Mb, this study suggests that the Tyr-associated H-bond network has distinct roles in regulating the protein structure, properties and functions, depending on its location in the protein scaffold. Therefore, it is possible to design a Tyr-associated H-bond network in general to create other artificial heme proteins with improved properties and functions.

Voltage collapse in complex power grids

PubMed Central

Simpson-Porco, John W.; Dörfler, Florian; Bullo, Francesco

2016-01-01

A large-scale power grid's ability to transfer energy from producers to consumers is constrained by both the network structure and the nonlinear physics of power flow. Violations of these constraints have been observed to result in voltage collapse blackouts, where nodal voltages slowly decline before precipitously falling. However, methods to test for voltage collapse are dominantly simulation-based, offering little theoretical insight into how grid structure influences stability margins. For a simplified power flow model, here we derive a closed-form condition under which a power network is safe from voltage collapse. The condition combines the complex structure of the network with the reactive power demands of loads to produce a node-by-node measure of grid stress, a prediction of the largest nodal voltage deviation, and an estimate of the distance to collapse. We extensively test our predictions on large-scale systems, highlighting how our condition can be leveraged to increase grid stability margins. PMID:26887284

Distinct hippocampal functional networks revealed by tractography-based parcellation.

PubMed

Adnan, Areeba; Barnett, Alexander; Moayedi, Massieh; McCormick, Cornelia; Cohn, Melanie; McAndrews, Mary Pat

2016-07-01

Recent research suggests the anterior and posterior hippocampus form part of two distinct functional neural networks. Here we investigate the structural underpinnings of this functional connectivity difference using diffusion-weighted imaging-based parcellation. Using this technique, we substantiated that the hippocampus can be parcellated into distinct anterior and posterior segments. These structurally defined segments did indeed show different patterns of resting state functional connectivity, in that the anterior segment showed greater connectivity with temporal and orbitofrontal cortex, whereas the posterior segment was more highly connected to medial and lateral parietal cortex. Furthermore, we showed that the posterior hippocampal connectivity to memory processing regions, including the dorsolateral prefrontal cortex, parahippocampal, inferior temporal and fusiform gyri and the precuneus, predicted interindividual relational memory performance. These findings provide important support for the integration of structural and functional connectivity in understanding the brain networks underlying episodic memory.

Evolution of Cooperation in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.

Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.

Origin of an extensive network of non-tectonic synclines in Eocene limestones of the Western Desert, Egypt

NASA Astrophysics Data System (ADS)

Tewksbury, Barbara J.; Tarabees, Elhamy A.; Mehrtens, Charlotte J.

2017-12-01

Satellite images of the Western Desert of Egypt display conspicuous sinuous color patterning that previous workers have interpreted as erosional flutes formed by catastrophic flooding. Our work with high resolution satellite imagery shows that the patterning is not erosional but, rather, the result of a network of thousands of narrow synclines in the Eocene bedrock capping the Limestone Plateau. Synclines form as isolated, 200-400 meter-wide downwarps in otherwise flat-lying strata. Limb dips are shallow, and doubly plunging hinges form multiple basin closures along syncline lengths. Anticlines form ;accidentally; in inter-syncline areas where two adjacent synclines lie close together. Synclines have two dominant orientations, WNW-ESE and NNW-SSE, parallel to two prominent joint and fault sets, and synclines branch, merge, and change orientation along their lengths. Synclines are all at the same scale with neither larger structures nor parasitic structures and are best described as non-tectonic sag synclines. An Egypt-wide inventory reveals that these synclines are both confined to Eocene limestones and developed, albeit it sporadically, over nearly 100,000 km2. The syncline network predates plateau gravels of the Katkut Formation, which have been interpreted as Oligocene or early Miocene in age, and the network is cut by faults related to Western Desert extension associated with Red Sea rifting. The mechanism that caused sag of overlying layers is not clear. Modern karst collapse, subsurface dissolution of evaporites, and collapse of paleokarst are all unlikely mechanisms given the timing of formation and the underlying stratigraphy. Silica diagenesis and downslope mobilization of underlying shales are possibilities, although uncertainty about the origin of silica in the limestones, plus the consistency of syncline orientations over large areas, make these models problematic. Hypogene karst, perhaps related to aggressive fluids associated with basaltic intrusions, may be the model most consistent with the admittedly limited data we currently have for the network.

Evaluating the performance of free-formed surface parts using an analytic network process

NASA Astrophysics Data System (ADS)

Qian, Xueming; Ma, Yanqiao; Liang, Dezhi

2018-03-01

To successfully design parts with a free-formed surface, the critical issue of how to evaluate and select a favourable evaluation strategy before design is raised. The evaluation of free-formed surface parts is a multiple criteria decision-making (MCDM) problem that requires the consideration of a large number of interdependent factors. The analytic network process (ANP) is a relatively new MCDM method that can systematically deal with all kinds of dependences. In this paper, the factors, which come from the life-cycle and influence the design of free-formed surface parts, are proposed. After analysing the interdependence among these factors, a Hybrid ANP (HANP) structure for evaluating the part’s curved surface is constructed. Then, a HANP evaluation of an impeller is presented to illustrate the application of the proposed method.

Shear-thickening behavior of Fe-ZSM5 zeolite slurry and its removal with alumina/boehmites

NASA Astrophysics Data System (ADS)

Liu, Xiao-guang; Li, Yan; Xue, Wen-dong; Sun, Jia-lin; Tang, Qian

2018-06-01

A cryogenic scanning electron microscopy (cryo-SEM) technique was used to explore the shear-thickening behavior of Fe-ZSM5 zeolite pastes and to discover its underlying mechanism. Bare Fe-ZSM5 zeolite samples were found to contain agglomerations, which may break the flow of the pastes and cause shear-thickening behaviors. However, the shear-thickening behaviors can be eliminated by the addition of halloysite and various boehmites because of improved particle packing. Furthermore, compared with pure Fe-ZSM5 zeolite samples and its composite samples with halloysite, the samples with boehmite (Pural SB or Disperal) additions exhibited network structures in their cryo-SEM images; these structures could facilitate the storage and release of flow water, smooth paste flow, and avoid shear-thickening. By contrast, another boehmite (Versal 250) formed agglomerations rather than network structures after being added to the Fe-ZSM5 zeolite paste and resulted in shear-thickening behavior. Consequently, the results suggest that these network structures play key roles in eliminating the shear-thickening behavior.

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations.

PubMed

Jackson, Matthew A; Bonder, Marc Jan; Kuncheva, Zhana; Zierer, Jonas; Fu, Jingyuan; Kurilshikov, Alexander; Wijmenga, Cisca; Zhernakova, Alexandra; Bell, Jordana T; Spector, Tim D; Steves, Claire J

2018-01-01

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

Genetics Home Reference: lattice corneal dystrophy type I

MedlinePlus

... have recurrent corneal erosions, which are caused by separation of particular layers of the cornea from one ... intricate network that forms in the spaces between cells and provides structural support to tissues. The protein ...

The structure of CO 2 hydrate between 0.7 and 1.0 GPa

DOE PAGES

Tulk, Chris A.; Machida, Shinichi; Klug, Dennis D.; ...

2014-11-05

A deuterated sample of CO 2 structure I (sI) clathrate hydrate (CO 2 ∙ 8.3 D 2O) has been formed and neutron diffraction experiments up to 1.0 GPa at 240 K were performed. The sI CO 2 hydrate transformed at 0.7 GPa into the high pressure phase that had been observed previously by Hirai, et al. (J. Phys. Chem. 133, 124511 (2010)) and O. Bollengier et al. (Geochim. Cosmochim. AC. 119, 322 (2013)), but which had not been structurally identified. The current neutron diffraction data were successfully fitted to a filled ice structure with CO 2 molecules filling the watermore » channels. This CO 2+water system has also been investigated using classical molecular dynamics and density functional ab initio methods to provide additional characterization of the high pressure structure. Both models indicate the water network adapts an MH-III ‘like’ filled ice structure with considerable disorder of the orientations of the CO 2molecule. Furthermore, the disorder appears be a direct result of the level of proton disorder in the water network. In contrast to the conclusions of Bollengier et al. our neutron diffraction data shows that the filled ice phase can be recovered to ambient pressure (0.1 MPa) at 96 K, and recrystallization to sI hydrate occurs upon subsequent heating to 150 K, possibly by first forming low density amorphous ice. Unlike other clathrate hydrate systems, which transform from the sI or sII structure to the hexagonal structure (sH) then to the filled ice structure, CO 2 hydrate transforms directly from the sI form to the filled ice structure.« less

The structure of CO 2 hydrate between 0.7 and 1.0 GPa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tulk, C. A.; Machida, S.; Klug, D. D.

A deuterated sample of CO2 structure I (sI) clathrate hydrate (CO2·8.3 D2O) has been formed and neutron diffraction experiments up to 1.0 GPa at 240 K were performed. The sI CO2 hydrate transformed at 0.7 GPa into the high pressure phase that had been observed previously by Hirai et al. [J. Phys. Chem. 133, 124511 (2010)] and Bollengier et al. [Geochim. Cosmochim. Acta 119, 322 (2013)], but which had not been structurally identified. The current neutron diffraction data were successfully fitted to a filled ice structure with CO2 molecules filling the water channels. This CO2+water system has also been investigatedmore » using classical molecular dynamics and density functional ab initio methods to provide additional characterization of the high pressure structure. Both models indicate the water network adapts a MH-III “like” filled ice structure with considerable disorder of the orientations of the CO2 molecule. Furthermore, the disorder appears to be a direct result of the level of proton disorder in the water network. In contrast to the conclusions of Bollengier et al., our neutron diffraction data show that the filled ice phase can be recovered to ambient pressure (0.1 MPa) at 96 K, and recrystallization to sI hydrate occurs upon subsequent heating to 150 K, possibly by first forming low density amorphous ice. Unlike other clathrate hydrate systems, which transform from the sI or sII structure to the hexagonal structure (sH) then to the filled ice structure, CO2 hydrate transforms directly from the sI form to the filled ice structure.« less

The structure of CO{sub 2} hydrate between 0.7 and 1.0 GPa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tulk, C. A.; Molaison, J. J.; Machida, S.

A deuterated sample of CO{sub 2} structure I (sI) clathrate hydrate (CO{sub 2}·8.3 D{sub 2}O) has been formed and neutron diffraction experiments up to 1.0 GPa at 240 K were performed. The sI CO{sub 2} hydrate transformed at 0.7 GPa into the high pressure phase that had been observed previously by Hirai et al. [J. Phys. Chem. 133, 124511 (2010)] and Bollengier et al. [Geochim. Cosmochim. Acta 119, 322 (2013)], but which had not been structurally identified. The current neutron diffraction data were successfully fitted to a filled ice structure with CO{sub 2} molecules filling the water channels. This CO{submore » 2}+water system has also been investigated using classical molecular dynamics and density functional ab initio methods to provide additional characterization of the high pressure structure. Both models indicate the water network adapts a MH-III “like” filled ice structure with considerable disorder of the orientations of the CO{sub 2} molecule. Furthermore, the disorder appears to be a direct result of the level of proton disorder in the water network. In contrast to the conclusions of Bollengier et al., our neutron diffraction data show that the filled ice phase can be recovered to ambient pressure (0.1 MPa) at 96 K, and recrystallization to sI hydrate occurs upon subsequent heating to 150 K, possibly by first forming low density amorphous ice. Unlike other clathrate hydrate systems, which transform from the sI or sII structure to the hexagonal structure (sH) then to the filled ice structure, CO{sub 2} hydrate transforms directly from the sI form to the filled ice structure.« less

The structure of CO 2 hydrate between 0.7 and 1.0 GPa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tulk, Chris A.; Machida, Shinichi; Klug, Dennis D.

A deuterated sample of CO 2 structure I (sI) clathrate hydrate (CO 2 ∙ 8.3 D 2O) has been formed and neutron diffraction experiments up to 1.0 GPa at 240 K were performed. The sI CO 2 hydrate transformed at 0.7 GPa into the high pressure phase that had been observed previously by Hirai, et al. (J. Phys. Chem. 133, 124511 (2010)) and O. Bollengier et al. (Geochim. Cosmochim. AC. 119, 322 (2013)), but which had not been structurally identified. The current neutron diffraction data were successfully fitted to a filled ice structure with CO 2 molecules filling the watermore » channels. This CO 2+water system has also been investigated using classical molecular dynamics and density functional ab initio methods to provide additional characterization of the high pressure structure. Both models indicate the water network adapts an MH-III ‘like’ filled ice structure with considerable disorder of the orientations of the CO 2molecule. Furthermore, the disorder appears be a direct result of the level of proton disorder in the water network. In contrast to the conclusions of Bollengier et al. our neutron diffraction data shows that the filled ice phase can be recovered to ambient pressure (0.1 MPa) at 96 K, and recrystallization to sI hydrate occurs upon subsequent heating to 150 K, possibly by first forming low density amorphous ice. Unlike other clathrate hydrate systems, which transform from the sI or sII structure to the hexagonal structure (sH) then to the filled ice structure, CO 2 hydrate transforms directly from the sI form to the filled ice structure.« less

Low-Dimensional Network Formation in Molten Sodium Carbonate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilding, Martin C.; Wilson, Mark; Alderman, Oliver L. G.

2016-04-15

Molten carbonates are highly inviscid liquids characterized by low melting points and high solubility of rare earth elements and volatile molecules. An understanding of the structure and related properties of these intriguing liquids has been limited to date. We report the results of a study of molten sodium carbonate (Na2CO3) which combines high energy X-ray diffraction, containerless techniques and computer simulation to provide insight into the liquid structure. Total structure factors (F-x(Q)) are collected on the laser-heated carbonate spheres suspended in flowing gases of varying composition in an aerodynamic levitation furnace. The respective partial structure factor contributions to Fx(Q) aremore » obtained by performing molecular dynamics simulations treating the carbonate anions as flexible entities. The carbonate liquid structure is found to be heavily temperature-dependent. At low temperatures a low-dimensional carbonate chain network forms, at T = 1100 K for example similar to 55% of the C atoms form part of a chain. The mean chain lengths decrease as temperature is increased and as the chains become shorter the rotation of the carbonate anions becomes more rapid enhancing the diffusion of Na+ ions.« less

Effect of pH on chitosan hydrogel polymer network structure.

PubMed

Xu, Hongcheng; Matysiak, Silvina

2017-06-29

Chitosan is a molecule that can form water-filled 3D polymer networks with a wide range of applications. A new coarse-grained model for chitosan hydrogel was developed to explore its pH-dependent self-assembly behavior and mechanical properties. Our results indicate that the underlying polymer physical crosslinking pattern induced by solution pH has a significant effect on hydrogel elastic moduli. With this model, we obtain pH-dependent structural and mechanical property changes in agreement with experimental observations, and provide a molecular mechanism behind the changes in polymer crosslinking patterns.

Social network extraction based on Web: 3. the integrated superficial method

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Sitompul, O. S.; Noah, S. A.

2018-03-01

The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n - 1)/2 for n social actors.

Friend suggestion in social network based on user log

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Modelling the public opinion transmission on social networks under opinion leaders

NASA Astrophysics Data System (ADS)

Li, Zuozhi; Li, Meng; Ji, Wanwan

2017-06-01

In this paper, based on Social Network Analysis (SNA), the social network model of opinion leaders influencing the public opinion transmission is explored. The hot event, A Female Driver Was Beaten Due To Lane Change, has characteristics of individual short-term and non-government intervention, which is used to data extraction, and formed of the network structure on opinion leaders influencing the public opinion transmission. And the evolution mechanism are analyzed in the three evolutionary situations. Opinion leaders influence micro-blogging public opinion on social network evolution model shows that this type of network public opinion transmission is largely constrained by opinion leaders, so the opinion leaders behavior supervising on the spread of this public opinion is pivotal, and which has a guiding significance.

Competitive cluster growth in complex networks.

PubMed

Moreira, André A; Paula, Demétrius R; Costa Filho, Raimundo N; Andrade, José S

2006-06-01

In this work we propose an idealized model for competitive cluster growth in complex networks. Each cluster can be thought of as a fraction of a community that shares some common opinion. Our results show that the cluster size distribution depends on the particular choice for the topology of the network of contacts among the agents. As an application, we show that the cluster size distributions obtained when the growth process is performed on hierarchical networks, e.g., the Apollonian network, have a scaling form similar to what has been observed for the distribution of a number of votes in an electoral process. We suggest that this similarity may be due to the fact that social networks involved in the electoral process may also possess an underlining hierarchical structure.

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

PubMed Central

Kraft, Reuben H.; Mckee, Phillip Justin; Dagro, Amy M.; Grafton, Scott T.

2012-01-01

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight. PMID:22915997

The Postsynaptic Density Proteins Homer and Shank Form a Polymeric Network Structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayashi, M.; Tang, C; Verpelli, C

2009-01-01

The postsynaptic density (PSD) is crucial for synaptic functions, but the molecular architecture retaining its structure and components remains elusive. Homer and Shank are among the most abundant scaffolding proteins in the PSD, working synergistically for maturation of dendritic spines. Here, we demonstrate that Homer and Shank, together, form a mesh-like matrix structure. Crystallographic analysis of this region revealed a pair of parallel dimeric coiled coils intercalated in a tail-to-tail fashion to form a tetramer, giving rise to the unique configuration of a pair of N-terminal EVH1 domains at each end of the coiled coil. In neurons, the tetramerization ismore » required for structural integrity of the dendritic spines and recruitment of proteins to synapses. We propose that the Homer-Shank complex serves as a structural framework and as an assembly platform for other PSD proteins.« less

Group percolation in interdependent networks

NASA Astrophysics Data System (ADS)

Wang, Zexun; Zhou, Dong; Hu, Yanqing

2018-03-01

In many real network systems, nodes usually cooperate with each other and form groups to enhance their robustness to risks. This motivates us to study an alternative type of percolation, group percolation, in interdependent networks under attack. In this model, nodes belonging to the same group survive or fail together. We develop a theoretical framework for this group percolation and find that the formation of groups can improve the resilience of interdependent networks significantly. However, the percolation transition is always of first order, regardless of the distribution of group sizes. As an application, we map the interdependent networks with intersimilarity structures, which have attracted much attention recently, onto the group percolation and confirm the nonexistence of continuous phase transitions.

Incoherence-Mediated Remote Synchronization

NASA Astrophysics Data System (ADS)

Zhang, Liyue; Motter, Adilson E.; Nishikawa, Takashi

2017-04-01

In previously identified forms of remote synchronization between two nodes, the intermediate portion of the network connecting the two nodes is not synchronized with them but generally exhibits some coherent dynamics. Here we report on a network phenomenon we call incoherence-mediated remote synchronization (IMRS), in which two noncontiguous parts of the network are identically synchronized while the dynamics of the intermediate part is statistically and information-theoretically incoherent. We identify mirror symmetry in the network structure as a mechanism allowing for such behavior, and show that IMRS is robust against dynamical noise as well as against parameter changes. IMRS may underlie neuronal information processing and potentially lead to network solutions for encryption key distribution and secure communication.

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

Organizing knowledge for tutoring fire loss prevention

NASA Astrophysics Data System (ADS)

Schmoldt, Daniel L.

1989-09-01

The San Bernardino National Forest in southern California has recently developed a systematic approach to wildfire prevention planning. However, a comprehensive document or other mechanism for teaching this process to other prevention personnel does not exist. An intelligent tutorial expert system is being constructed to provide a means for learning the process and to assist in the creation of specific prevention plans. An intelligent tutoring system (ITS) contains two types of knowledge—domain and tutoring. The domain knowledge for wildfire prevention is structured around several foci: (1) individual concepts used in prevention planning; (2) explicitly specified interrelationships between concepts; (3) deductive methods that contain subjective judgment normally unavailable to less-experienced users; (4) analytical models of fire behavior used for identification of hazard areas; (5) how-to guidance needed for performance of planning tasks; and (6) expository information that provides a rationale for planning steps and ideas. Combining analytical, procedure, inferential, conceptual, and expositional knowledge into a tutoring environment provides the student and/or user with a multiple perspective of the subject matter. A concept network provides a unifying framework for structuring and utilizing these diverse forms of prevention planning knowledge. This network structure borrows from and combines semantic networks and frame-based knowledge representations. The flexibility of this organization facilitates an effective synthesis and organization of multiple knowledge forms.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Welch, Jr., Paul Michael; Welch, Cynthia F.

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

A novel approach for assessments of erythrocyte sedimentation rate.

PubMed

Pribush, A; Hatskelzon, L; Meyerstein, N

2011-06-01

Previous studies have shown that the dispersed phase of sedimenting blood undergoes dramatic structural changes: Discrete red blood cell (RBC) aggregates formed shortly after a settling tube is filled with blood are combined into a continuous network followed by its collapse via the formation of plasma channels, and finally, the collapsed network is dispersed into individual fragments. Based on this scheme of structural transformation, a novel approach for assessments of erythrocyte sedimentation is suggested. Information about erythrocyte sedimentation is extracted from time records of the blood conductivity measured after a dispersion of RBC network into individual fragments. It was found that the sedimentation velocity of RBC network fragments correlates positively with the intensity of attractive intercellular interactions, whereas no effect of hematocrit (Hct) was observed. Thus, unlike Westergren erythrocyte sedimentation rate, sedimentation data obtained by the proposed method do not require correction for Hct. © 2010 Blackwell Publishing Ltd.

Gift-giving and network structure in rural China: utilizing long-term spontaneous gift records.

PubMed

Chen, Xi

2014-01-01

The tradition of keeping written records of gift received during household ceremonies in many countries offers researchers an underutilized means of data collection for social network analysis. This paper first summarizes unique features of the gift record data that circumvent five prevailing sampling and measurement issues in the literature, and we discuss their advantages over existing studies at both the individual level and the dyadic link level using previous data sources. We then document our research project in rural China that implements a multiple wave census-type household survey and a long-term gift record collection. The pattern of gift-giving in major household social events and its recent escalation is analyzed. There are significantly positive correlations between gift network centrality and various forms of informal insurance. Finally, economic inequality and competitive marriage market are among the main demographic and socioeconomic determinants of the observed gift network structure.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

DOE PAGES

Welch, Jr., Paul Michael; Welch, Cynthia F.

2017-04-27

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

Gift-Giving and Network Structure in Rural China: Utilizing Long-Term Spontaneous Gift Records

PubMed Central

Chen, Xi

2014-01-01

The tradition of keeping written records of gift received during household ceremonies in many countries offers researchers an underutilized means of data collection for social network analysis. This paper first summarizes unique features of the gift record data that circumvent five prevailing sampling and measurement issues in the literature, and we discuss their advantages over existing studies at both the individual level and the dyadic link level using previous data sources. We then document our research project in rural China that implements a multiple wave census-type household survey and a long-term gift record collection. The pattern of gift-giving in major household social events and its recent escalation is analyzed. There are significantly positive correlations between gift network centrality and various forms of informal insurance. Finally, economic inequality and competitive marriage market are among the main demographic and socioeconomic determinants of the observed gift network structure. PMID:25111696

A binary-decision-diagram-based two-bit arithmetic logic unit on a GaAs-based regular nanowire network with hexagonal topology.

PubMed

Zhao, Hong-Quan; Kasai, Seiya; Shiratori, Yuta; Hashizume, Tamotsu

2009-06-17

A two-bit arithmetic logic unit (ALU) was successfully fabricated on a GaAs-based regular nanowire network with hexagonal topology. This fundamental building block of central processing units can be implemented on a regular nanowire network structure with simple circuit architecture based on graphical representation of logic functions using a binary decision diagram and topology control of the graph. The four-instruction ALU was designed by integrating subgraphs representing each instruction, and the circuitry was implemented by transferring the logical graph structure to a GaAs-based nanowire network formed by electron beam lithography and wet chemical etching. A path switching function was implemented in nodes by Schottky wrap gate control of nanowires. The fabricated circuit integrating 32 node devices exhibits the correct output waveforms at room temperature allowing for threshold voltage variation.

Nuclear networking.

PubMed

Xie, Wei; Burke, Brian

2017-07-04

Nuclear lamins are intermediate filament proteins that represent important structural components of metazoan nuclear envelopes (NEs). By combining proteomics and superresolution microscopy, we recently reported that both A- and B-type nuclear lamins form spatially distinct filament networks at the nuclear periphery of mouse fibroblasts. In particular, A-type lamins exhibit differential association with nuclear pore complexes (NPCs). Our studies reveal that the nuclear lamina network in mammalian somatic cells is less ordered and more complex than that of amphibian oocytes, the only other system in which the lamina has been visualized at high resolution. In addition, the NPC component Tpr likely links NPCs to the A-type lamin network, an association that appears to be regulated by C-terminal modification of various A-type lamin isoforms. Many questions remain, however, concerning the structure and assembly of lamin filaments, as well as with their mode of association with other nuclear components such as peripheral chromatin.

Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring

NASA Astrophysics Data System (ADS)

Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis

In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

PubMed Central

Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

2012-01-01

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of complex multi-cellular organisms. PMID:22807664

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

NASA Astrophysics Data System (ADS)

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-12-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

PubMed Central

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-01-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks. PMID:27917958

Social Networks and Cooperation in Hunter-Gatherers

PubMed Central

Apicella, Coren L.; Marlowe, Frank W.; Fowler, James H.; Christakis, Nicholas A.

2011-01-01

Social networks exhibit striking structural regularities1,2, and theory and evidence suggest that they may have played a role in the development of large-scale cooperation in humans3–7. Here, we characterize the social networks of the Hadza, an evolutionarily relevant population of hunter-gatherers8. We show that Hadza networks exhibit important properties also seen in modernized networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay, and homophily. Moreover, we demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Finally, social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history; that early humans may have formed ties with both kin and non-kin based, in part, on their tendency to cooperate; and that social networks may have contributed to the emergence of cooperation. PMID:22281599

Complex network view of evolving manifolds

NASA Astrophysics Data System (ADS)

da Silva, Diamantino C.; Bianconi, Ginestra; da Costa, Rui A.; Dorogovtsev, Sergey N.; Mendes, José F. F.

2018-03-01

We study complex networks formed by triangulations and higher-dimensional simplicial complexes representing closed evolving manifolds. In particular, for triangulations, the set of possible transformations of these networks is restricted by the condition that at each step, all the faces must be triangles. Stochastic application of these operations leads to random networks with different architectures. We perform extensive numerical simulations and explore the geometries of growing and equilibrium complex networks generated by these transformations and their local structural properties. This characterization includes the Hausdorff and spectral dimensions of the resulting networks, their degree distributions, and various structural correlations. Our results reveal a rich zoo of architectures and geometries of these networks, some of which appear to be small worlds while others are finite dimensional with Hausdorff dimension equal or higher than the original dimensionality of their simplices. The range of spectral dimensions of the evolving triangulations turns out to be from about 1.4 to infinity. Our models include simplicial complexes representing manifolds with evolving topologies, for example, an h -holed torus with a progressively growing number of holes. This evolving graph demonstrates features of a small-world network and has a particularly heavy-tailed degree distribution.

Dynamic Modeling of Systemic Risk in Financial Networks

NASA Astrophysics Data System (ADS)

Avakian, Adam

Modern financial networks are complicated structures that can contain multiple types of nodes and connections between those nodes. Banks, governments and even individual people weave into an intricate network of debt, risk correlations and many other forms of interconnectedness. We explore multiple types of financial network models with a focus on understanding the dynamics and causes of cascading failures in such systems. In particular, we apply real-world data from multiple sources to these models to better understand real-world financial networks. We use the results of the Federal Reserve "Banking Organization Systemic Risk Report" (FR Y-15), which surveys the largest US banks on their level of interconnectedness, to find relationships between various measures of network connectivity and systemic risk in the US financial sector. This network model is then stress-tested under a number of scenarios to determine systemic risks inherent in the various network structures. We also use detailed historical balance sheet data from the Venezuelan banking system to build a bipartite network model and find relationships between the changing network structure over time and the response of the system to various shocks. We find that the relationship between interconnectedness and systemic risk is highly dependent on the system and model but that it is always a significant one. These models are useful tools that add value to regulators in creating new measurements of systemic risk in financial networks. These models could be used as macroprudential tools for monitoring the health of the entire banking system as a whole rather than only of individual banks.

Loops in hierarchical channel networks

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Magnasco, Marcelo

2012-02-01

Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

The prisoner’s dilemma on co-evolving networks under perfect rationality

NASA Astrophysics Data System (ADS)

Biely, Christoly; Dragosits, Klaus; Thurner, Stefan

2007-04-01

We consider the prisoner’s dilemma being played repeatedly on a dynamic network, where agents may choose their actions as well as their co-players. This leads to co-evolution of network structure and strategy patterns of the players. Individual decisions are made fully rationally and are based on local information only. They are made such that links to defecting agents are resolved and that cooperating agents build up new links. The exact form of the updating scheme is motivated by profit maximization and not by imitation. If players update their decisions in a synchronized way the system exhibits oscillatory dynamics: Periods of growing cooperation (and total linkage) alternate with periods of increasing defection. The cyclical behavior is reduced and the system stabilizes at significant total cooperation levels when players are less synchronized. In this regime we find emergent network structures resembling ‘complex’ and hierarchical topology. The exponent of the power-law degree distribution ( γ∼8.6) perfectly matches empirical results for human communication networks.

Opinion formation and distribution in a bounded-confidence model on various networks

NASA Astrophysics Data System (ADS)

Meng, X. Flora; Van Gorder, Robert A.; Porter, Mason A.

2018-02-01

In the social, behavioral, and economic sciences, it is important to predict which individual opinions eventually dominate in a large population, whether there will be a consensus, and how long it takes for a consensus to form. Such ideas have been studied heavily both in physics and in other disciplines, and the answers depend strongly both on how one models opinions and on the network structure on which opinions evolve. One model that was created to study consensus formation quantitatively is the Deffuant model, in which the opinion distribution of a population evolves via sequential random pairwise encounters. To consider heterogeneity of interactions in a population along with social influence, we study the Deffuant model on various network structures (deterministic synthetic networks, random synthetic networks, and social networks constructed from Facebook data). We numerically simulate the Deffuant model and conduct regression analyses to investigate the dependence of the time to reach steady states on various model parameters, including a confidence bound for opinion updates, the number of participating entities, and their willingness to compromise. We find that network structure and parameter values both have important effects on the convergence time and the number of steady-state opinion groups. For some network architectures, we observe that the relationship between the convergence time and model parameters undergoes a transition at a critical value of the confidence bound. For some networks, the steady-state opinion distribution also changes from consensus to multiple opinion groups at this critical value.

Contact Trees: Network Visualization beyond Nodes and Edges

PubMed Central

Sallaberry, Arnaud; Fu, Yang-chih; Ho, Hwai-Chung; Ma, Kwan-Liu

2016-01-01

Node-Link diagrams make it possible to take a quick glance at how nodes (or actors) in a network are connected by edges (or ties). A conventional network diagram of a “contact tree” maps out a root and branches that represent the structure of nodes and edges, often without further specifying leaves or fruits that would have grown from small branches. By furnishing such a network structure with leaves and fruits, we reveal details about “contacts” in our ContactTrees upon which ties and relationships are constructed. Our elegant design employs a bottom-up approach that resembles a recent attempt to understand subjective well-being by means of a series of emotions. Such a bottom-up approach to social-network studies decomposes each tie into a series of interactions or contacts, which can help deepen our understanding of the complexity embedded in a network structure. Unlike previous network visualizations, ContactTrees highlight how relationships form and change based upon interactions among actors, as well as how relationships and networks vary by contact attributes. Based on a botanical tree metaphor, the design is easy to construct and the resulting tree-like visualization can display many properties at both tie and contact levels, thus recapturing a key ingredient missing from conventional techniques of network visualization. We demonstrate ContactTrees using data sets consisting of up to three waves of 3-month contact diaries over the 2004-2012 period, and discuss how this design can be applied to other types of datasets. PMID:26784350

Kinetic products in coordination networks: ab initio X-ray powder diffraction analysis.

PubMed

Martí-Rujas, Javier; Kawano, Masaki

2013-02-19

Porous coordination networks are materials that maintain their crystal structure as molecular "guests" enter and exit their pores. They are of great research interest with applications in areas such as catalysis, gas adsorption, proton conductivity, and drug release. As with zeolite preparation, the kinetic states in coordination network preparation play a crucial role in determining the final products. Controlling the kinetic state during self-assembly of coordination networks is a fundamental aspect of developing further functionalization of this class of materials. However, unlike for zeolites, there are few structural studies reporting the kinetic products made during self-assembly of coordination networks. Synthetic routes that produce the necessary selectivity are complex. The structural knowledge obtained from X-ray crystallography has been crucial for developing rational strategies for design of organic-inorganic hybrid networks. However, despite the explosive progress in the solid-state study of coordination networks during the last 15 years, researchers still do not understand many chemical reaction processes because of the difficulties in growing single crystals suitable for X-ray diffraction: Fast precipitation can lead to kinetic (metastable) products, but in microcrystalline form, unsuitable for single crystal X-ray analysis. X-ray powder diffraction (XRPD) routinely is used to check phase purity, crystallinity, and to monitor the stability of frameworks upon guest removal/inclusion under various conditions, but rarely is used for structure elucidation. Recent advances in structure determination of microcrystalline solids from ab initio XRPD have allowed three-dimensional structure determination when single crystals are not available. Thus, ab initio XRPD structure determination is becoming a powerful method for structure determination of microcrystalline solids, including porous coordination networks. Because of the great interest across scientific disciplines in coordination networks, especially porous coordination networks, the ability to determine crystal structures when the crystals are not suitable for single crystal X-ray analysis is of paramount importance. In this Account, we report the potential of kinetic control to synthesize new coordination networks and we describe ab initio XRPD structure determination to characterize these networks' crystal structures. We describe our recent work on selective instant synthesis to yield kinetically controlled porous coordination networks. We demonstrate that instant synthesis can selectively produce metastable networks that are not possible to synthesize by conventional solution chemistry. Using kinetic products, we provide mechanistic insights into thermally induced (573-723 K) (i.e., annealing method) structural transformations in porous coordination networks as well as examples of guest exchange/inclusion reactions. Finally, we describe a memory effect that allows the transfer of structural information from kinetic precursor structures to thermally stable structures through amorphous intermediate phases. We believe that ab initio XRPD structure determination will soon be used to investigate chemical processes that lead intrinsically to microcrystalline solids, which up to now have not been fully understood due to the unavailability of single crystals. For example, only recently have researchers used single-crystal X-ray diffraction to elucidate crystal-to-crystal chemical reactions taking place in the crystalline scaffold of coordination networks. The potential of ab initio X-ray powder diffraction analysis goes beyond single-crystal-to-single-crystal processes, potentially allowing members of this field to study intriguing in situ reactions, such as reactions within pores.

The Construction of Higher Education Entrepreneur Services Network System a Research Based on Ecological Systems Theory

NASA Astrophysics Data System (ADS)

Xue, Jingxin

The article aims to completely, systematically and objectively analyze the current situation of Entrepreneurship Education in China with Ecological Systems Theory. From this perspective, the author discusses the structure, function and its basic features of higher education entrepreneur services network system, and puts forward the opinion that every entrepreneurship organization in higher education institution does not limited to only one platform. Different functional supporting platforms should be combined closed through composite functional organization to form an integrated network system, in which each unit would impels others' development.

Fragmentation, rings and coarsening: structure and transformations of nanocrystal aggregate networks on a liquid surface

NASA Astrophysics Data System (ADS)

Yang, Bo; Scheidtmann, Jens; Mayer, Joachim; Wuttig, Matthias; Michely, Thomas

2002-01-01

Deposition of Ag on a silicon oil surface leads to the formation of nm-sized Ag crystals floating on the oil surface. These nanocrystals mutually attract each other, forming strongly branched nanocrystal aggregates and continuous aggregate networks. Transformation processes of such nanocrystal aggregate networks are imaged in situ by optical microscopy. The observations are explained on the basis of a simple model involving diffusion of nanocrystals along aggregate edges and the rupture of branches resulting from branch width fluctuations due to edge diffusion.

Origin of hyperbolicity in brain-to-brain coordination networks

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 < 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

Two-Dimensional Nanoporous Networks Formed by Liquid-to-Solid Transfer of Hydrogen-Bonded Macrocycles Built from DNA Bases.

PubMed

Bilbao, Nerea; Destoop, Iris; De Feyter, Steven; González-Rodríguez, David

2016-01-11

We present an approach that makes use of DNA base pairing to produce hydrogen-bonded macrocycles whose supramolecular structure can be transferred from solution to a solid substrate. A hierarchical assembly process ultimately leads to two-dimensional nanostructured porous networks that are able to host size-complementary guests. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tensegrity II. How structural networks influence cellular information processing networks

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

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

The Dynamics of Coalition Formation on Complex Networks

NASA Astrophysics Data System (ADS)

Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

2015-08-01

Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

Particle-filled microporous materials

DOEpatents

McAllister, Jerome W.; Kinzer, Kevin E.; Mrozinski, James S.; Johnson, Eric J.; Dyrud, James F.

1990-01-01

A microporous particulate-filled thermoplastic polymeric article is provided. The article can be in the form of a film, a fiber, or a tube. The article has a thermoplastic polymeric structure having a plurality of interconnected passageways to provide a network of communicating pores. The microporous structure contains discrete submicron or low micron-sized particulate filler, the particulate filler being substantially non-agglomerated.

Particle-filled microporous materials

DOEpatents

McAllister, Jerome W.; Kinzer, Kevin E.; Mrozinski, James S.; Johnson, Eric J.

1992-07-14

A microporous particulate-filled thermoplastic polymeric article is provided. The article can be in the form of a film, a fiber, or a tube. The article has a thermoplastic polymeric structure having a plurality of interconnected passageways to provide a network of communicating pores. The microporous structure contains discrete submicron or low micron-sized particulate filler, the particulate filler being substantially non-agglomerated.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

The use of social networking to improve the quality of interprofessional education.

PubMed

Pittenger, Amy L

2013-10-14

To evaluate the feasibility and effectiveness of using an online social networking platform for interprofessional education. Three groups of 6 students were formed with 1 student in each group from medicine, nursing, dentistry, pharmacy, veterinary medicine, and public health. Each group followed a different collaborative educational model with a unique pedagogical structure. Students in all groups interacted via an online social networking platform for a minimum of 15 weeks and met in person once at the end of the 15-week experience for a focus group session. The students were tasked with developing a collaborative recommendation for using social networking in interprofessional education programs. Most of the students who reported in a post-experience survey that their expectations were not met were in the minimally structured group. Almost all students in the facilitated and highly structured groups indicated that this experience positively impacted their knowledge of other health professions. Most students stated that interacting within a social networking space for 15 weeks with other members of the university's health professions programs was a positive and effective interprofessional education experience. Social networking is feasible and can be used effectively within an overall strategy for interprofessional education, but design and placement within a core content course is critical to success.

Structure and Conductivity of Semiconducting Polymer Hydrogels.

PubMed

Huber, Rachel C; Ferreira, Amy S; Aguirre, Jordan C; Kilbride, Daniel; Toso, Daniel B; Mayoral, Kenny; Zhou, Z Hong; Kopidakis, Nikos; Rubin, Yves; Schwartz, Benjamin J; Mason, Thomas G; Tolbert, Sarah H

2016-07-07

Poly(fluorene-alt-thiophene) (PFT) is a conjugated polyelectrolyte that self-assembles into rod-like micelles in water, with the conjugated polymer backbone running along the length of the micelle. At modest concentrations (∼10 mg/mL in aqueous solutions), PFT forms hydrogels, and this work focuses on understanding the structure and intermolecular interactions in those gel networks. The network structure can be directly visualized using cryo electron microscopy. Oscillatory rheology studies further tell us about connectivity within the gel network, and the data are consistent with a picture where polymer chains bridge between micelles to hold the network together. Addition of tetrahydrofuran (THF) to the gels breaks those connections, but once the THF is removed, the gel becomes stronger than it was before, presumably due to the creation of a more interconnected nanoscale architecture. Small polymer oligomers can also passivate the bridging polymer chains, breaking connections between micelles and dramatically weakening the hydrogel network. Fits to solution-phase small-angle X-ray scattering data using a Dammin bead model support the hypothesis of a bridging connection between PFT micelles, even in dilute aqueous solutions. Finally, time-resolved microwave conductivity measurements on dried samples show an increase in carrier mobility after THF annealing of the PFT gel, likely due to increased connectivity within the polymer network.

The Use of Social Networking to Improve the Quality of Interprofessional Education

PubMed Central

2013-01-01

Objective. To evaluate the feasibility and effectiveness of using an online social networking platform for interprofessional education. Design. Three groups of 6 students were formed with 1 student in each group from medicine, nursing, dentistry, pharmacy, veterinary medicine, and public health. Each group followed a different collaborative educational model with a unique pedagogical structure. Students in all groups interacted via an online social networking platform for a minimum of 15 weeks and met in person once at the end of the 15-week experience for a focus group session. The students were tasked with developing a collaborative recommendation for using social networking in interprofessional education programs. Assessment. Most of the students who reported in a post-experience survey that their expectations were not met were in the minimally structured group. Almost all students in the facilitated and highly structured groups indicated that this experience positively impacted their knowledge of other health professions. Most students stated that interacting within a social networking space for 15 weeks with other members of the university’s health professions programs was a positive and effective interprofessional education experience. Conclusion. Social networking is feasible and can be used effectively within an overall strategy for interprofessional education, but design and placement within a core content course is critical to success. PMID:24159215

Water: a responsive small molecule.

PubMed

Shultz, Mary Jane; Vu, Tuan Hoang; Meyer, Bryce; Bisson, Patrick

2012-01-17

Unique among small molecules, water forms a nearly tetrahedral yet flexible hydrogen-bond network. In addition to its flexibility, this network is dynamic: bonds are formed or broken on a picosecond time scale. These unique features make probing the local structure of water challenging. Despite the challenges, there is intense interest in developing a picture of the local water structure due to water's fundamental importance in many fields of chemistry. Understanding changes in the local network structure of water near solutes likely holds the key to unlock problems from analyzing parameters that determine the three dimensional structure of proteins to modeling the fate of volatile materials released into the atmosphere. Pictures of the local structure of water are heavily influenced by what is known about the structure of ice. In hexagonal I(h) ice, the most stable form of solid water under ordinary conditions, water has an equal number of donor and acceptor bonds; a kind of symmetry. This symmetric tetrahedral coordination is only approximately preserved in the liquid. The most obvious manifestation of this altered tetrahedral bonding is the greater density in the liquid compared with the solid. Formation of an interface or addition of solutes further modifies the local bonding in water. Because the O-H stretching frequency is sensitive to the environment, vibrational spectroscopy provides an excellent probe for the hydrogen-bond structure in water. In this Account, we examine both local interactions between water and small solutes and longer range interactions at the aqueous surface. Locally, the results suggest that water is not a symmetric donor or acceptor, but rather has a propensity to act as an acceptor. In interactions with hydrocarbons, action is centered at the water oxygen. For soluble inorganic salts, interaction is greater with the cation than the anion. The vibrational spectrum of the surface of salt solutions is altered compared with that of neat water. Studies of local salt-water interactions suggest that the picture of the local water structure and the ion distribution at the surface deduced from the surface vibrational spectrum should encompass both ions of the salt.

C60-pentacene network formation by 2-D co-crystallization.

PubMed

Jin, Wei; Dougherty, Daniel B; Cullen, William G; Robey, Steven; Reutt-Robey, Janice E

2009-09-01

We report experiments highlighting the mechanistic role of mobile pentacene precursors in the formation of a network C(60)-pentacene co-crystalline structure on Ag(111). This co-crystalline arrangement was first observed by low temperature scanning tunneling microscopy (STM) by Zhang et al. (Zhang, H. L.; Chen, W.; Huang, H.; Chen, L.; Wee, A. T. S. J. Am. Chem. Soc. 2008, 130, 2720-2721). We now show that this structure forms readily at room temperature from a two-dimensional (2-D) mixture. Pentacene, evaporated onto Ag(111) to coverages of 0.4-1.0 ML, produces a two-dimensional (2-D) gas. Subsequently deposited C(60) molecules combine with the pentacene 2-D gas to generate a network structure, consisting of chains of close-packed C(60) molecules, spaced by individual C(60) linkers and 1 nm x 2.5 nm pores containing individual pentacene molecules. Spontaneous formation of this stoichiometric (C(60))(4)-pentacene network from a range of excess pentacene surface coverage (0.4 to 1.0 ML) indicates a self-limiting assembly process. We refine the structure model for this phase and discuss the generality of this co-crystallization mechanism.

Network architecture of the cerebral nuclei (basal ganglia) association and commissural connectome.

PubMed

Swanson, Larry W; Sporns, Olaf; Hahn, Joel D

2016-10-04

The cerebral nuclei form the ventral division of the cerebral hemisphere and are thought to play an important role in neural systems controlling somatic movement and motivation. Network analysis was used to define global architectural features of intrinsic cerebral nuclei circuitry in one hemisphere (association connections) and between hemispheres (commissural connections). The analysis was based on more than 4,000 reports of histologically defined axonal connections involving all 45 gray matter regions of the rat cerebral nuclei and revealed the existence of four asymmetrically interconnected modules. The modules form four topographically distinct longitudinal columns that only partly correspond to previous interpretations of cerebral nuclei structure-function organization. The network of connections within and between modules in one hemisphere or the other is quite dense (about 40% of all possible connections), whereas the network of connections between hemispheres is weak and sparse (only about 5% of all possible connections). Particularly highly interconnected regions (rich club and hubs within it) form a topologically continuous band extending through two of the modules. Connection path lengths among numerous pairs of regions, and among some of the network's modules, are relatively long, thus accounting for low global efficiency in network communication. These results provide a starting point for reexamining the connectional organization of the cerebral hemispheres as a whole (right and left cerebral cortex and cerebral nuclei together) and their relation to the rest of the nervous system.

Evolutionary transitions in controls reconcile adaptation with continuity of evolution.

PubMed

Badyaev, Alexander V

2018-05-19

Evolution proceeds by accumulating functional solutions, necessarily forming an uninterrupted lineage from past solutions of ancestors to the current design of extant forms. At the population level, this process requires an organismal architecture in which the maintenance of local adaptation does not preclude the ability to innovate in the same traits and their continuous evolution. Representing complex traits as networks enables us to visualize a fundamental principle that resolves tension between adaptation and continuous evolution: phenotypic states encompassing adaptations traverse the continuous multi-layered landscape of past physical, developmental and functional associations among traits. The key concept that captures such traversing is network controllability - the ability to move a network from one state into another while maintaining its functionality (reflecting evolvability) and to efficiently propagate information or products through the network within a phenotypic state (maintaining its robustness). Here I suggest that transitions in network controllability - specifically in the topology of controls - help to explain how robustness and evolvability are balanced during evolution. I will focus on evolutionary transitions in degeneracy of metabolic networks - a ubiquitous property of phenotypic robustness where distinct pathways achieve the same end product - to suggest that associated changes in network controls is a common rule underlying phenomena as distinct as phenotypic plasticity, organismal accommodation of novelties, genetic assimilation, and macroevolutionary diversification. Capitalizing on well understood principles by which network structure translates into function of control nodes, I show that accumulating redundancy in one type of network controls inevitably leads to the emergence of another type of controls, forming evolutionary cycles of network controllability that, ultimately, reconcile local adaptation with continuity of evolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spectroscopic study of uracil, 1-methyluracil and 1-methyl-4-thiouracil: Hydrogen bond interactions in crystals and ab-initio molecular dynamics.

PubMed

Brela, Mateusz Z; Boczar, Marek; Malec, Leszek M; Wójcik, Marek J; Nakajima, Takahito

2018-05-15

Hydrogen bond networks in uracil, 1-methyluracil and 1-methyl-4-thiouracil were studied by ab initio molecular dynamics as well as analysis of the orbital interactions. The power spectra calculated by ab initio molecular dynamics for atoms involved in hydrogen bonds were analyzed. We calculated spectra by using anharmonic approximation based on the autocorrelation function of the atom positions obtained from the Born-Oppenheimer simulations. Our results show the differences between hydrogen bond networks in uracil and its methylated derivatives. The studied methylated derivatives, 1-methyluracil as well as 1-methyl-4-thiouracil, form dimeric structures in the crystal phase, while uracil does not form that kind of structures. The presence of sulfur atom instead oxygen atom reflects weakness of the hydrogen bonds that build dimers. Copyright © 2018 Elsevier B.V. All rights reserved.

Water adsorption on the Fe3O4(111) surface: dissociation and network formation.

PubMed

Zaki, Eman; Mirabella, Francesca; Ivars-Barceló, Francisco; Seifert, Jan; Carey, Spencer; Shaikhutdinov, Shamil; Freund, Hans-Joachim; Li, Xiaoke; Paier, Joachim; Sauer, Joachim

2018-06-13

We monitored adsorption of water on a well-defined Fe3O4(111) film surface at different temperatures as a function of coverage using infrared reflection-absorption spectroscopy, temperature programmed desorption, and single crystal adsorption calorimetry. Additionally, density functional theory was employed using a Fe3O4(111)-(2 × 2) slab model to generate 15 energy minimum structures for various coverages. Corresponding vibrational properties of the adsorbed water species were also computed. The results show that water molecules readily dissociate on regular surface Fetet1-O ion pairs to form "monomers", i.e., terminal Fe-OH and surface OH groups. Further water molecules adsorb on the hydroxyl covered surface non-dissociatively and form "dimers" and larger oligomers, which ultimately assemble into an ordered (2 × 2) hydrogen-bonded network structure with increasing coverage prior to the formation of a solid water film.

Chimera States in Continuous Media: Existence and Distinctness

NASA Astrophysics Data System (ADS)

Nicolaou, Zachary G.; Riecke, Hermann; Motter, Adilson E.

2017-12-01

The defining property of chimera states is the coexistence of coherent and incoherent domains in systems that are structurally and spatially homogeneous. The recent realization that such states might be common in oscillator networks raises the question of whether an analogous phenomenon can occur in continuous media. Here, we show that chimera states can exist in continuous systems even when the coupling is strictly local, as in many fluid and pattern forming media. Using the complex Ginzburg-Landau equation as a model system, we characterize chimera states consisting of a coherent domain of a frozen spiral structure and an incoherent domain of amplitude turbulence. We show that in this case, in contrast with discrete network systems, fluctuations in the local coupling field play a crucial role in limiting the coherent regions. We suggest these findings shed light on new possible forms of coexisting order and disorder in fluid systems.

Semantic Analysis of Email Using Domain Ontologies and WordNet

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Keller, Richard M.

2005-01-01

The problem of capturing and accessing knowledge in paper form has been supplanted by a problem of providing structure to vast amounts of electronic information. Systems that can construct semantic links for natural language documents like email messages automatically will be a crucial element of semantic email tools. We have designed an information extraction process that can leverage the knowledge already contained in an existing semantic web, recognizing references in email to existing nodes in a network of ontology instances by using linguistic knowledge and knowledge of the structure of the semantic web. We developed a heuristic score that uses several forms of evidence to detect references in email to existing nodes in the Semanticorganizer repository's network. While these scores cannot directly support automated probabilistic inference, they can be used to rank nodes by relevance and link those deemed most relevant to email messages.

Modal and Temporal Argumentation Networks

NASA Astrophysics Data System (ADS)

Barringer, Howard; Gabbay, Dov M.

The traditional Dung networks depict arguments as atomic and studies the relationships of attack between them. This can be generalised in two ways. One is to consider, for example, various forms of attack, support and feedback. Another is to add content to nodes and put there not just atomic arguments but more structure, for example, proofs in some logic or simply just formulas from a richer language. This paper offers to use temporal and modal language formulas to represent arguments in the nodes of a network. The suitable semantics for such networks is Kripke semantics. We also introduce a new key concept of usability of an argument.

Constitutive modelling of composite biopolymer networks.

PubMed

Fallqvist, B; Kroon, M

2016-04-21

The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Voluntary Vaccination through Self-organizing Behaviors on Locally-mixed Social Networks.

PubMed

Shi, Benyun; Qiu, Hongjun; Niu, Wenfang; Ren, Yizhi; Ding, Hong; Chen, Dan

2017-06-01

Voluntary vaccination reflects how individuals weigh the risk of infection and the cost of vaccination against the spread of vaccine-preventable diseases, such as smallpox and measles. In a homogeneously mixing population, the infection risk of an individual depends largely on the proportion of vaccinated individuals due to the effects of herd immunity. While in a structured population, the infection risk can also be affected by the structure of individuals' social network. In this paper, we focus on studying individuals' self-organizing behaviors under the circumstance of voluntary vaccination in different types of social networks. Specifically, we assume that each individual together with his/her neighbors forms a local well-mixed environment, where individuals meet equally often as long as they have a common neighbor. We carry out simulations on four types of locally-mixed social networks to investigate the network effects on voluntary vaccination. Furthermore, we also evaluate individuals' vaccinating decisions through interacting with their "neighbors of neighbors". The results and findings of this paper provide a new perspective for vaccination policy-making by taking into consideration human responses in complex social networks.

Segmentation of dermoscopy images using wavelet networks.

PubMed

Sadri, Amir Reza; Zekri, Maryam; Sadri, Saeed; Gheissari, Niloofar; Mokhtari, Mojgan; Kolahdouzan, Farzaneh

2013-04-01

This paper introduces a new approach for the segmentation of skin lesions in dermoscopic images based on wavelet network (WN). The WN presented here is a member of fixed-grid WNs that is formed with no need of training. In this WN, after formation of wavelet lattice, determining shift and scale parameters of wavelets with two screening stage and selecting effective wavelets, orthogonal least squares algorithm is used to calculate the network weights and to optimize the network structure. The existence of two stages of screening increases globality of the wavelet lattice and provides a better estimation of the function especially for larger scales. R, G, and B values of a dermoscopy image are considered as the network inputs and the network structure formation. Then, the image is segmented and the skin lesions exact boundary is determined accordingly. The segmentation algorithm were applied to 30 dermoscopic images and evaluated with 11 different metrics, using the segmentation result obtained by a skilled pathologist as the ground truth. Experimental results show that our method acts more effectively in comparison with some modern techniques that have been successfully used in many medical imaging problems.

Scaling and percolation in the small-world network model

NASA Astrophysics Data System (ADS)

Newman, M. E. J.; Watts, D. J.

1999-12-01

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one nontrivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the crossover from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Padé approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model.

Supramolecular Organization of the α121-α565 Collagen IV Network*

PubMed Central

Robertson, Wesley E.; Rose, Kristie L.; Hudson, Billy G.; Vanacore, Roberto M.

2014-01-01

Collagen IV is a family of 6 chains (α1-α6), that form triple-helical protomers that assemble into supramolecular networks. Two distinct networks with chain compositions of α121 and α345 have been established. These oligomerize into separate α121 and α345 networks by a homotypic interaction through their trimeric noncollagenous (NC1) domains, forming α121 and α345 NC1 hexamers, respectively. These are stabilized by novel sulfilimine (SN) cross-links, a covalent cross-link that forms between Met93 and Hyl211 at the trimer-trimer interface. A third network with a composition of α1256 has been proposed, but its supramolecular organization has not been established. In this study we investigated the supramolecular organization of this network by determining the chain identity of sulfilimine-cross-linked NC1 domains derived from the α1256 NC1 hexamer. High resolution mass spectrometry analyses of peptides revealed that sulfilimine bonds specifically cross-link α1 to α5 and α2 to α6 NC1 domains, thus providing the spatial orientation between interacting α121 and α565 trimers. Using this information, we constructed a three-dimensional homology model in which the α565 trimer shows a good chemical and structural complementarity to the α121 trimer. Our studies provide the first chemical evidence for an α565 protomer and its heterotypic interaction with the α121 protomer. Moreover, our findings, in conjunction with our previous studies, establish that the six collagen IV chains are organized into three canonical protomers α121, α345, and α565 forming three distinct networks: α121, α345, and α121-α565, each of which is stabilized by sulfilimine bonds between their C-terminal NC1 domains. PMID:25006246

Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network.

PubMed

Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Hedman, Anna M; van den Heuvel, Martijn P; van Haren, Neeltje E M; Kahn, René S; Hulshoff Pol, Hilleke E

2016-01-01

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10,000 reference networks (p=0.031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network. Copyright © 2015 Elsevier Inc. All rights reserved.

Sol-gel optics for biomeasurements

NASA Astrophysics Data System (ADS)

Lechna-Marczynska, Monika I.; Podbielska, Halina; Ulatowska-Jarza, Agnieszka; Holowacz, Iwona; Andrzejewski, Damian

2001-10-01

Sol-gel technique is a method for producing of glass-like materials without involving a melting process. Organic compounds such as alcoholates of silicon, sodium or calcium can be used. The irregular non-crystalline network forms a gel structure where the metallic atoms are bonded to oxygen atoms. Low-temperature treatment turns this gel into an inorganic glass-like structure. There are numbers of applications of these materials that can be produced in various forms and shapes. Here, silica based sol-gel bulks and thin films optodes for biomedical applications will be presented.

On the molecular origins of biomass recalcitrance: the interaction network and solvation structures of cellulose microfibrils.

PubMed

Gross, Adam S; Chu, Jhih-Wei

2010-10-28

Biomass recalcitrance is a fundamental bottleneck to producing fuels from renewable sources. To understand its molecular origin, we characterize the interaction network and solvation structures of cellulose microfibrils via all-atom molecular dynamics simulations. The network is divided into three components: intrachain, interchain, and intersheet interactions. Analysis of their spatial dependence and interaction energetics indicate that intersheet interactions are the most robust and strongest component and do not display a noticeable dependence on solvent exposure. Conversely, the strength of surface-exposed intrachain and interchain hydrogen bonds is significantly reduced. Comparing the interaction networks of I(β) and I(α) cellulose also shows that the number of intersheet interactions is a clear descriptor that distinguishes the two allomorphs and is consistent with the observation that I(β) is the more stable form. These results highlight the dominant role of the often-overlooked intersheet interactions in giving rise to biomass recalcitrance. We also analyze the solvation structures around the surfaces of microfibrils and show that the structural and chemical features at cellulose surfaces constrict water molecules into specific density profiles and pair correlation functions. Calculations of water density and compressibility in the hydration shell show noticeable but not drastic differences. Therefore, specific solvation structures are more prominent signatures of different surfaces.

Barreloid Borders and Neuronal Activity Shape Panglial Gap Junction-Coupled Networks in the Mouse Thalamus.

PubMed

Claus, Lena; Philippot, Camille; Griemsmann, Stephanie; Timmermann, Aline; Jabs, Ronald; Henneberger, Christian; Kettenmann, Helmut; Steinhäuser, Christian

2018-01-01

The ventral posterior nucleus of the thalamus plays an important role in somatosensory information processing. It contains elongated cellular domains called barreloids, which are the structural basis for the somatotopic organization of vibrissae representation. So far, the organization of glial networks in these barreloid structures and its modulation by neuronal activity has not been studied. We have developed a method to visualize thalamic barreloid fields in acute slices. Combining electrophysiology, immunohistochemistry, and electroporation in transgenic mice with cell type-specific fluorescence labeling, we provide the first structure-function analyses of barreloidal glial gap junction networks. We observed coupled networks, which comprised both astrocytes and oligodendrocytes. The spread of tracers or a fluorescent glucose derivative through these networks was dependent on neuronal activity and limited by the barreloid borders, which were formed by uncoupled or weakly coupled oligodendrocytes. Neuronal somata were distributed homogeneously across barreloid fields with their processes running in parallel to the barreloid borders. Many astrocytes and oligodendrocytes were not part of the panglial networks. Thus, oligodendrocytes are the cellular elements limiting the communicating panglial network to a single barreloid, which might be important to ensure proper metabolic support to active neurons located within a particular vibrissae signaling pathway. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

How women organize social networks different from men

PubMed Central

Szell, Michael; Thurner, Stefan

2013-01-01

Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks. Here we study gender-specific differences of a multiplex network from a complete behavioral dataset of an online-game society of about 300,000 players. On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females. On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males. These results confirm quantitatively that females and males manage their social networks in substantially different ways. PMID:23393616

How women organize social networks different from men.

PubMed

Szell, Michael; Thurner, Stefan

2013-01-01

Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks. Here we study gender-specific differences of a multiplex network from a complete behavioral dataset of an online-game society of about 300,000 players. On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females. On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males. These results confirm quantitatively that females and males manage their social networks in substantially different ways.

Covalently bonded networks through surface-confined polymerization

NASA Astrophysics Data System (ADS)

El Garah, Mohamed; MacLeod, Jennifer M.; Rosei, Federico

2013-07-01

The prospect of synthesizing ordered, covalently bonded structures directly on a surface has recently attracted considerable attention due to its fundamental interest and for potential applications in electronics and photonics. This prospective article focuses on efforts to synthesize and characterize epitaxial one- and two-dimensional (1D and 2D, respectively) polymeric networks on single crystal surfaces. Recent studies, mostly performed using scanning tunneling microscopy (STM), demonstrate the ability to induce polymerization based on Ullmann coupling, thermal dehalogenation and dehydration reactions. The 2D polymer networks synthesized to date have exhibited structural limitations and have been shown to form only small domains on the surface. We discuss different approaches to control 1D and 2D polymerization, with particular emphasis on the surface phenomena that are critical to the formation of larger ordered domains.

Structural methodologies for auditing SNOMED.

PubMed

Wang, Yue; Halper, Michael; Min, Hua; Perl, Yehoshua; Chen, Yan; Spackman, Kent A

2007-10-01

SNOMED is one of the leading health care terminologies being used worldwide. As such, quality assurance is an important part of its maintenance cycle. Methodologies for auditing SNOMED based on structural aspects of its organization are presented. In particular, automated techniques for partitioning SNOMED into smaller groups of concepts based primarily on relationships patterns are defined. Two abstraction networks, the area taxonomy and p-area taxonomy, are derived from the partitions. The high-level views afforded by these abstraction networks form the basis for systematic auditing. The networks tend to highlight errors that manifest themselves as irregularities at the abstract level. They also support group-based auditing, where sets of purportedly similar concepts are focused on for review. The auditing methodologies are demonstrated on one of SNOMED's top-level hierarchies. Errors discovered during the auditing process are reported.

The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients.

PubMed

Kossakowski, Jolanda J; Epskamp, Sacha; Kieffer, Jacobien M; van Borkulo, Claudia D; Rhemtulla, Mijke; Borsboom, Denny

2016-04-01

Health-Related Quality of Life (HRQoL) research has typically adopted either a formative approach, in which HRQoL is the common effect of its observables, or a reflective approach--defining HRQoL as a latent variable that determines observable characteristics of HRQoL. Both approaches, however, do not take into account the complex organization of these characteristics. The objective of this study was to introduce a new approach for analyzing HRQoL data, namely a network model (NM). An NM, as opposed to traditional research strategies, accounts for interactions among observables and offers a complementary analytic approach. We applied the NM to samples of Dutch cancer patients (N = 485) and Dutch healthy adults (N = 1742) who completed the 36-item Short Form Health Survey (SF-36). Networks were constructed for both samples separately and for a combined sample with diagnostic status added as an extra variable. We assessed the network structures and compared the structures of the two separate samples on the item and domain levels. The relative importance of individual items in the network structures was determined using centrality analyses. We found that the global structure of the SF-36 is dominant in all networks, supporting the validity of questionnaire's subscales. Furthermore, results suggest that the network structure of both samples was highly similar. Centrality analyses revealed that maintaining a daily routine despite one's physical health predicts HRQoL levels best. We concluded that the NM provides a fruitful alternative to classical approaches used in the psychometric analysis of HRQoL data.

Dengue-2 structural proteins associate with human proteins to produce a coagulation and innate immune response biased interactome.

PubMed

Folly, Brenda B; Weffort-Santos, Almeriane M; Fathman, C G; Soares, Luis R B

2011-01-31

Dengue virus infection is a public health threat to hundreds of millions of individuals in the tropical regions of the globe. Although Dengue infection usually manifests itself in its mildest, though often debilitating clinical form, dengue fever, life-threatening complications commonly arise in the form of hemorrhagic shock and encephalitis. The etiological basis for the virus-induced pathology in general, and the different clinical manifestations in particular, are not well understood. We reasoned that a detailed knowledge of the global biological processes affected by virus entry into a cell might help shed new light on this long-standing problem. A bacterial two-hybrid screen using DENV2 structural proteins as bait was performed, and the results were used to feed a manually curated, global dengue-human protein interaction network. Gene ontology and pathway enrichment, along with network topology and microarray meta-analysis, were used to generate hypothesis regarding dengue disease biology. Combining bioinformatic tools with two-hybrid technology, we screened human cDNA libraries to catalogue proteins physically interacting with the DENV2 virus structural proteins, Env, cap and PrM. We identified 31 interacting human proteins representing distinct biological processes that are closely related to the major clinical diagnostic feature of dengue infection: haemostatic imbalance. In addition, we found dengue-binding human proteins involved with additional key aspects, previously described as fundamental for virus entry into cells and the innate immune response to infection. Construction of a DENV2-human global protein interaction network revealed interesting biological properties suggested by simple network topology analysis. Our experimental strategy revealed that dengue structural proteins interact with human protein targets involved in the maintenance of blood coagulation and innate anti-viral response processes, and predicts that the interaction of dengue proteins with a proposed human protein interaction network produces a modified biological outcome that may be behind the hallmark pathologies of dengue infection.

Animal social networks as substrate for cultural behavioural diversity.

PubMed

Whitehead, Hal; Lusseau, David

2012-02-07

We used individual-based stochastic models to examine how social structure influences the diversity of socially learned behaviour within a non-human population. For continuous behavioural variables we modelled three forms of dyadic social learning, averaging the behavioural value of the two individuals, random transfer of information from one individual to the other, and directional transfer from the individual with highest behavioural value to the other. Learning had potential error. We also examined the transfer of categorical behaviour between individuals with random directionality and two forms of error, the adoption of a randomly chosen existing behavioural category or the innovation of a new type of behaviour. In populations without social structuring the diversity of culturally transmitted behaviour increased with learning error and population size. When the populations were structured socially either by making individuals members of permanent social units or by giving them overlapping ranges, behavioural diversity increased with network modularity under all scenarios, although the proportional increase varied considerably between continuous and categorical behaviour, with transmission mechanism, and population size. Although functions of the form e(c)¹(m)⁻(c)² + (c)³(Log(N)) predicted the mean increase in diversity with modularity (m) and population size (N), behavioural diversity could be highly unpredictable both between simulations with the same set of parameters, and within runs. Errors in social learning and social structuring generally promote behavioural diversity. Consequently, social learning may be considered to produce culture in populations whose social structure is sufficiently modular. Copyright © 2011 Elsevier Ltd. All rights reserved.

Extending the accuracy of the SNAP interatomic potential form

NASA Astrophysics Data System (ADS)

Wood, Mitchell A.; Thompson, Aidan P.

2018-06-01

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functions in EAM. The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similar to artificial neural network potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting. The quality of this new potential form is measured through a robust cross-validation analysis.

Coupling effects on turning points of infectious diseases epidemics in scale-free networks.

PubMed

Kim, Kiseong; Lee, Sangyeon; Lee, Doheon; Lee, Kwang Hyung

2017-05-31

Pandemic is a typical spreading phenomenon that can be observed in the human society and is dependent on the structure of the social network. The Susceptible-Infective-Recovered (SIR) model describes spreading phenomena using two spreading factors; contagiousness (β) and recovery rate (γ). Some network models are trying to reflect the social network, but the real structure is difficult to uncover. We have developed a spreading phenomenon simulator that can input the epidemic parameters and network parameters and performed the experiment of disease propagation. The simulation result was analyzed to construct a new marker VRTP distribution. We also induced the VRTP formula for three of the network mathematical models. We suggest new marker VRTP (value of recovered on turning point) to describe the coupling between the SIR spreading and the Scale-free (SF) network and observe the aspects of the coupling effects with the various of spreading and network parameters. We also derive the analytic formulation of VRTP in the fully mixed model, the configuration model, and the degree-based model respectively in the mathematical function form for the insights on the relationship between experimental simulation and theoretical consideration. We discover the coupling effect between SIR spreading and SF network through devising novel marker VRTP which reflects the shifting effect and relates to entropy.

Nestedness across biological scales

PubMed Central

Marquitti, Flavia M. D.; Raimundo, Rafael L. G.; Sebastián-González, Esther; Coltri, Patricia P.; Perez, S. Ivan; Brandt, Débora Y. C.; Nunes, Kelly; Daura-Jorge, Fábio G.; Floeter, Sergio R.; Guimarães, Paulo R.

2017-01-01

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks. PMID:28166284

In situ formed Si nanoparticle network with micron-sized Si particles for lithium-ion battery anodes.

PubMed

Wu, Mingyan; Sabisch, Julian E C; Song, Xiangyun; Minor, Andrew M; Battaglia, Vincent S; Liu, Gao

2013-01-01

To address the significant challenges associated with large volume change of micrometer-sized Si particles as high-capacity anode materials for lithium-ion batteries, we demonstrated a simple but effective strategy: using Si nanoparticles as a structural and conductive additive, with micrometer-sized Si as the main lithium-ion storage material. The Si nanoparticles connected into the network structure in situ during the charge process, to provide electronic connectivity and structure stability for the electrode. The resulting electrode showed a high specific capacity of 2500 mAh/g after 30 cycles with high initial Coulombic efficiency (73%) and good rate performance during electrochemical lithiation and delithiation: between 0.01 and 1 V vs Li/Li(+).

Red cell membrane skeleton: structure-function relationships.

PubMed

Palek, J; Liu, S C

1980-01-01

This papaer reviews our present understanding of ultrastructure, organization, and functional characteristics of the erythrocyte membrane cytoskeleton. This two-dimensional fibrillar network of submembrane proteins can be visualized after extraction of lipids and integral membrane proteins by Triton X-100. Current data suggest that the major structural components of the cytoskeleton are heterodimers of double-stranded spectrin that form tetramers by head-to-head associations. The tetramers may be connected into a fibrillar meshwork by oligomers of actin. The control of membrane integrity by this network is illustrated by examples of two hemolyotic anemias characterized by marked membrane instability and vesiculation: 1) hereditary spherocytic anemia of the house mouse associated with spectrin deficiency and 2) hereditary pyropoikilocytosis, a hemolytic anemia in man characterized by thermal instability of the membrane and the presence of abnormal spectrin, which exhibits an increased propensity to thermal denaturation. Stabilization of the cytoskeletal network by covalent cross-links between the nearest cytoskeletal and integral membrane proteins results in a decrease of membrane deformability and a fixation of erythrocytes in their abnormal shape. Such cross-linkings include: 1) transamidative cross-links produced by introduction of Ca2+ (>0.5 mM) into fresh erythrocytes, and 2) intermolecular disulfide couplings, which are formed after extensive oxidation of fresh erythrocytes or after mild oxidation of ATP-depleted, but not fresh, erythrocytes. The significance of these cross-links in stabilization of shape of abnormal erythrocytes such as schistocytes remains to be determined. We conclude that spectrin and actin form a fibrillar submembrane network that plays an important role in control of membrane integrity, erythrocyte deformability, and stabilization of cells in abnormal shapes.

From partnerships to networks: new approaches for measuring U.S. National Heritage Area effectiveness.

PubMed

Laven, Daniel N; Krymkowski, Daniel H; Ventriss, Curtis L; Manning, Robert E; Mitchell, Nora J

2010-08-01

National Heritage Areas (NHAs) are an alternative and increasingly popular form of protected area management in the United States. NHAs seek to integrate environmental objectives with community and economic objectives at regional or landscape scales. NHA designations have increased rapidly in the last 20 years, generating a substantial need for evaluative information about (a) how NHAs work; (b) outcomes associated with the NHA process; and (c) the costs and benefits of investing public moneys into the NHA approach. Qualitative evaluation studies recently conducted at three NHAs have identified the importance of understanding network structure and function in the context of evaluating NHA management effectiveness. This article extends these case studies by examining quantitative network data from each of the sites. The authors analyze these data using both a descriptive approach and a statistically more robust approach known as exponential random graph modeling. Study findings indicate the presence of transitive structures and the absence of three-cycle structures in each of these networks. This suggests that these networks are relatively ''open,'' which may be desirable, given the uncertainty of the environments in which they operate. These findings also suggest, at least at the sites reported here, that the NHA approach may be an effective way to activate and develop networks of intersectoral organizational partners. Finally, this study demonstrates the utility of using quantitative network analysis to better understand the effectiveness of protected area management models that rely on partnership networks to achieve their intended outcomes.

Internal epithelia in Drosophila display rudimentary competence to form cytoplasmic networks of transgenic human vimentin.

PubMed

Gullmets, Josef; Torvaldson, Elin; Lindqvist, Julia; Imanishi, Susumu Y; Taimen, Pekka; Meinander, Annika; Eriksson, John E

2017-12-01

Cytoplasmic intermediate filaments (cIFs) are found in all eumetazoans, except arthropods. To investigate the compatibility of cIFs in arthropods, we expressed human vimentin (hVim), a cIF with filament-forming capacity in vertebrate cells and tissues, transgenically in Drosophila Transgenic hVim could be recovered from whole-fly lysates by using a standard procedure for intermediate filament (IF) extraction. When this procedure was used to test for the possible presence of IF-like proteins in flies, only lamins and tropomyosin were observed in IF-enriched extracts, thereby providing biochemical reinforcement to the paradigm that arthropods lack cIFs. In Drosophila , transgenic hVim was unable to form filament networks in S2 cells and mesenchymal tissues; however, cage-like vimentin structures could be observed around the nuclei in internal epithelia, which suggests that Drosophila retains selective competence for filament formation. Taken together, our results imply that although the filament network formation competence is partially lost in Drosophila , a rudimentary filament network formation ability remains in epithelial cells. As a result of the observed selective competence for cIF assembly in Drosophila , we hypothesize that internal epithelial cIFs were the last cIFs to disappear from arthropods.-Gullmets, J., Torvaldson, E., Lindqvist, J., Imanishi, S. Y., Taimen, P., Meinander, A., Eriksson, J. E. Internal epithelia in Drosophila display rudimentary competence to form cytoplasmic networks of transgenic human vimentin. © FASEB.

Social networks of patients with chronic skin lesions: nursing care.

PubMed

Bandeira, Luciana Alves; Santos, Maxuel Cruz Dos; Duarte, Êrica Rosalba Mallmann; Bandeira, Andrea Gonçalves; Riquinho, Deise Lisboa; Vieira, Letícia Becker

2018-01-01

To describe the social networks of patients with chronic skin damages. A qualitative study conducted through semi-structured interviews with nine subjects with chronic skin lesions from June 2016 to March 2017; we used the theoretical-methodological framework of Lia Sanicola's Social Network. The analysis of the relational maps revealed that the primary network was formed mainly by relatives and neighbors; its characteristics, such as: reduced size, low density and few exchanges/relationships, configures fragility in these links. The secondary network was essentially described by health services, and the nurse was cited as a linker in the therapeutic process. Faced with the fragility of the links and social isolation, the primary health care professionals are fundamental foundations for the construction of networks of social support and care for patients with chronic skin lesions.

The impact of socio-technical communication styles on the diversity and innovation potential of global science collaboratories

DOE PAGES

Ozmen, Ozgur; Yilmaz, Levent; Smith, Jeffrey

2016-02-09

Emerging cyber-infrastructure tools are enabling scientists to transparently co-develop, share, and communicate about real-time diverse forms of knowledge artifacts. In these environments, communication preferences of scientists are posited as an important factor affecting innovation capacity and robustness of social and knowledge network structures. Scientific knowledge creation in such communities is called global participatory science (GPS). Recently, using agent-based modeling and collective action theory as a basis, a complex adaptive social communication network model (CollectiveInnoSim) is implemented. This work leverages CollectiveInnoSim implementing communication preferences of scientists. Social network metrics and knowledge production patterns are used as proxy metrics to infer innovationmore » potential of emergent knowledge and collaboration networks. The objective is to present the underlying communication dynamics of GPS in a form of computational model and delineate the impacts of various communication preferences of scientists on innovation potential of the collaboration network. Ultimately, the insight gained can help policy-makers to design GPS environments and promote innovation.« less

The impact of socio-technical communication styles on the diversity and innovation potential of global science collaboratories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozmen, Ozgur; Yilmaz, Levent; Smith, Jeffrey

Emerging cyber-infrastructure tools are enabling scientists to transparently co-develop, share, and communicate about real-time diverse forms of knowledge artifacts. In these environments, communication preferences of scientists are posited as an important factor affecting innovation capacity and robustness of social and knowledge network structures. Scientific knowledge creation in such communities is called global participatory science (GPS). Recently, using agent-based modeling and collective action theory as a basis, a complex adaptive social communication network model (CollectiveInnoSim) is implemented. This work leverages CollectiveInnoSim implementing communication preferences of scientists. Social network metrics and knowledge production patterns are used as proxy metrics to infer innovationmore » potential of emergent knowledge and collaboration networks. The objective is to present the underlying communication dynamics of GPS in a form of computational model and delineate the impacts of various communication preferences of scientists on innovation potential of the collaboration network. Ultimately, the insight gained can help policy-makers to design GPS environments and promote innovation.« less

Design of fuzzy systems using neurofuzzy networks.

PubMed

Figueiredo, M; Gomide, F

1999-01-01

This paper introduces a systematic approach for fuzzy system design based on a class of neural fuzzy networks built upon a general neuron model. The network structure is such that it encodes the knowledge learned in the form of if-then fuzzy rules and processes data following fuzzy reasoning principles. The technique provides a mechanism to obtain rules covering the whole input/output space as well as the membership functions (including their shapes) for each input variable. Such characteristics are of utmost importance in fuzzy systems design and application. In addition, after learning, it is very simple to extract fuzzy rules in the linguistic form. The network has universal approximation capability, a property very useful in, e.g., modeling and control applications. Here we focus on function approximation problems as a vehicle to illustrate its usefulness and to evaluate its performance. Comparisons with alternative approaches are also included. Both, nonnoisy and noisy data have been studied and considered in the computational experiments. The neural fuzzy network developed here and, consequently, the underlying approach, has shown to provide good results from the accuracy, complexity, and system design points of view.

Process-based network decomposition reveals backbone motif structure

PubMed Central

Wang, Guanyu; Du, Chenghang; Chen, Hao; Simha, Rahul; Rong, Yongwu; Xiao, Yi; Zeng, Chen

2010-01-01

A central challenge in systems biology today is to understand the network of interactions among biomolecules and, especially, the organizing principles underlying such networks. Recent analysis of known networks has identified small motifs that occur ubiquitously, suggesting that larger networks might be constructed in the manner of electronic circuits by assembling groups of these smaller modules. Using a unique process-based approach to analyzing such networks, we show for two cell-cycle networks that each of these networks contains a giant backbone motif spanning all the network nodes that provides the main functional response. The backbone is in fact the smallest network capable of providing the desired functionality. Furthermore, the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. The process-based approach used in the above analysis has additional benefits: It is scalable, analytic (resulting in a single analyzable expression that describes the behavior), and computationally efficient (all possible minimal networks for a biological process can be identified and enumerated). PMID:20498084

Self-assembly of amphiphilic molecules in organic liquids

NASA Astrophysics Data System (ADS)

Tung, Shih-Huang

2007-12-01

Amphiphilic molecules are well-known for their ability to self-assemble in water to form structures such as micelles and vesicles. In comparison, much less is known about amphiphilic self-assembly in nonpolar organic liquids. Such "reverse" self assembly can produce many of the counterparts to structures found in water. In this dissertation, we focus on the formation and dynamics of such reverse structures. We seek to obtain fundamental insight into the driving forces for reverse self-assembly processes. Three specific types of reverse structures are studied: (a) reverse wormlike micelles, i.e., long, flexible micellar chains; (b) reverse vesicles, i.e., hollow containers enclosed by reverse bilayers; and (c) organogel networks. While our focus is on the fundamentals, we note that reverse structures can be useful in a variety of applications ranging from drug delivery, controlled release, hosts for enzymatic reactions, and templates for nanomaterials synthesis. In the first part of this study, we describe a new route for forming reverse wormlike micelles in nonpolar organic liquids. This route involves the addition of trace amounts of a bile salt to solutions of the phospholipid, lecithin. We show that bile salts, due to their unique "facially amphiphilic" structure, can promote the aggregation of lecithin molecules into these reverse micellar chains. The resulting samples are viscoelastic and show interesting rheological properties. Unusual trends are seen in the temperature dependence of their rheology, which indicates the importance of hydrogen-bonding interactions in the formation of these micelles. Another remarkable feature of their rheology is the presence of strain-stiffening, where the material becomes stiffer at high deformations. Strain-stiffening has been seen before for elastic gels of biopolymers; here, we demonstrate the same properties for viscoelastic micellar solutions. The second reverse aggregate we deal with is the reverse vesicle. We present a new route for forming stable unilamellar reverse vesicles, and this involves mixing short- and long-chain lipids (lecithins) with a trace of sodium chloride. The ratio of the short to long-chain lipid controls the type and size of self-assembled structure formed, and as this ratio is increased, a transition from reverse micelles to vesicles occurs. The structural changes can be explained in terms of molecular geometry, with the sodium chloride acting as a "glue" in binding lipid headgroups together through electrostatic interactions. The final part of this dissertation focuses on organogels. The two-tailed anionic surfactant, AOT, is well-known to form spherical reverse micelles in organic solvents. We have found that trace amounts (e.g., less than 1 mM) of the dihydroxy bile salt, sodium deoxycholate (SDC) can transform these dilute micellar solutions into self-supporting, transparent organogels. The structure and rheology of these organogels is reminiscent of the self-assembled networks formed by proteins such as actin in water. The organogels are based on networks of long, rigid, cylindrical filaments, with SDC molecules stacked together in the filament core.

Physics, stability, and dynamics of supply networks

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Lämmer, Stefan; Seidel, Thomas; Šeba, Pétr; Płatkowski, Tadeusz

2004-12-01

We show how to treat supply networks as physical transport problems governed by balance equations and equations for the adaptation of production speeds. Although the nonlinear behavior is different, the linearized set of coupled differential equations is formally related to those of mechanical or electrical oscillator networks. Supply networks possess interesting features due to their complex topology and directed links. We derive analytical conditions for absolute and convective instabilities. The empirically observed “bullwhip effect” in supply chains is explained as a form of convective instability based on resonance effects. Moreover, it is generalized to arbitrary supply networks. Their related eigenvalues are usually complex, depending on the network structure (even without loops). Therefore, their generic behavior is characterized by damped or growing oscillations. We also show that regular distribution networks possess two negative eigenvalues only, but perturbations generate a spectrum of complex eigenvalues.

Anatomy of triply-periodic network assemblies: characterizing skeletal and inter-domain surface geometry of block copolymer gyroids.

PubMed

Prasad, Ishan; Jinnai, Hiroshi; Ho, Rong-Ming; Thomas, Edwin L; Grason, Gregory M

2018-05-09

Triply-periodic networks (TPNs), like the well-known gyroid and diamond network phases, abound in soft matter assemblies, from block copolymers (BCPs), lyotropic liquid crystals and surfactants to functional architectures in biology. While TPNs are, in reality, volume-filling patterns of spatially-varying molecular composition, physical and structural models most often reduce their structure to lower-dimensional geometric objects: the 2D interfaces between chemical domains; and the 1D skeletons that thread through inter-connected, tubular domains. These lower-dimensional structures provide a useful basis of comparison to idealized geometries based on triply-periodic minimal, or constant-mean curvature surfaces, and shed important light on the spatially heterogeneous packing of molecular constituents that form the networks. Here, we propose a simple, efficient and flexible method to extract a 1D skeleton from 3D volume composition data of self-assembled networks. We apply this method to both self-consistent field theory predictions as well as experimental electron microtomography reconstructions of the double-gyroid phase of an ABA triblock copolymer. We further demonstrate how the analysis of 1D skeleton, 2D inter-domain surfaces, and combinations therefore, provide physical and structural insight into TPNs, across multiple length scales. Specifically, we propose and compare simple measures of network chirality as well as domain thickness, and analyze their spatial and statistical distributions in both ideal (theoretical) and non-ideal (experimental) double gyroid assemblies.

Distribution of shortest path lengths in a class of node duplication network models

NASA Astrophysics Data System (ADS)

Steinbock, Chanania; Biham, Ofer; Katzav, Eytan

2017-09-01

We present analytical results for the distribution of shortest path lengths (DSPL) in a network growth model which evolves by node duplication (ND). The model captures essential properties of the structure and growth dynamics of social networks, acquaintance networks, and scientific citation networks, where duplication mechanisms play a major role. Starting from an initial seed network, at each time step a random node, referred to as a mother node, is selected for duplication. Its daughter node is added to the network, forming a link to the mother node, and with probability p to each one of its neighbors. The degree distribution of the resulting network turns out to follow a power-law distribution, thus the ND network is a scale-free network. To calculate the DSPL we derive a master equation for the time evolution of the probability Pt(L =ℓ ) , ℓ =1 ,2 ,⋯ , where L is the distance between a pair of nodes and t is the time. Finding an exact analytical solution of the master equation, we obtain a closed form expression for Pt(L =ℓ ) . The mean distance 〈L〉 t and the diameter Δt are found to scale like lnt , namely, the ND network is a small-world network. The variance of the DSPL is also found to scale like lnt . Interestingly, the mean distance and the diameter exhibit properties of a small-world network, rather than the ultrasmall-world network behavior observed in other scale-free networks, in which 〈L〉 t˜lnlnt .

Pore network extraction from pore space images of various porous media systems

NASA Astrophysics Data System (ADS)

Yi, Zhixing; Lin, Mian; Jiang, Wenbin; Zhang, Zhaobin; Li, Haishan; Gao, Jian

2017-04-01

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

Organizing the public health-clinical health interface: theoretical bases.

PubMed

St-Pierre, Michèle; Reinharz, Daniel; Gauthier, Jacques-Bernard

2006-01-01

This article addresses the issue of the interface between public health and clinical health within the context of the search for networking approaches geared to a more integrated delivery of health services. The articulation of an operative interface is complicated by the fact that the definition of networking modalities involves complex intra- and interdisciplinary and intra- and interorganizational systems across which a new transversal dynamics of intervention practices and exchanges between service structures must be established. A better understanding of the situation is reached by shedding light on the rationale underlying the organizational methods that form the bases of the interface between these two sectors of activity. The Quebec experience demonstrates that neither the structural-functionalist approach, which emphasizes remodelling establishment structures and functions as determinants of integration, nor the structural-constructivist approach, which prioritizes distinct fields of practice in public health and clinical health, adequately serves the purpose of networking and integration. Consequently, a theoretical reframing is imperative. In this regard, structuration theory, which fosters the simultaneous study of methods of inter-structure coordination and inter-actor cooperation, paves the way for a better understanding of the situation and, in turn, to the emergence of new integration possibilities.

Different morphologic formation patterns of dark patches in the black-spotted frog (Pelophylax nigromaculata) and the Asiatic toad (Bufo gargarizans).

PubMed

Guangming, Gan; Tao, Zhao; Chao, Li; Moyan, Zhao

2017-01-01

The black-spotted frog (Pelophylax nigromaculata) and Asiatic toad (Bufo gargarizans), two relatively distantly related species, live in different habitats with different adaptive dark patches. To explain the formation of dark patches, the distribution patterns of melanin granules were examined with light microscopy and transmission electron microscopy. Melanin granules were produced and gathered into the "cap" structures on top of the nuclei in most epidermal cells. The "cap" structures may play a role in forming the dorsal dark patches coupled with three-layer melanophores, which can give rise to three layers of interconnected melanin networks in the dorsal dermis in P. nigromaculata. Epidermal melanocytes are rare and do not have a definitive role in forming dorsal dark patches in either P. nigromaculata or B. gargarizans. In B. gargarizans, the dermal melanophores only give rise to a single-layered melanin network, which hardly results in dark patches in the dorsal skin. However, the dermal melanophores migrate twice and form into pseudostratified networks, leading to dark patch formation in the ventral skin in B. gargarizans. The melanin granules precisely coregulate dark patches in the dermis and/or epidermis in P. nigromaculata and B. gargarizans. The dark patch formation depends on melanin granules in the epidermis or/and dermis in P. nigromaculata and B. gargarizans.

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

FAMILY STRUCTURE, DYNAMICS AND PSYCHIATRIC DISORDER IN INDIA1

PubMed Central

Chopra, H.D.

1984-01-01

SUMMARY This paper briefly reviews the literature on family structure, dynamics and relationships between family-jointness and different psychiatric disorders in India. Many recent studies indicate that the nuclear families are more vulnerable and plea is made for maintaining the traditional joint family system, even in some modified forms, because of its “built-in-immunity” and supportive networks. PMID:21966010

Particle-filled microporous materials

DOEpatents

McAllister, J.W.; Kinzer, K.E.; Mrozinski, J.S.; Johnson, E.J.; Dyrud, J.F.

1990-09-18

A microporous particulate-filled thermoplastic polymeric article is provided. The article can be in the form of a film, a fiber, or a tube. The article has a thermoplastic polymeric structure having a plurality of interconnected passageways to provide a network of communicating pores. The microporous structure contains discrete submicron or low micron-sized particulate filler, the particulate filler being substantially non-agglomerated. 3 figs.

Is Structure Dependence an Innate Constraint? New Experimental Evidence from Children's Complex-Question Production

ERIC Educational Resources Information Center

Ambridge, Ben; Rowland, Caroline F.; Pine, Julian M.

2008-01-01

According to Crain and Nakayama (1987), when forming complex yes/no questions, children do not make errors such as "Is the boy who smoking is crazy?" because they have innate knowledge of "structure dependence" and so will not move the auxiliary from the relative clause. However, simple recurrent networks are also able to avoid…

Local structural mechanism for frozen-in dynamics in metallic glasses

NASA Astrophysics Data System (ADS)

Liu, X. J.; Wang, S. D.; Wang, H.; Wu, Y.; Liu, C. T.; Li, M.; Lu, Z. P.

2018-04-01

The nature of the glass transition is a fundamental and long-standing intriguing issue in the condensed-matter physics and materials science community. In particular, the structural response by which a liquid is arrested dynamically to form a glass or amorphous solid upon approaching its freezing temperature [the glass transition temperature (Tg)] remains unclear. Various structural scenarios in terms of the percolation theory have been proposed recently to understand such a phenomenon; however, there is still no consensus on what the general percolation entity is and how the entity responds to the sudden slowdown dynamics during the glass transition. In this paper, we demonstrate that one-dimensional local linear ordering (LLO) is a universal structural motif associated with the glass transition for various metallic glasses. The quantitative evolution of LLO with temperature indicates that a percolating LLO network forms to serve as the backbone of the rigid glass solid when the temperature approaches the freezing point, resulting in the frozen-in dynamics accompanying the glass transition. The percolation transition occurs by pinning different LLO networks together, which only needs the introduction of a small number of "joint" atoms between them, and therefore the energy expenditure is very low.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

Formation of Helically Structured Chitin/CaCO3 Hybrids through an Approach Inspired by the Biomineralization Processes of Crustacean Cuticles.

PubMed

Matsumura, Shunichi; Kajiyama, Satoshi; Nishimura, Tatsuya; Kato, Takashi

2015-10-01

Chitin/CaCO3 hybrids with helical structures are formed through a biomineralization-inspired crystallization process under ambient conditions. Liquid-crystalline chitin whiskers are used as helically ordered templates. The liquid-crystalline structures are stabilized by acidic polymer networks which interact with the chitin templates. The crystallization of CaCO3 is conducted by soaking the templates in the colloidal suspension of amorphous CaCO3 (ACC) at room temperature. At the initial stage of crystallization, ACC particles are introduced inside the templates, and they crystallize to CaCO3 nanocrystals. The acidic polymer networks induce CaCO3 crystallization. The characterization of the resultant hybrids reveals that they possess helical order and homogeneous hybrid structures of chitin and CaCO3 , which resemble the structure and composition of the exoskeleton of crustaceans. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Is a cross-β-sheet structure of low molecular weight peptides necessary for the formation of fibrils and peptide hydrogels?

PubMed

Ilawe, Niranjan V; Schweitzer-Stenner, Reinhard; DiGuiseppi, David; Wong, Bryan M

2018-04-26

Short peptides have emerged as versatile building blocks for supramolecular structures and hydrogels. In particular, the presence of aromatic amino acid residues and/or aromatic end groups is generally considered to be a prerequisite for initiating aggregation of short peptides into nanotubes or cross β-sheet type fibrils. However, the cationic GAG tripeptide surprisingly violates these rules. Specifically, in water/ethanol mixtures, GAG peptides aggregate into very long crystalline fibrils at temperatures below 35 °C where they eventually form a spanning network structure and, thus, a hydrogel. Two gel phases are formed in this network, and they differ substantially in chirality and thickness of the underlying fibrils, their rheological parameters, and the kinetics of oligomerization, fibrilization, and gel formation. The spectroscopic data strongly suggests that the observed fibrils do not exhibit canonical cross β-sheet structures and are indicative of a yet unknown secondary conformation. To complement our unusual experimental observations in this perspective article, we performed large-scale DFT calculations to probe the geometry and spectroscopic properties of these GAG oligomers. Most importantly, our experimental and computational results yield rather unconventional structures that are not reminiscent of classical cross-β-sheet structures, and we give two extremely likely candidates for oligomer structures that are consistent with experimental amide I' profiles in IR and vibrational circular dichroism (VCD) spectra of the two gel phases.

[Regional geriatric care concept in the District of Lippe : Structural effects and network formation in the case management-based model project].

PubMed

Şahin, Charlotte; Iseringhausen, Olaf; Hower, Kira; Liebe, Constanze; Rethmeier-Hanke, Anja; Wedmann, Bernd

2018-04-01

Regional planning of healthcare requires special consideration for the complex needs of elderly, multimorbid people living in a domestic environment. In the District of Lippe, a hospital (Klinikum Lippe) and network of ambulatory care physicians (Ärztenetz Lippe) developed and tested a geriatric care network based on case management for geriatric patients living in a domestic environment. The establishment of the geriatric care network (e.g. promoting networking acceptance and implementation) was formatively evaluated, e. g. with qualitative methods. Data were acquired by guideline-based interviews with experts and analyzed by qualitative content analysis according to Mayring. Structural effects included forming a cross-sectoral and interdisciplinary network for a functioning care network and a geriatric care pathway. The practical work of case managers (CM) is essential for communication with patients, family members and care providers as well as integrating providers into the network. A critical factor was working together with general practitioners and the close cooperation with the hospital's department of geriatric. The quality of care is improved because of exchange of information between sectors and continuity in the course of care. In the District of Lippe the quality of care was improved and structures of care were integrated by the network according to the needs of the target group. The integrative perspective was achieved in particular by the geriatric care pathway and integration of providers into the communication and care process; however, the scope of this care model could not be extended into routine care due to the rigid and subdivided health care system.

A New Measure of Centrality for Brain Networks

PubMed Central

Joyce, Karen E.; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru

2010-01-01

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures. Degree identifies the most connected nodes, whereas betweenness centrality identifies those located on the most traveled paths. Eigenvector centrality considers nodes connected to other high degree nodes as highly central. In the work presented here, we propose a new centrality metric called leverage centrality that considers the extent of connectivity of a node relative to the connectivity of its neighbors. The leverage centrality of a node in a network is determined by the extent to which its immediate neighbors rely on that node for information. Although similar in concept, there are essential differences between eigenvector and leverage centrality that are discussed in this manuscript. Degree, betweenness, eigenvector, and leverage centrality were compared using functional brain networks generated from healthy volunteers. Functional cartography was also used to identify neighborhood hubs (nodes with high degree within a network neighborhood). Provincial hubs provide structure within the local community, and connector hubs mediate connections between multiple communities. Leverage proved to yield information that was not captured by degree, betweenness, or eigenvector centrality and was more accurate at identifying neighborhood hubs. We propose that this metric may be able to identify critical nodes that are highly influential within the network. PMID:20808943

Assessment of morphometric characteristics of Chakrar watershed in Madhya Pradesh India using geospatial technique

NASA Astrophysics Data System (ADS)

Soni, Sandeep

2017-09-01

The quantitative analysis of the watershed is important for the quantification of the channel network and to understand its geo-hydrological behaviour. Assessment of drainage network and their relative parameters have been quantitatively carried out for the Chakrar watershed of Madhya Pradesh, India, to understand the prevailing geological variation, topographic information and structural setup of the watershed and their interrelationship. Remote Sensing and Geographical Information System (GIS) has been used for the delineation and calculation of the morphometric parameters of the watershed. The Chakrar watershed is sprawled over an area of 415 km2 with dendritic, parallel and trellis drainage pattern. It is sub-divided into nine sub-watersheds. The study area is designated as sixth-order basin and lower and middle order streams mostly dominate the basin with the drainage density value of 2.46 km/km2 which exhibits gentle to steep slope terrain, medium dense vegetation, and less permeable with medium precipitation. The mean bifurcation value of the basin is 4.16 and value of nine sub-watersheds varies from 2.83 to 4.44 which reveals drainage networks formed on homogeneous rocks when the influences of geologic structures on the stream network is negligible. Form factor, circularity ratio and elongation ratio indicate an elongated basin shape having less prone to flood, lower erosion and sediment transport capacities. The results from the morphometric assessment of the watershed are important in water resources evaluation and its management and for the selection of recharge structure in the area for future water management.

A systematic review protocol: social network analysis of tobacco use.

PubMed

Maddox, Raglan; Davey, Rachel; Lovett, Ray; van der Sterren, Anke; Corbett, Joan; Cochrane, Tom

2014-08-08

Tobacco use is the single most preventable cause of death in the world. Evidence indicates that behaviours such as tobacco use can influence social networks, and that social network structures can influence behaviours. Social network analysis provides a set of analytic tools to undertake methodical analysis of social networks. We will undertake a systematic review to provide a comprehensive synthesis of the literature regarding social network analysis and tobacco use. The review will answer the following research questions: among participants who use tobacco, does social network structure/position influence tobacco use? Does tobacco use influence peer selection? Does peer selection influence tobacco use? We will follow the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines and search the following databases for relevant articles: CINAHL (Cumulative Index to Nursing and Allied Health Literature); Informit Health Collection; PsycINFO; PubMed/MEDLINE; Scopus/Embase; Web of Science; and the Wiley Online Library. Keywords include tobacco; smoking; smokeless; cigarettes; cigar and 'social network' and reference lists of included articles will be hand searched. Studies will be included that provide descriptions of social network analysis of tobacco use.Qualitative, quantitative and mixed method data that meets the inclusion criteria for the review, including methodological rigour, credibility and quality standards, will be synthesized using narrative synthesis. Results will be presented using outcome statistics that address each of the research questions. This systematic review will provide a timely evidence base on the role of social network analysis of tobacco use, forming a basis for future research, policy and practice in this area. This systematic review will synthesise the evidence, supporting the hypothesis that social network structures can influence tobacco use. This will also include exploring the relationship between social network structure, social network position, peer selection, peer influence and tobacco use across all age groups, and across different demographics. The research will increase our understanding of social networks and their impact on tobacco use, informing policy and practice while highlighting gaps in the literature and areas for further research.

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Layered structures of organic/inorganic hybrid halide perovskites

NASA Astrophysics Data System (ADS)

Huan, Tran Doan; Tuoc, Vu Ngoc; Minh, Nguyen Viet

2016-03-01

Organic-inorganic hybrid halide perovskites, in which the A cations of an ABX3 perovskite are replaced by organic cations, may be used for photovoltaic and solar thermoelectric applications. In this contribution, we systematically study three lead-free hybrid perovskites, i.e., methylammonium tin iodide CH3NH3SnI3 , ammonium tin iodide NH4SnI3 , and formamidnium tin iodide HC (NH2)2SnI3 by first-principles calculations. We find that in addition to the commonly known motif in which the corner-shared SnI6 octahedra form a three-dimensional network, these materials may also favor a two-dimensional (layered) motif formed by alternating layers of the SnI6 octahedra and the organic cations. These two motifs are nearly equal in free energy and are separated by low barriers. These layered structures features many flat electronic bands near the band edges, making their electronic structures significantly different from those of the structural phases composed of three-dimension networks of SnI6 octahedra. Furthermore, because the electronic structures of HC (NH2)2SnI3 are found to be rather similar to those of CH3NH3SnI3 , formamidnium tin iodide may also be promising for the applications of methylammonium tin iodide.

Global network structure of dominance hierarchy of ant workers.

PubMed

Shimoji, Hiroyuki; Abe, Masato S; Tsuji, Kazuki; Masuda, Naoki

2014-10-06

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Using arborescences to estimate hierarchicalness in directed complex networks

PubMed Central

2018-01-01

Complex networks are a useful tool for the understanding of complex systems. One of the emerging properties of such systems is their tendency to form hierarchies: networks can be organized in levels, with nodes in each level exerting control on the ones beneath them. In this paper, we focus on the problem of estimating how hierarchical a directed network is. We propose a structural argument: a network has a strong top-down organization if we need to delete only few edges to reduce it to a perfect hierarchy—an arborescence. In an arborescence, all edges point away from the root and there are no horizontal connections, both characteristics we desire in our idealization of what a perfect hierarchy requires. We test our arborescence score in synthetic and real-world directed networks against the current state of the art in hierarchy detection: agony, flow hierarchy and global reaching centrality. These tests highlight that our arborescence score is intuitive and we can visualize it; it is able to better distinguish between networks with and without a hierarchical structure; it agrees the most with the literature about the hierarchy of well-studied complex systems; and it is not just a score, but it provides an overall scheme of the underlying hierarchy of any directed complex network. PMID:29381761

Global network structure of dominance hierarchy of ant workers

PubMed Central

Shimoji, Hiroyuki; Abe, Masato S.; Tsuji, Kazuki; Masuda, Naoki

2014-01-01

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. PMID:25100318

The Private Lives of Minerals: Social Network Analysis Applied to Mineralogy and Petrology

NASA Astrophysics Data System (ADS)

Hazen, R. M.; Morrison, S. M.; Fox, P. A.; Golden, J. J.; Downs, R. T.; Eleish, A.; Prabhu, A.; Li, C.; Liu, C.

2016-12-01

Comprehensive databases of mineral species (rruff.info/ima) and their geographic localities and co-existing mineral assemblages (mindat.org) reveal patterns of mineral association and distribution that mimic social networks, as commonly applied to such varied topics as social media interactions, the spread of disease, terrorism networks, and research collaborations. Applying social network analysis (SNA) to common assemblages of rock-forming igneous and regional metamorphic mineral species, we find patterns of cohesion, segregation, density, and cliques that are similar to those of human social networks. These patterns highlight classic trends in lithologic evolution and are illustrated with sociograms, in which mineral species are the "nodes" and co-existing species form "links." Filters based on chemistry, age, structural group, and other parameters highlight visually both familiar and new aspects of mineralogy and petrology. We quantify sociograms with SNA metrics, including connectivity (based on the frequency of co-occurrence of mineral pairs), homophily (the extent to which co-existing mineral species share compositional and other characteristics), network closure (based on the degree of network interconnectivity), and segmentation (as revealed by isolated "cliques" of mineral species). Exploitation of large and growing mineral data resources with SNA offers promising avenues for discovering previously hidden trends in mineral diversity-distribution systematics, as well as providing new pedagogical approaches to teaching mineralogy and petrology.

A network dynamics approach to chemical reaction networks

NASA Astrophysics Data System (ADS)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

Reducing emergency bed-days for older people? Network governance lessons from the 'Improving the Future for Older People' programme.

PubMed

Sheaff, Rod; Windle, Karen; Wistow, Gerald; Ashby, Sue; Beech, Roger; Dickinson, Angela; Henderson, Catherine; Knapp, Martin

2014-04-01

In 2007, the UK government set performance targets and public service agreements to control the escalation of emergency bed-days. Some years earlier, nine English local authorities had each created local networks with their health and third sector partners to tackle this increase. These networks formed the 'Improving the Future for Older People' initiative (IFOP), one strand of the national 'Innovation Forum' programme, set up in 2003. The nine sites set themselves one headline target to be achieved jointly over three years; a 20 per cent reduction in the number of emergency bed-days used by people aged 75 and over. Three ancillary targets were also monitored: emergency admissions, delayed discharges and project sustainability. Collectively the sites exceeded their headline target. Using a realistic evaluation approach, we explored which aspects of network governance appeared to have contributed to these emergency bed-day reductions. We found no simple link between network governance type and outcomes. The governance features associated with an effective IFOP network appeared to suggest that the selection and implementation of a small number of evidence-based services was central to networks' effectiveness. Each service needed to be coordinated by a network-based strategic group and hierarchically implemented at operational level by the responsible network member. Having a network-based implementation group with a 'joined-at-the-top' governance structure also appeared to promote network effectiveness. External factors, including NHS incentives, health reorganisations and financial targets similarly contributed to differences in performance. Targets and financial incentives could focus action but undermine horizontal networking. Local networks should specify which interventions network structures are intended to deliver. Effective projects are those likely to be evidence based, unique to the network and difficult to implement through vertical structures alone. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effect of Amphiphiles on the Rheology of Triglyceride Networks

NASA Astrophysics Data System (ADS)

Seth, Jyoti

2014-11-01

Networks of aggregated crystallites form the structural backbone of many products from the food, cosmetic and pharmaceutical industries. Such materials are generally formulated by cooling a saturated solution to yield the desired solid fraction. Crystal nucleation and growth followed by aggregation leads to formation of a space percolating fractal-network. It is understood that microstructural hierarchy and particle-particle interactions determine material behavior during processing, storage and use. In this talk, rheology of suspensions of triglycerides (TAG, like tristearin) will be explored. TAGs exhibit a rich assortment of polymorphs and form suspensions that are evidently sensitive to surface modifying additives like surfactants and polymers. Here, a theoretical framework will be presented for suspensions containing TAG crystals interacting via pairwise potentials. The work builds on existing models of fractal aggregates to understand microstructure and its correlation with material rheology. Effect of amphiphilic additives is derived through variation of particle-particle interactions. Theoretical predictions for storage modulus will be compared against experimental observations and data from the literature and micro structural predictions against microscopy. Such a theory may serve as a step towards predicting short and long-term behavior of aggregated suspensions formulated via crystallization.

Prediction in Health Domain Using Bayesian Networks Optimization Based on Induction Learning Techniques

NASA Astrophysics Data System (ADS)

Felgaer, Pablo; Britos, Paola; García-Martínez, Ramón

A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

Filamentary structures that self-organize due to adhesion

NASA Astrophysics Data System (ADS)

Sengab, A.; Picu, R. C.

2018-03-01

We study the self-organization of random collections of elastic filaments that interact adhesively. The evolution from an initial fully random quasi-two-dimensional state is controlled by filament elasticity, adhesion and interfilament friction, and excluded volume. Three outcomes are possible: the system may remain locked in the initial state, may organize into isolated fiber bundles, or may form a stable, connected network of bundles. The range of system parameters leading to each of these states is identified. The network of bundles is subisostatic and is stabilized by prestressed triangular features forming at bundle-to-bundle nodes, similar to the situation in foams. Interfiber friction promotes locking and expands the parametric range of nonevolving systems.

Hot Spots in a Network of Functional Sites

PubMed Central

Ozbek, Pemra; Soner, Seren; Haliloglu, Turkan

2013-01-01

It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation. PMID:24023934

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Subcommunities and Their Mutual Relationships in a Transaction Network

NASA Astrophysics Data System (ADS)

Iino, T.; Iyetomi, H.

We investigate a Japanese transaction network consisting ofabout 800 thousand firms (nodes) and four million business relations (links) with focus on its modular structure. Communities detected by maximizing modularity often are dominated by firms with common features or behaviors in the network, such as characterized by regions or industry sectors. However, it is well known that the modularity optimization approach has a resolution limit problem, that is, it fails in identifying fine communities buried in large communities. To unfold such hidden structures, we apply the community detection to each of subnetworks formed by isolating those communities from the whole body. Subcommunities thus identified are composed of firms with finer regions, more specified sectors or business affiliations. Also we introduce a new idea of reduced modularity matrix to measure the strength of relations between (sub)communities.

Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

PubMed Central

2018-01-01

Abstract It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate in multiple spike sequences at multiple between-spike time delays, the possible complexity of networks is prohibitively large. We present a novel approach that is capable of (1) extracting spike timing networks regardless of their sequence complexity, and (2) that describes their spiking sequences with high temporal precision. We achieve this by decomposing frequency-transformed neuronal spiking into separate networks, characterizing each network’s spike sequence by a time delay per neuron, forming a spike sequence timeline. These networks provide a detailed template for an investigation of the experimental relevance of their spike sequences. Using simulated spike timing networks, we show network extraction is robust to spiking noise, spike timing jitter, and partial occurrences of the involved spike sequences. Using rat multineuron recordings, we demonstrate the approach is capable of revealing real spike timing networks with sub-millisecond temporal precision. By uncovering spike timing networks, the prevalence, structure, and function of complex spike sequences can be investigated in greater detail, allowing us to gain a better understanding of their role in neuronal functioning. PMID:29789811

Network morphospace

PubMed Central

Avena-Koenigsberger, Andrea; Goñi, Joaquín; Solé, Ricard; Sporns, Olaf

2015-01-01

The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the ‘network morphospace’. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common ‘morphological’ characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems. PMID:25540237

Coevolution of cooperation and network structure under natural selection

NASA Astrophysics Data System (ADS)

Yang, D.-P.; Lin, H.; Shuai, J. W.

2011-02-01

A coevolution model by coupling mortality and fertility selection is introduced to investigate the evolution of cooperation and network structure in the prisoner's dilemma game. The cooperation level goes through a continuous phase transition vs. defection temptation b for low mortality selection intensity β and through a discontinuous one for infinite β. The cooperation level is enhanced most at β≈1 for any b. The local and global properties of the network structure, such as cluster and cooperating k-core, are investigated for the understanding of cooperation evolution. Cooperation is promoted by forming a tight cooperating k-core at moderate β, but too large β will destroy the cooperating k-core rapidly resulting in a rapid drop of the cooperation level. Importantly, the infinite β changes the normalized sucker's payoff S from 0 to 1-b and its dynamics of the cooperation level undergoes a very slow power-law decay, which leads the evolution into the regime of neutral evolution.

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

PubMed Central

Bolser, Dan; Dafas, Panos; Harrington, Richard; Park, Jong; Schroeder, Michael

2003-01-01

Background Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. Results We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Conclusions Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level. PMID:14531933