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Sample records for networks evolve rapidly

  1. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  2. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  3. Evolving phenotypic networks in silico.

    Science.gov (United States)

    François, Paul

    2014-11-01

    Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

  4. Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

    Science.gov (United States)

    Steiner, Christopher F.

    2012-01-01

    The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

  5. Directed evolution to re-adapt a co-evolved network within an enzyme.

    Science.gov (United States)

    Strafford, John; Payongsri, Panwajee; Hibbert, Edward G; Morris, Phattaraporn; Batth, Sukhjeet S; Steadman, David; Smith, Mark E B; Ward, John M; Hailes, Helen C; Dalby, Paul A

    2012-01-01

    We have previously used targeted active-site saturation mutagenesis to identify a number of transketolase single mutants that improved activity towards either glycolaldehyde (GA), or the non-natural substrate propionaldehyde (PA). Here, all attempts to recombine the singles into double mutants led to unexpected losses of specific activity towards both substrates. A typical trade-off occurred between soluble expression levels and specific activity for all single mutants, but many double mutants decreased both properties more severely suggesting a critical loss of protein stability or native folding. Statistical coupling analysis (SCA) of a large multiple sequence alignment revealed a network of nine co-evolved residues that affected all but one double mutant. Such networks maintain important functional properties such as activity, specificity, folding, stability, and solubility and may be rapidly disrupted by introducing one or more non-naturally occurring mutations. To identify variants of this network that would accept and improve upon our best D469 mutants for activity towards PA, we created a library of random single, double and triple mutants across seven of the co-evolved residues, combining our D469 variants with only naturally occurring mutations at the remaining sites. A triple mutant cluster at D469, E498 and R520 was found to behave synergistically for the specific activity towards PA. Protein expression was severely reduced by E498D and improved by R520Q, yet variants containing both mutations led to improved specific activity and enzyme expression, but with loss of solubility and the formation of inclusion bodies. D469S and R520Q combined synergistically to improve k(cat) 20-fold for PA, more than for any previous transketolase mutant. R520Q also doubled the specific activity of the previously identified D469T to create our most active transketolase mutant to date. Our results show that recombining active-site mutants obtained by saturation mutagenesis

  6. A general evolving model for growing bipartite networks

    International Nuclear Information System (INIS)

    Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin

    2012-01-01

    In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.

  7. Surrogate-assisted identification of influences of network construction on evolving weighted functional networks

    Science.gov (United States)

    Stahn, Kirsten; Lehnertz, Klaus

    2017-12-01

    We aim at identifying factors that may affect the characteristics of evolving weighted networks derived from empirical observations. To this end, we employ various chains of analysis that are often used in field studies for a data-driven derivation and characterization of such networks. As an example, we consider fully connected, weighted functional brain networks before, during, and after epileptic seizures that we derive from multichannel electroencephalographic data recorded from epilepsy patients. For these evolving networks, we estimate clustering coefficient and average shortest path length in a time-resolved manner. Lastly, we make use of surrogate concepts that we apply at various levels of the chain of analysis to assess to what extent network characteristics are dominated by properties of the electroencephalographic recordings and/or the evolving weighted networks, which may be accessible more easily. We observe that characteristics are differently affected by the unavoidable referencing of the electroencephalographic recording, by the time-series-analysis technique used to derive the properties of network links, and whether or not networks were normalized. Importantly, for the majority of analysis settings, we observe temporal evolutions of network characteristics to merely reflect the temporal evolutions of mean interaction strengths. Such a property of the data may be accessible more easily, which would render the weighted network approach—as used here—as an overly complicated description of simple aspects of the data.

  8. Social networks: Evolving graphs with memory dependent edges

    Science.gov (United States)

    Grindrod, Peter; Parsons, Mark

    2011-10-01

    The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

  9. Interactively Evolving Compositional Sound Synthesis Networks

    DEFF Research Database (Denmark)

    Jónsson, Björn Þór; Hoover, Amy K.; Risi, Sebastian

    2015-01-01

    the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first......While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved...

  10. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  11. Knowledge extraction from evolving spiking neural networks with rank order population coding.

    Science.gov (United States)

    Soltic, Snjezana; Kasabov, Nikola

    2010-12-01

    This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

  12. Resiliently evolving supply-demand networks

    Science.gov (United States)

    Rubido, Nicolás; Grebogi, Celso; Baptista, Murilo S.

    2014-01-01

    The ability to design a transport network such that commodities are brought from suppliers to consumers in a steady, optimal, and stable way is of great importance for distribution systems nowadays. In this work, by using the circuit laws of Kirchhoff and Ohm, we provide the exact capacities of the edges that an optimal supply-demand network should have to operate stably under perturbations, i.e., without overloading. The perturbations we consider are the evolution of the connecting topology, the decentralization of hub sources or sinks, and the intermittence of supplier and consumer characteristics. We analyze these conditions and the impact of our results, both on the current United Kingdom power-grid structure and on numerically generated evolving archetypal network topologies.

  13. Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability.

    Directory of Open Access Journals (Sweden)

    Kirsten H Ten Tusscher

    2011-10-01

    Full Text Available A major goal of evolutionary developmental biology (evo-devo is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs. This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy. In the second scenario segments and domains evolve simultaneously (SS strategy. We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation

  14. Network Analysis of Earth's Co-Evolving Geosphere and Biosphere

    Science.gov (United States)

    Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.

    2017-12-01

    A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In

  15. Recommendation in evolving online networks

    Science.gov (United States)

    Hu, Xiao; Zeng, An; Shang, Ming-Sheng

    2016-02-01

    Recommender system is an effective tool to find the most relevant information for online users. By analyzing the historical selection records of users, recommender system predicts the most likely future links in the user-item network and accordingly constructs a personalized recommendation list for each user. So far, the recommendation process is mostly investigated in static user-item networks. In this paper, we propose a model which allows us to examine the performance of the state-of-the-art recommendation algorithms in evolving networks. We find that the recommendation accuracy in general decreases with time if the evolution of the online network fully depends on the recommendation. Interestingly, some randomness in users' choice can significantly improve the long-term accuracy of the recommendation algorithm. When a hybrid recommendation algorithm is applied, we find that the optimal parameter gradually shifts towards the diversity-favoring recommendation algorithm, indicating that recommendation diversity is essential to keep a high long-term recommendation accuracy. Finally, we confirm our conclusions by studying the recommendation on networks with the real evolution data.

  16. Degree distribution of a new model for evolving networks

    Indian Academy of Sciences (India)

    on intuitive but realistic consideration that nodes are added to the network with both preferential and random attachments. The degree distribution of the model is between a power-law and an exponential decay. Motivated by the features of network evolution, we introduce a new model of evolving networks, incorporating the ...

  17. Weighted Evolving Networks with Self-organized Communities

    International Nuclear Information System (INIS)

    Xie Zhou; Wang Xiaofan; Li Xiang

    2008-01-01

    In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of ν ≥ 1, γ > 2, and α > 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness

  18. Regional and Inter-Regional Effects in Evolving Climate Networks

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Vejmelka, Martin; Donner, R.; Marwan, N.; Kurths, J.; Paluš, Milan

    2014-01-01

    Roč. 21, č. 2 (2014), s. 451-462 ISSN 1023-5809 R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : climate networks * evolving networks * principal component analysis * network connectivity * El Nino Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.987, year: 2014

  19. On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

    Science.gov (United States)

    Chen, Bor-Sen; Lin, Ying-Po

    2011-01-01

    In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

  20. Communicability across evolving networks.

    Science.gov (United States)

    Grindrod, Peter; Parsons, Mark C; Higham, Desmond J; Estrada, Ernesto

    2011-04-01

    Many natural and technological applications generate time-ordered sequences of networks, defined over a fixed set of nodes; for example, time-stamped information about "who phoned who" or "who came into contact with who" arise naturally in studies of communication and the spread of disease. Concepts and algorithms for static networks do not immediately carry through to this dynamic setting. For example, suppose A and B interact in the morning, and then B and C interact in the afternoon. Information, or disease, may then pass from A to C, but not vice versa. This subtlety is lost if we simply summarize using the daily aggregate network given by the chain A-B-C. However, using a natural definition of a walk on an evolving network, we show that classic centrality measures from the static setting can be extended in a computationally convenient manner. In particular, communicability indices can be computed to summarize the ability of each node to broadcast and receive information. The computations involve basic operations in linear algebra, and the asymmetry caused by time's arrow is captured naturally through the noncommutativity of matrix-matrix multiplication. Illustrative examples are given for both synthetic and real-world communication data sets. We also discuss the use of the new centrality measures for real-time monitoring and prediction.

  1. Evolving RBF neural networks for adaptive soft-sensor design.

    Science.gov (United States)

    Alexandridis, Alex

    2013-12-01

    This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

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

    Directory of Open Access Journals (Sweden)

    Christian Torres-Sosa

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

  3. A Weighted Evolving Network with Community Size Preferential Attachment

    International Nuclear Information System (INIS)

    Zhuo Zhiwei; Shan Erfang

    2010-01-01

    Community structure is an important characteristic in real complex network. It is a network consists of groups of nodes within which links are dense but among which links are sparse. In this paper, the evolving network include node, link and community growth and we apply the community size preferential attachment and strength preferential attachment to a growing weighted network model and utilize weight assigning mechanism from BBV model. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

  4. How People Interact in Evolving Online Affiliation Networks

    Science.gov (United States)

    Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

    2012-07-01

    The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

  5. Quantum games on evolving random networks

    OpenAIRE

    Pawela, Łukasz

    2015-01-01

    We study the advantages of quantum strategies in evolutionary social dilemmas on evolving random networks. We focus our study on the two-player games: prisoner's dilemma, snowdrift and stag-hunt games. The obtained result show the benefits of quantum strategies for the prisoner's dilemma game. For the other two games, we obtain regions of parameters where the quantum strategies dominate, as well as regions where the classical strategies coexist.

  6. Functional Topology of Evolving Urban Drainage Networks

    Science.gov (United States)

    Yang, Soohyun; Paik, Kyungrock; McGrath, Gavan S.; Urich, Christian; Krueger, Elisabeth; Kumar, Praveen; Rao, P. Suresh C.

    2017-11-01

    We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [P>(A≥δ>)˜aδ-ɛ]. For the smallest UDNs ((A≥δ>) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [P>(A≥δ>)=aδ-ɛexp⁡>(-cδ>)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent ɛ for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.

  7. An evolving network model with modular growth

    International Nuclear Information System (INIS)

    Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi

    2012-01-01

    In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)

  8. Evolving spiking networks with variable resistive memories.

    Science.gov (United States)

    Howard, Gerard; Bull, Larry; de Lacy Costello, Ben; Gale, Ella; Adamatzky, Andrew

    2014-01-01

    Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural networks. The evolutionary design process exploits parameter self-adaptation and allows the topology and synaptic weights to be evolved for each network in an autonomous manner. Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution. These variable resistive networks are evaluated on a noisy robotic dynamic-reward scenario against two static resistive memories and a system containing standard connections only. The results indicate that the extra behavioural degrees of freedom available to the networks incorporating variable resistive memories enable them to outperform the comparative synapse types.

  9. Gravity Effects on Information Filtering and Network Evolving

    Science.gov (United States)

    Liu, Jin-Hu; Zhang, Zi-Ke; Chen, Lingjiao; Liu, Chuang; Yang, Chengcheng; Wang, Xueqi

    2014-01-01

    In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on two real-world data sets, Del.icio.us and MovieLens, show that it can not only enhance the algorithmic performance, but can also better characterize the properties of real networks. This work may shed some light on the in-depth understanding of the effect of gravity model. PMID:24622162

  10. A new evolutionary system for evolving artificial neural networks.

    Science.gov (United States)

    Yao, X; Liu, Y

    1997-01-01

    This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

  11. Delineating slowly and rapidly evolving fractions of the Drosophila genome.

    Science.gov (United States)

    Keith, Jonathan M; Adams, Peter; Stephen, Stuart; Mattick, John S

    2008-05-01

    Evolutionary conservation is an important indicator of function and a major component of bioinformatic methods to identify non-protein-coding genes. We present a new Bayesian method for segmenting pairwise alignments of eukaryotic genomes while simultaneously classifying segments into slowly and rapidly evolving fractions. We also describe an information criterion similar to the Akaike Information Criterion (AIC) for determining the number of classes. Working with pairwise alignments enables detection of differences in conservation patterns among closely related species. We analyzed three whole-genome and three partial-genome pairwise alignments among eight Drosophila species. Three distinct classes of conservation level were detected. Sequences comprising the most slowly evolving component were consistent across a range of species pairs, and constituted approximately 62-66% of the D. melanogaster genome. Almost all (>90%) of the aligned protein-coding sequence is in this fraction, suggesting much of it (comprising the majority of the Drosophila genome, including approximately 56% of non-protein-coding sequences) is functional. The size and content of the most rapidly evolving component was species dependent, and varied from 1.6% to 4.8%. This fraction is also enriched for protein-coding sequence (while containing significant amounts of non-protein-coding sequence), suggesting it is under positive selection. We also classified segments according to conservation and GC content simultaneously. This analysis identified numerous sub-classes of those identified on the basis of conservation alone, but was nevertheless consistent with that classification. Software, data, and results available at www.maths.qut.edu.au/-keithj/. Genomic segments comprising the conservation classes available in BED format.

  12. Link Prediction in Evolving Networks Based on Popularity of Nodes.

    Science.gov (United States)

    Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

    2017-08-02

    Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

  13. Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

    CERN Document Server

    Knabe, Johannes F

    2013-01-01

    Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

  14. Evolving Deep Networks Using HPC

    Energy Technology Data Exchange (ETDEWEB)

    Young, Steven R. [ORNL, Oak Ridge; Rose, Derek C. [ORNL, Oak Ridge; Johnston, Travis [ORNL, Oak Ridge; Heller, William T. [ORNL, Oak Ridge; Karnowski, thomas P. [ORNL, Oak Ridge; Potok, Thomas E. [ORNL, Oak Ridge; Patton, Robert M. [ORNL, Oak Ridge; Perdue, Gabriel [Fermilab; Miller, Jonathan [Santa Maria U., Valparaiso

    2017-01-01

    While a large number of deep learning networks have been studied and published that produce outstanding results on natural image datasets, these datasets only make up a fraction of those to which deep learning can be applied. These datasets include text data, audio data, and arrays of sensors that have very different characteristics than natural images. As these “best” networks for natural images have been largely discovered through experimentation and cannot be proven optimal on some theoretical basis, there is no reason to believe that they are the optimal network for these drastically different datasets. Hyperparameter search is thus often a very important process when applying deep learning to a new problem. In this work we present an evolutionary approach to searching the possible space of network hyperparameters and construction that can scale to 18, 000 nodes. This approach is applied to datasets of varying types and characteristics where we demonstrate the ability to rapidly find best hyperparameters in order to enable practitioners to quickly iterate between idea and result.

  15. Do motifs reflect evolved function?--No convergent evolution of genetic regulatory network subgraph topologies.

    Science.gov (United States)

    Knabe, Johannes F; Nehaniv, Chrystopher L; Schilstra, Maria J

    2008-01-01

    Methods that analyse the topological structure of networks have recently become quite popular. Whether motifs (subgraph patterns that occur more often than in randomized networks) have specific functions as elementary computational circuits has been cause for debate. As the question is difficult to resolve with currently available biological data, we approach the issue using networks that abstractly model natural genetic regulatory networks (GRNs) which are evolved to show dynamical behaviors. Specifically one group of networks was evolved to be capable of exhibiting two different behaviors ("differentiation") in contrast to a group with a single target behavior. In both groups we find motif distribution differences within the groups to be larger than differences between them, indicating that evolutionary niches (target functions) do not necessarily mold network structure uniquely. These results show that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Moreover, analysis of motif functional relevance by lesioning did not suggest that motifs were of greater importance to the functioning of the network than arbitrary subgraph patterns. Only when drastically restricting network size, so that one motif corresponds to a whole functionally evolved network, was preference for particular connection patterns found. This suggests that in non-restricted, bigger networks, entanglement with the rest of the network hinders topological subgraph analysis.

  16. An evolving model of online bipartite networks

    Science.gov (United States)

    Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang

    2013-12-01

    Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.

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

    International Nuclear Information System (INIS)

    Jezewski, W.

    2002-01-01

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

  18. Dynamical community structure of populations evolving on genotype networks

    International Nuclear Information System (INIS)

    Capitán, José A.; Aguirre, Jacobo; Manrubia, Susanna

    2015-01-01

    Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics

  19. Evolving ATLAS Computing For Today’s Networks

    CERN Document Server

    Campana, S; The ATLAS collaboration; Jezequel, S; Negri, G; Serfon, C; Ueda, I

    2012-01-01

    The ATLAS computing infrastructure was designed many years ago based on the assumption of rather limited network connectivity between computing centres. ATLAS sites have been organized in a hierarchical model, where only a static subset of all possible network links can be exploited and a static subset of well connected sites (CERN and the T1s) can cover important functional roles such as hosting master copies of the data. The pragmatic adoption of such simplified approach, in respect of a more relaxed scenario interconnecting all sites, was very beneficial during the commissioning of the ATLAS distributed computing system and essential in reducing the operational cost during the first two years of LHC data taking. In the mean time, networks evolved far beyond this initial scenario: while a few countries are still poorly connected with the rest of the WLCG infrastructure, most of the ATLAS computing centres are now efficiently interlinked. Our operational experience in running the computing infrastructure in ...

  20. Social networks and online environments: when science and practice co-evolve

    OpenAIRE

    Rosen, Devan; Barnett, George A.; Kim, Jang Hyun

    2011-01-01

    The science of social network analysis has co-evolved with the development of online environments and computer-mediated communication. Unique and precise data available from computer and information systems have allowed network scientists to explore novel social phenomena and develop new methods. Additionally, advances in the structural analysis and visualization of computer-mediated social networks have informed developers and shaped the design of social media tools. This article reviews som...

  1. Adaptive control of dynamical synchronization on evolving networks with noise disturbances

    Science.gov (United States)

    Yuan, Wu-Jie; Zhou, Jian-Fang; Sendiña-Nadal, Irene; Boccaletti, Stefano; Wang, Zhen

    2018-02-01

    In real-world networked systems, the underlying structure is often affected by external and internal unforeseen factors, making its evolution typically inaccessible. An adaptive strategy was introduced for maintaining synchronization on unpredictably evolving networks [Sorrentino and Ott, Phys. Rev. Lett. 100, 114101 (2008), 10.1103/PhysRevLett.100.114101], which yet does not consider the noise disturbances widely existing in networks' environments. We provide here strategies to control dynamical synchronization on slowly and unpredictably evolving networks subjected to noise disturbances which are observed at the node and at the communication channel level. With our strategy, the nodes' coupling strength is adaptively adjusted with the aim of controlling synchronization, and according only to their received signal and noise disturbances. We first provide a theoretical analysis of the control scheme by introducing an error potential function to seek for the minimization of the synchronization error. Then, we show numerical experiments which verify our theoretical results. In particular, it is found that our adaptive strategy is effective even for the case in which the dynamics of the uncontrolled network would be explosive (i.e., the states of all the nodes would diverge to infinity).

  2. Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design

    Science.gov (United States)

    Schaffer, J. David

    2015-06-01

    Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.

  3. Snake venoms are integrated systems, but abundant venom proteins evolve more rapidly.

    Science.gov (United States)

    Aird, Steven D; Aggarwal, Shikha; Villar-Briones, Alejandro; Tin, Mandy Man-Ying; Terada, Kouki; Mikheyev, Alexander S

    2015-08-28

    While many studies have shown that extracellular proteins evolve rapidly, how selection acts on them remains poorly understood. We used snake venoms to understand the interaction between ecology, expression level, and evolutionary rate in secreted protein systems. Venomous snakes employ well-integrated systems of proteins and organic constituents to immobilize prey. Venoms are generally optimized to subdue preferred prey more effectively than non-prey, and many venom protein families manifest positive selection and rapid gene family diversification. Although previous studies have illuminated how individual venom protein families evolve, how selection acts on venoms as integrated systems, is unknown. Using next-generation transcriptome sequencing and mass spectrometry, we examined microevolution in two pitvipers, allopatrically separated for at least 1.6 million years, and their hybrids. Transcriptomes of parental species had generally similar compositions in regard to protein families, but for a given protein family, the homologs present and concentrations thereof sometimes differed dramatically. For instance, a phospholipase A2 transcript comprising 73.4 % of the Protobothrops elegans transcriptome, was barely present in the P. flavoviridis transcriptome (king cobra genome, suggesting that rapid evolution of abundant proteins may be generally true for snake venoms. Looking more broadly at Protobothrops, we show that rapid evolution of the most abundant components is due to positive selection, suggesting an interplay between abundance and adaptation. Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness. Natural selection then acts on the additive genetic variance of these components, in proportion to their contributions to overall fitness. Adaptive

  4. A model for the emergence of cooperation, interdependence, and structure in evolving networks

    Science.gov (United States)

    Jain, Sanjay; Krishna, Sandeep

    2001-01-01

    Evolution produces complex and structured networks of interacting components in chemical, biological, and social systems. We describe a simple mathematical model for the evolution of an idealized chemical system to study how a network of cooperative molecular species arises and evolves to become more complex and structured. The network is modeled by a directed weighted graph whose positive and negative links represent "catalytic" and "inhibitory" interactions among the molecular species, and which evolves as the least populated species (typically those that go extinct) are replaced by new ones. A small autocatalytic set, appearing by chance, provides the seed for the spontaneous growth of connectivity and cooperation in the graph. A highly structured chemical organization arises inevitably as the autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.

  5. Evolving autonomous learning in cognitive networks.

    Science.gov (United States)

    Sheneman, Leigh; Hintze, Arend

    2017-12-01

    There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

  6. A Markovian model of evolving world input-output network.

    Directory of Open Access Journals (Sweden)

    Vahid Moosavi

    Full Text Available The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

  7. A Markovian model of evolving world input-output network.

    Science.gov (United States)

    Moosavi, Vahid; Isacchini, Giulio

    2017-01-01

    The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

  8. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

    2011-01-01

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  9. Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

    Science.gov (United States)

    Liu, Sijia; Chen, Pin-Yu; Hero, Alfred O.

    2018-04-01

    We consider the problem of accelerating distributed optimization in multi-agent networks by sequentially adding edges. Specifically, we extend the distributed dual averaging (DDA) subgradient algorithm to evolving networks of growing connectivity and analyze the corresponding improvement in convergence rate. It is known that the convergence rate of DDA is influenced by the algebraic connectivity of the underlying network, where better connectivity leads to faster convergence. However, the impact of network topology design on the convergence rate of DDA has not been fully understood. In this paper, we begin by designing network topologies via edge selection and scheduling. For edge selection, we determine the best set of candidate edges that achieves the optimal tradeoff between the growth of network connectivity and the usage of network resources. The dynamics of network evolution is then incurred by edge scheduling. Further, we provide a tractable approach to analyze the improvement in the convergence rate of DDA induced by the growth of network connectivity. Our analysis reveals the connection between network topology design and the convergence rate of DDA, and provides quantitative evaluation of DDA acceleration for distributed optimization that is absent in the existing analysis. Lastly, numerical experiments show that DDA can be significantly accelerated using a sequence of well-designed networks, and our theoretical predictions are well matched to its empirical convergence behavior.

  10. Deploying IPv6 in 3GPP networks evolving mobile broadband from 2G to LTE and beyond

    CERN Document Server

    Korhonen, Jouni; Soininen, Jonne

    2013-01-01

    Deploying IPv6 in 3GPP Networks - Evolving Mobile Broadband from 2G to LTE and Beyond  A practical guide enabling mobile operators to deploy IPv6 with confidence The most widely used cellular mobile broadband network technology is based on the 3GPP standards. The history and background of the 3GPP technology is in the Global Mobile Service (GSM) technology and the work done in European Telecommunications Standards Institute (ETSI). This primary voice service network has evolved to be the dominant mobile Internet access technology. Deploying IPv6 in

  11. Genome-Wide Analysis in Three Fusarium Pathogens Identifies Rapidly Evolving Chromosomes and Genes Associated with Pathogenicity

    Science.gov (United States)

    Sperschneider, Jana; Gardiner, Donald M.; Thatcher, Louise F.; Lyons, Rebecca; Singh, Karam B.; Manners, John M.; Taylor, Jennifer M.

    2015-01-01

    Pathogens and hosts are in an ongoing arms race and genes involved in host–pathogen interactions are likely to undergo diversifying selection. Fusarium plant pathogens have evolved diverse infection strategies, but how they interact with their hosts in the biotrophic infection stage remains puzzling. To address this, we analyzed the genomes of three Fusarium plant pathogens for genes that are under diversifying selection. We found a two-speed genome structure both on the chromosome and gene group level. Diversifying selection acts strongly on the dispensable chromosomes in Fusarium oxysporum f. sp. lycopersici and on distinct core chromosome regions in Fusarium graminearum, all of which have associations with virulence. Members of two gene groups evolve rapidly, namely those that encode proteins with an N-terminal [SG]-P-C-[KR]-P sequence motif and proteins that are conserved predominantly in pathogens. Specifically, 29 F. graminearum genes are rapidly evolving, in planta induced and encode secreted proteins, strongly pointing toward effector function. In summary, diversifying selection in Fusarium is strongly reflected as genomic footprints and can be used to predict a small gene set likely to be involved in host–pathogen interactions for experimental verification. PMID:25994930

  12. China's evolving role in global production networks: Implications for Trump's trade war

    OpenAIRE

    Athukorala, Prema-chandra

    2017-01-01

    This paper examines China's evolving role in global production networks and its implications for assessing the potential impact of the "trade war" declared by President Trump. The analysis, which is based on a systematic disaggregation of trade based on global production sharing into components and final assembly, suggests that the Sino-US trade gap is a structural phenomenon driven by the pivotal role played by China within East Asia cantered production networks. The global competitiveness o...

  13. Rapid molecular evolution across amniotes of the IIS/TOR network.

    Science.gov (United States)

    McGaugh, Suzanne E; Bronikowski, Anne M; Kuo, Chih-Horng; Reding, Dawn M; Addis, Elizabeth A; Flagel, Lex E; Janzen, Fredric J; Schwartz, Tonia S

    2015-06-02

    The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

  14. A fibre based triature interferometer for measuring rapidly evolving, ablatively driven plasma densities

    Science.gov (United States)

    Macdonald, J.; Bland, S. N.; Threadgold, J.

    2015-08-01

    We report on the first use of a fibre interferometer incorporating triature analysis for measuring rapidly evolving plasma densities of ne ˜ 1013/cm3 and above, such as those produced by simple coaxial plasma guns. The resultant system is extremely portable, easy to field in experiments, relatively cheap to produce, and—with the exception of a small open area in which the plasma is sampled—safe in operation as all laser light is enclosed.

  15. Rapidly Evolving Transients in the Dark Energy Survey

    Energy Technology Data Exchange (ETDEWEB)

    Pursiainen, M.; et al.

    2018-03-13

    We present the results of a search for rapidly evolving transients in the Dark Energy Survey Supernova Programme. These events are characterized by fast light curve evolution (rise to peak in $\\lesssim 10$ d and exponential decline in $\\lesssim30$ d after peak). We discovered 72 events, including 37 transients with a spectroscopic redshift from host galaxy spectral features. The 37 events increase the total number of rapid optical transients by more than factor of two. They are found at a wide range of redshifts ($0.05M_\\mathrm{g}>-22.25$). The multiband photometry is well fit by a blackbody up to few weeks after peak. The events appear to be hot ($T\\approx10000-30000$ K) and large ($R\\approx 10^{14}-2\\cdot10^{15}$ cm) at peak, and generally expand and cool in time, though some events show evidence for a receding photosphere with roughly constant temperature. Spectra taken around peak are dominated by a blue featureless continuum consistent with hot, optically thick ejecta. We compare our events with a previously suggested physical scenario involving shock breakout in an optically thick wind surrounding a core-collapse supernova (CCSNe), we conclude that current models for such a scenario might need an additional power source to describe the exponential decline. We find these transients tend to favor star-forming host galaxies, which could be consistent with a core-collapse origin. However, more detailed modeling of the light curves is necessary to determine their physical origin.

  16. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Paul Tonelli

    Full Text Available A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1 the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2 synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT. Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1 in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2 whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  17. Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

    International Nuclear Information System (INIS)

    Zhang Guiqing; Yang Qiuying; Chen Tianlun

    2008-01-01

    Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities

  18. Evolving dynamics of trading behavior based on coordination game in complex networks

    Science.gov (United States)

    Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

    2016-05-01

    This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

  19. The General Evolving Model for Energy Supply-Demand Network with Local-World

    Science.gov (United States)

    Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

    2013-10-01

    In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

  20. Security for Virtual Private Networks

    OpenAIRE

    Magdalena Nicoleta Iacob

    2015-01-01

    Network security must be a permanent concern for every company, given the fact that threats are evolving today more rapidly than in the past. This paper contains a general classification of cryptographic algorithms used in today networks and presents an implementation of virtual private networks using one of the most secure methods - digital certificates authentication.

  1. Mean-field approach to evolving spatial networks, with an application to osteocyte network formation

    Science.gov (United States)

    Taylor-King, Jake P.; Basanta, David; Chapman, S. Jonathan; Porter, Mason A.

    2017-07-01

    We consider evolving networks in which each node can have various associated properties (a state) in addition to those that arise from network structure. For example, each node can have a spatial location and a velocity, or it can have some more abstract internal property that describes something like a social trait. Edges between nodes are created and destroyed, and new nodes enter the system. We introduce a "local state degree distribution" (LSDD) as the degree distribution at a particular point in state space. We then make a mean-field assumption and thereby derive an integro-partial differential equation that is satisfied by the LSDD. We perform numerical experiments and find good agreement between solutions of the integro-differential equation and the LSDD from stochastic simulations of the full model. To illustrate our theory, we apply it to a simple model for osteocyte network formation within bones, with a view to understanding changes that may take place during cancer. Our results suggest that increased rates of differentiation lead to higher densities of osteocytes, but with a smaller number of dendrites. To help provide biological context, we also include an introduction to osteocytes, the formation of osteocyte networks, and the role of osteocytes in bone metastasis.

  2. Cancer immunotherapy: Opportunities and challenges in the rapidly evolving clinical landscape.

    Science.gov (United States)

    Emens, Leisha A; Ascierto, Paolo A; Darcy, Phillip K; Demaria, Sandra; Eggermont, Alexander M M; Redmond, William L; Seliger, Barbara; Marincola, Francesco M

    2017-08-01

    Cancer immunotherapy is now established as a powerful way to treat cancer. The recent clinical success of immune checkpoint blockade (antagonists of CTLA-4, PD-1 and PD-L1) highlights both the universal power of treating the immune system across tumour types and the unique features of cancer immunotherapy. Immune-related adverse events, atypical clinical response patterns, durable responses, and clear overall survival benefit distinguish cancer immunotherapy from cytotoxic cancer therapy. Combination immunotherapies that transform non-responders to responders are under rapid development. Current challenges facing the field include incorporating immunotherapy into adjuvant and neoadjuvant cancer therapy, refining dose, schedule and duration of treatment and developing novel surrogate endpoints that accurately capture overall survival benefit early in treatment. As the field rapidly evolves, we must prioritise the development of biomarkers to guide the use of immunotherapies in the most appropriate patients. Immunotherapy is already transforming cancer from a death sentence to a chronic disease for some patients. By making smart, evidence-based decisions in developing next generation immunotherapies, cancer should become an imminently treatable, curable and even preventable disease. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Evolving patterns in a collaboration network of global R&D on monoclonal antibodies.

    Science.gov (United States)

    Kong, Xiangjun; Wan, Jian-Bo; Hu, Hao; Su, Shibing; Hu, Yuanjia

    2017-10-01

    We investigated the evolution process of collaborative inter-organizational network of the research and development (R&D) on monoclonal antibody (mAb) over the past 30 y. The annual detection of the collaboration network provides dynamics on network structures and relationship changes among different organizations. Our research showed continuous growth of the network's scale and complexity due to the constant entry of new organizations and the forging of new partnering relationships. The evolving topological features reveal a core-periphery structure that became clearer over time and an increasing heterogeneity within the collaborative mAb R&D network. As measured by the number of network participants, dedicated biotechnology firms (DBFs) were the dominant organization form in the field of mAb development, but their average centrality was reduced during the period of 2004-2009, when pharmaceutical companies took over the positions of DBFs. Along with the network evolution, 2 waves of substitution on the leading positions were driven by technological innovations and mergers and acquisitions (M&A). In addition, this study analyzed organizational-level behaviors to help understand the evolution of network structures over the field of mAb development across the different technologically innovative or economic contexts.

  4. Rapid innovation diffusion in social networks.

    Science.gov (United States)

    Kreindler, Gabriel E; Young, H Peyton

    2014-07-22

    Social and technological innovations often spread through social networks as people respond to what their neighbors are doing. Previous research has identified specific network structures, such as local clustering, that promote rapid diffusion. Here we derive bounds that are independent of network structure and size, such that diffusion is fast whenever the payoff gain from the innovation is sufficiently high and the agents' responses are sufficiently noisy. We also provide a simple method for computing an upper bound on the expected time it takes for the innovation to become established in any finite network. For example, if agents choose log-linear responses to what their neighbors are doing, it takes on average less than 80 revision periods for the innovation to diffuse widely in any network, provided that the error rate is at least 5% and the payoff gain (relative to the status quo) is at least 150%. Qualitatively similar results hold for other smoothed best-response functions and populations that experience heterogeneous payoff shocks.

  5. Intrinsic immunogenicity of rapidly-degradable polymers evolves during degradation.

    Science.gov (United States)

    Andorko, James I; Hess, Krystina L; Pineault, Kevin G; Jewell, Christopher M

    2016-03-01

    Recent studies reveal many biomaterial vaccine carriers are able to activate immunostimulatory pathways, even in the absence of other immune signals. How the changing properties of polymers during biodegradation impact this intrinsic immunogenicity is not well studied, yet this information could contribute to rational design of degradable vaccine carriers that help direct immune response. We use degradable poly(beta-amino esters) (PBAEs) to explore intrinsic immunogenicity as a function of the degree of polymer degradation and polymer form (e.g., soluble, particles). PBAE particles condensed by electrostatic interaction to mimic a common vaccine approach strongly activate dendritic cells, drive antigen presentation, and enhance T cell proliferation in the presence of antigen. Polymer molecular weight strongly influences these effects, with maximum stimulation at short degradation times--corresponding to high molecular weight--and waning levels as degradation continues. In contrast, free polymer is immunologically inert. In mice, PBAE particles increase the numbers and activation state of cells in lymph nodes. Mechanistic studies reveal that this evolving immunogenicity occurs as the physicochemical properties and concentration of particles change during polymer degradation. This work confirms the immunological profile of degradable, synthetic polymers can evolve over time and creates an opportunity to leverage this feature in new vaccines. Degradable polymers are increasingly important in vaccination, but how the inherent immunogenicity of polymers changes during degradation is poorly understood. Using common rapidly-degradable vaccine carriers, we show that the activation of immune cells--even in the absence of other adjuvants--depends on polymer form (e.g., free, particulate) and the extent of degradation. These changing characteristics alter the physicochemical properties (e.g., charge, size, molecular weight) of polymer particles, driving changes in

  6. Optimum Combining for Rapidly Fading Channels in Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Sonia Furman

    2003-10-01

    Full Text Available Research and technology in wireless communication systems such as radar and cellular networks have successfully implemented alternative design approaches that utilize antenna array techniques such as optimum combining, to mitigate the degradation effects of multipath in rapid fading channels. In ad hoc networks, these methods have not yet been exploited primarily due to the complexity inherent in the network's architecture. With the high demand for improved signal link quality, devices configured with omnidirectional antennas can no longer meet the growing need for link quality and spectrum efficiency. This study takes an empirical approach to determine an optimum combining antenna array based on 3 variants of interelement spacing. For rapid fading channels, the simulation results show that the performance in the network of devices retrofitted with our antenna arrays consistently exceeded those with an omnidirectional antenna. Further, with the optimum combiner, the performance increased by over 60% compared to that of an omnidirectional antenna in a rapid fading channel.

  7. Analyzing Evolving Social Network 2 (EVOLVE2)

    Science.gov (United States)

    2015-04-01

    WORK UNIT NUMBER N2 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of Southern California 3720 S. Flower Street, Third Floor Los...score, and resource allocation. Below the double line are link prediction heuristics introduced in this paper. name symbol definition common neighbors...LIST OF SYMBOLS , ABBREVIATIONS AND ACRONYMS A adjacency matrix of a network D diagonal out-degree matrix DW out-degree matrix of the reweighted network

  8. Evolving Spiking Neural Networks for Recognition of Aged Voices.

    Science.gov (United States)

    Silva, Marco; Vellasco, Marley M B R; Cataldo, Edson

    2017-01-01

    The aging of the voice, known as presbyphonia, is a natural process that can cause great change in vocal quality of the individual. This is a relevant problem to those people who use their voices professionally, and its early identification can help determine a suitable treatment to avoid its progress or even to eliminate the problem. This work focuses on the development of a new model for the identification of aging voices (independently of their chronological age), using as input attributes parameters extracted from the voice and glottal signals. The proposed model, named Quantum binary-real evolving Spiking Neural Network (QbrSNN), is based on spiking neural networks (SNNs), with an unsupervised training algorithm, and a Quantum-Inspired Evolutionary Algorithm that automatically determines the most relevant attributes and the optimal parameters that configure the SNN. The QbrSNN model was evaluated in a database composed of 120 records, containing samples from three groups of speakers. The results obtained indicate that the proposed model provides better accuracy than other approaches, with fewer input attributes. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  9. Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

    Science.gov (United States)

    Partha, Raghavendran; Raman, Karthik

    2014-01-01

    Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to

  10. Coevolution within a transcriptional network by compensatory trans and cis mutations

    KAUST Repository

    Kuo, D.; Licon, K.; Bandyopadhyay, S.; Chuang, R.; Luo, C.; Catalana, J.; Ravasi, Timothy; Tan, K.; Ideker, T.

    2010-01-01

    Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA

  11. Spatiotemporal reconstruction of the Aquilegia rapid radiation through next-generation sequencing of rapidly evolving cpDNA regions.

    Science.gov (United States)

    Fior, Simone; Li, Mingai; Oxelman, Bengt; Viola, Roberto; Hodges, Scott A; Ometto, Lino; Varotto, Claudio

    2013-04-01

    Aquilegia is a well-known model system in the field of evolutionary biology, but obtaining a resolved and well-supported phylogenetic reconstruction for the genus has been hindered by its recent and rapid diversification. Here, we applied 454 next-generation sequencing to PCR amplicons of 21 of the most rapidly evolving regions of the plastome to generate c. 24 kb of sequences from each of 84 individuals from throughout the genus. The resulting phylogeny has well-supported resolution of the main lineages of the genus, although recent diversification such as in the European taxa remains unresolved. By producing a chronogram of the whole Ranunculaceae family based on published data, we inferred calibration points for dating the Aquilegia radiation. The genus originated in the upper Miocene c. 6.9 million yr ago (Ma) in Eastern Asia, and diversification occurred c. 4.8 Ma with the split of two main clades, one colonizing North America, and the other Western Eurasia through the mountains of Central Asia. This was followed by a back-to-Asia migration, originating from the European stock using a North Asian route. These results provide the first backbone phylogeny and spatiotemporal reconstruction of the Aquilegia radiation, and constitute a robust framework to address the adaptative nature of speciation within the group. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  12. Evolving production network structures

    DEFF Research Database (Denmark)

    Grunow, Martin; Gunther, H.O.; Burdenik, H.

    2007-01-01

    When deciding about future production network configurations, the current structures have to be taken into account. Further, core issues such as the maturity of the products and the capacity requirements for test runs and ramp-ups must be incorporated. Our approach is based on optimization...... modelling and assigns products and capacity expansions to production sites under the above constraints. It also considers the production complexity at the individual sites and the flexibility of the network. Our implementation results for a large manufacturing network reveal substantial possible cost...

  13. Emergence of epidemics in rapidly varying networks

    International Nuclear Information System (INIS)

    Kohar, Vivek; Sinha, Sudeshna

    2013-01-01

    We describe a simple model mimicking disease spreading on a network with dynamically varying connections, and investigate the dynamical consequences of switching links in the network. Our central observation is that the disease cycles get more synchronized, indicating the onset of epidemics, as the underlying network changes more rapidly. This behavior is found for periodically switched links, as well as links that switch randomly in time. We find that the influence of changing links is more pronounced in networks where the nodes have lower degree, and the disease cycle has a longer infective stage. Further, when the switching of links is periodic we observe finer dynamical features, such as beating patterns in the emergent oscillations and resonant enhancement of synchronization, arising from the interplay between the time-scales of the connectivity changes and that of the epidemic outbreaks

  14. Connecting Network Properties of Rapidly Disseminating Epizoonotics

    Science.gov (United States)

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

    2012-01-01

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

  15. The effect of aging on network structure

    OpenAIRE

    Zhu, Han; Wang, Xin-Ran; Zhu, Jian-Yang

    2003-01-01

    In network evolution, the effect of aging is universal: in scientific collaboration network, scientists have a finite time span of being active; in movie actors network, once popular stars are retiring from stage; devices on the Internet may become outmoded with techniques developing so rapidly. Here we find in citation networks that this effect can be represented by an exponential decay factor, $e^{-\\beta \\tau}$, where $\\tau $ is the node age, while other evolving networks (the Internet for ...

  16. Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators

    Science.gov (United States)

    Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V. E.; Stefanovska, Aneta

    2012-12-01

    Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.109.024101 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

  17. Ecological connectivity networks in rapidly expanding cities.

    Science.gov (United States)

    Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

    2017-06-01

    Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for

  18. Ecological connectivity networks in rapidly expanding cities

    Directory of Open Access Journals (Sweden)

    Amal Najihah M. Nor

    2017-06-01

    Full Text Available Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow (Passer montanus and Yellow-vented bulbul (Pycnonotus goiavier in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines. The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such

  19. EVOLVE 2014 International Conference

    CERN Document Server

    Tantar, Emilia; Sun, Jian-Qiao; Zhang, Wei; Ding, Qian; Schütze, Oliver; Emmerich, Michael; Legrand, Pierrick; Moral, Pierre; Coello, Carlos

    2014-01-01

    This volume encloses research articles that were presented at the EVOLVE 2014 International Conference in Beijing, China, July 1–4, 2014.The book gathers contributions that emerged from the conference tracks, ranging from probability to set oriented numerics and evolutionary computation; all complemented by the bridging purpose of the conference, e.g. Complex Networks and Landscape Analysis, or by the more application oriented perspective. The novelty of the volume, when considering the EVOLVE series, comes from targeting also the practitioner’s view. This is supported by the Machine Learning Applied to Networks and Practical Aspects of Evolutionary Algorithms tracks, providing surveys on new application areas, as in the networking area and useful insights in the development of evolutionary techniques, from a practitioner’s perspective. Complementary to these directions, the conference tracks supporting the volume, follow on the individual advancements of the subareas constituting the scope of the confe...

  20. Satcom access in the Evolved Packet Core

    NARCIS (Netherlands)

    Cano Soveri, M.D.; Norp, A.H.J.; Popova, M.P.

    2011-01-01

    Satellite communications (Satcom) networks are increasingly integrating with terrestrial communications networks, namely Next Generation Networks (NGN). In the area of NGN the Evolved Packet Core (EPC) is a new network architecture that can support multiple access technologies. When Satcom is

  1. Satcom access in the evolved packet core

    NARCIS (Netherlands)

    Cano, M.D.; Norp, A.H.J.; Popova, M.P.

    2012-01-01

    Satellite communications (Satcom) networks are increasingly integrating with terrestrial communications networks, namely Next Generation Networks (NGN). In the area of NGN the Evolved Packet Core (EPC) is a new network architecture that can support multiple access technologies. When Satcom is

  2. Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition.

    Science.gov (United States)

    Valt, Christian; Klein, Christoph; Boehm, Stephan G

    2015-08-01

    Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming. © 2014 The British Psychological Society.

  3. Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

    Science.gov (United States)

    Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

    2017-01-01

    The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

  4. Patient with rapidly evolving neurological disease with neuropathological lesions of Creutzfeldt-Jakob disease, Lewy body dementia, chronic subcortical vascular encephalopathy and meningothelial meningioma.

    Science.gov (United States)

    Vita, Maria Gabriella; Tiple, Dorina; Bizzarro, Alessandra; Ladogana, Anna; Colaizzo, Elisa; Capellari, Sabina; Rossi, Marcello; Parchi, Piero; Masullo, Carlo; Pocchiari, Maurizio

    2017-04-01

    We report a case of rapidly evolving neurological disease in a patient with neuropathological lesions of Creutzfeldt-Jakob disease (CJD), Lewy body dementia (LBD), chronic subcortical vascular encephalopathy and meningothelial meningioma. The coexistence of severe multiple pathologies in a single patient strengthens the need to perform accurate clinical differential diagnoses in rapidly progressive dementias. © 2016 Japanese Society of Neuropathology.

  5. An evolving model for the lodging-service network in a tourism destination

    Science.gov (United States)

    Hernández, Juan M.; González-Martel, Christian

    2017-09-01

    Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing model that explains how part of the supply components in a tourism system forms a social network. Specifically, the lodgings and services in a destination are the network nodes and a link between them appears if a representative tourist hosted in the lodging visits/consumes the service during his/her stay. The specific link between both categories are determined by a random and preferential attachment rule. The analytic results show that the long-term degree distribution of services follows a shifted power-law distribution. The numerical simulations show slight disagreements with the theoretical results in the case of the one-mode degree distribution of services, due to the low order of convergence to zero of X-motifs. The model predictions are compared with real data coming from a popular tourist destination in Gran Canaria, Spain, showing a good agreement between analytical and empirical data for the degree distribution of services. The theoretical model was validated assuming four type of perturbations in the real data.

  6. Managing Evolving Global Operations Networks

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Johansen, John

    2015-01-01

    For many globally dispersed organisations, the home base (HB) is a historic locus of integrative and coordinating efforts that safeguard overall performance. However, the dynamism of global operations networks is increasingly pulling the centre of gravity away from the HB and dispersing it across...... the network, challenging the HB’s ability to sustain its centrality over time. To counteract this tendency, this paper addresses the gap in the literature regarding the development of the network management capability of the HB within the context of its network. Data was collected through a retrospective...... longitudinal case study of an intra-organisational operations network of one OEM and its three foreign subsidiaries. The findings suggest a row of strategic roles and corresponding managerial capabilities, which the HB needs to develop depending on the changing subsidiaries’ competencies and HB...

  7. canEvolve: a web portal for integrative oncogenomics.

    Directory of Open Access Journals (Sweden)

    Mehmet Kemal Samur

    Full Text Available BACKGROUND & OBJECTIVE: Genome-wide profiles of tumors obtained using functional genomics platforms are being deposited to the public repositories at an astronomical scale, as a result of focused efforts by individual laboratories and large projects such as the Cancer Genome Atlas (TCGA and the International Cancer Genome Consortium. Consequently, there is an urgent need for reliable tools that integrate and interpret these data in light of current knowledge and disseminate results to biomedical researchers in a user-friendly manner. We have built the canEvolve web portal to meet this need. RESULTS: canEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. canEvolve provides results of integrative analysis of gene expression profiles with copy number alterations and with miRNA profiles as well as generalized integrative analysis using gene set enrichment analysis. The network analysis capability includes storage and visualization of gene co-expression, inferred gene regulatory networks and protein-protein interaction information. Finally, canEvolve provides correlations between gene expression and clinical outcomes in terms of univariate survival analysis. CONCLUSION: At present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network

  8. Laplacian Estrada and normalized Laplacian Estrada indices of evolving graphs.

    Science.gov (United States)

    Shang, Yilun

    2015-01-01

    Large-scale time-evolving networks have been generated by many natural and technological applications, posing challenges for computation and modeling. Thus, it is of theoretical and practical significance to probe mathematical tools tailored for evolving networks. In this paper, on top of the dynamic Estrada index, we study the dynamic Laplacian Estrada index and the dynamic normalized Laplacian Estrada index of evolving graphs. Using linear algebra techniques, we established general upper and lower bounds for these graph-spectrum-based invariants through a couple of intuitive graph-theoretic measures, including the number of vertices or edges. Synthetic random evolving small-world networks are employed to show the relevance of the proposed dynamic Estrada indices. It is found that neither the static snapshot graphs nor the aggregated graph can approximate the evolving graph itself, indicating the fundamental difference between the static and dynamic Estrada indices.

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

    Science.gov (United States)

    Pesavento, Michael J; Pinto, David J

    2012-11-01

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

  10. Laplacian Estrada and normalized Laplacian Estrada indices of evolving graphs.

    Directory of Open Access Journals (Sweden)

    Yilun Shang

    Full Text Available Large-scale time-evolving networks have been generated by many natural and technological applications, posing challenges for computation and modeling. Thus, it is of theoretical and practical significance to probe mathematical tools tailored for evolving networks. In this paper, on top of the dynamic Estrada index, we study the dynamic Laplacian Estrada index and the dynamic normalized Laplacian Estrada index of evolving graphs. Using linear algebra techniques, we established general upper and lower bounds for these graph-spectrum-based invariants through a couple of intuitive graph-theoretic measures, including the number of vertices or edges. Synthetic random evolving small-world networks are employed to show the relevance of the proposed dynamic Estrada indices. It is found that neither the static snapshot graphs nor the aggregated graph can approximate the evolving graph itself, indicating the fundamental difference between the static and dynamic Estrada indices.

  11. Homophyly/Kinship Model: Naturally Evolving Networks

    Science.gov (United States)

    Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

    2015-10-01

    It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

  12. Evolving the NCSA CyberCollaboratory for Distributed Environmental Observatory Networks

    Science.gov (United States)

    Myers, J.; Liu, Y.; Minsker, B.; Futrelle, J.; Downey, S.; Kim, I.; Rantanen, E.

    2007-12-01

    Since 2004, NCSA's Cybercollaboratory, which is built on top of the open source Liferay portal framework, has been evolving as part of NCSA's efforts to build national cyberinfrastructure to support collaborative research in environmental engineering and hydrological sciences and allow users to efficiently share contents (sensors, data, model, documents, etc.) in a context-sensitive way (e.g., providing different tools/data based on group affiliation and geospatial contexts). During this period, we provided the CyberCollaboratory to users in CLEANER (Collaborative Large-scale Engineering Analysis Network for Environmental Research, now WATer and Environmental Research Systems (WATERS) network) Project Office and several CLEANER /WATERS testbed projects. Preliminary statistics shows that one in four users (among over 400 registered users) provided contents with many other reading/accessing those contents (such as messages, documents, wikis). During the course of this use, and in evaluation by others including representatives from the CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science) community, we have received significant feedback on issues of usability and suitability to various communities involved in environmental observatories. Much of this feedback applies to collaborative portals in general and some reflect a comparison of portals with newer Web 2.0 style social -networking sites. For example, users working in multiple groups found it difficult to get an overview of all of their activities and found differences in group layouts to be confusing. Users also found the standard account creation and group management processes cumbersome compared to inviting people to be friends on social sites and wanted a better sense of presence and social networks within the portal. The fragmentation of group documents between local stores, the portal document repository and email, and issues of "lost updates" was another significant concern. This

  13. Online Social Networking: A Primer for Radiology

    OpenAIRE

    Prasanna, Prasanth M.; Seagull, F. Jacob; Nagy, Paul

    2011-01-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-c...

  14. Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

    Science.gov (United States)

    Kasabov, Nikola; Dhoble, Kshitij; Nuntalid, Nuttapod; Indiveri, Giacomo

    2013-05-01

    On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass rank-order learning mechanism and a strategy to evolve a new spiking neuron and new connections to learn new patterns from incoming data. So far these networks have been mainly used for fast image and speech frame-based recognition. Alternative spike-time learning methods, such as Spike-Timing Dependent Plasticity (STDP) and its variant Spike Driven Synaptic Plasticity (SDSP), can also be used to learn spatio-temporal representations, but they usually require many iterations in an unsupervised or semi-supervised mode of learning. This paper introduces a new class of eSNN, dynamic eSNN, that utilise both rank-order learning and dynamic synapses to learn SSTD in a fast, on-line mode. The paper also introduces a new model called deSNN, that utilises rank-order learning and SDSP spike-time learning in unsupervised, supervised, or semi-supervised modes. The SDSP learning is used to evolve dynamically the network changing connection weights that capture spatio-temporal spike data clusters both during training and during recall. The new deSNN model is first illustrated on simple examples and then applied on two case study applications: (1) moving object recognition using address-event representation (AER) with data collected using a silicon retina device; (2) EEG SSTD recognition for brain-computer interfaces. The deSNN models resulted in a superior performance in terms of accuracy and speed when compared with other SNN models that use either rank-order or STDP learning. The reason is that the deSNN makes use of both the information contained in the order of the first input spikes

  15. Emerging localized food networks in Denmark

    DEFF Research Database (Denmark)

    Hansen, Mette Weinreich; Kristensen, Niels Heine

    2012-01-01

    , together with an analysis of how this has evolved and expanded. The challenges this rapid expansion puts on the internal network and organisation, and on the local food supplieres - the organic farmers - are elaborated in this paper. Also – from a rural sociology perspective – the interaction......One of the fastest growing food related social movements are citizen driven food networks. The Danish initiatives emerged in Copenhagen from an open culinary, social, environmental and organic oriented network. The theories and strategies of the original initiative is presented in this paper...

  16. Adaptive cyclically dominating game on co-evolving networks: numerical and analytic results

    Science.gov (United States)

    Choi, Chi Wun; Xu, Chen; Hui, Pak Ming

    2017-10-01

    A co-evolving and adaptive Rock (R)-Paper (P)-Scissors (S) game (ARPS) in which an agent uses one of three cyclically dominating strategies is proposed and studied numerically and analytically. An agent takes adaptive actions to achieve a neighborhood to his advantage by rewiring a dissatisfying link with a probability p or switching strategy with a probability 1 - p. Numerical results revealed two phases in the steady state. An active phase for p pc has three separate clusters of agents using only R, P, and S, respectively with terminated adaptive actions. A mean-field theory based on the link densities in co-evolving network is formulated and the trinomial closure scheme is applied to obtain analytical solutions. The analytic results agree with simulation results on ARPS well. In addition, the different probabilities of winning, losing, and drawing a game among the agents are identified as the origin of the small discrepancy between analytic and simulation results. As a result of the adaptive actions, agents of higher degrees are often those being taken advantage of. Agents with a smaller (larger) degree than the mean degree have a higher (smaller) probability of winning than losing. The results are informative for future attempts on formulating more accurate theories.

  17. Network motif frequency vectors reveal evolving metabolic network organisation.

    Science.gov (United States)

    Pearcy, Nicole; Crofts, Jonathan J; Chuzhanova, Nadia

    2015-01-01

    At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

  18. Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

    Science.gov (United States)

    Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

    2016-01-01

    Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for

  19. Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

    Directory of Open Access Journals (Sweden)

    Arno Steinacher

    Full Text Available Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest

  20. Clique size and network characteristics in hyperlink cinema. Constraints of evolved psychology.

    Science.gov (United States)

    Krems, Jaimie Arona; Dunbar, R I M

    2013-12-01

    Hyperlink cinema is an emergent film genre that seeks to push the boundaries of the medium in order to mirror contemporary life in the globalized community. Films in the genre thus create an interacting network across space and time in such a way as to suggest that people's lives can intersect on scales that would not have been possible without modern technologies of travel and communication. This allows us to test the hypothesis that new kinds of media might permit us to break through the natural cognitive constraints that limit the number and quality of social relationships we can manage in the conventional face-to-face world. We used network analysis to test this hypothesis with data from 12 hyperlink films, using 10 motion pictures from a more conventional film genre as a control. We found few differences between hyperlink cinema films and the control genre, and few differences between hyperlink cinema films and either the real world or classical drama (e.g., Shakespeare's plays). Conversation group size seems to be especially resilient to alteration. It seems that, despite many efficiency advantages, modern media are unable to circumvent the constraints imposed by our evolved psychology.

  1. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  2. A rapid reliability estimation method for directed acyclic lifeline networks with statistically dependent components

    International Nuclear Information System (INIS)

    Kang, Won-Hee; Kliese, Alyce

    2014-01-01

    Lifeline networks, such as transportation, water supply, sewers, telecommunications, and electrical and gas networks, are essential elements for the economic and societal functions of urban areas, but their components are highly susceptible to natural or man-made hazards. In this context, it is essential to provide effective pre-disaster hazard mitigation strategies and prompt post-disaster risk management efforts based on rapid system reliability assessment. This paper proposes a rapid reliability estimation method for node-pair connectivity analysis of lifeline networks especially when the network components are statistically correlated. Recursive procedures are proposed to compound all network nodes until they become a single super node representing the connectivity between the origin and destination nodes. The proposed method is applied to numerical network examples and benchmark interconnected power and water networks in Memphis, Shelby County. The connectivity analysis results show the proposed method's reasonable accuracy and remarkable efficiency as compared to the Monte Carlo simulations

  3. Three perspectives on the evolving electric vehicles innovation network of Finland

    Energy Technology Data Exchange (ETDEWEB)

    Rasanen, R.-S.; Temmes, A.; Lovio, R.

    2013-06-01

    This report compiles the electric vehicle related work done in 2012 in the project: Future innovation and technology policy for sustainable system-level transitions: the case of transport (FIP-Trans). The project focuses on researching alternative and complementary socio-technical pathways and related policy options for sustainable transition in the Finnish transport sector. The project is financed by Tekes - the Finnish Funding Agency for Technology and Innovation. Analysis is continued in 2013. In this paper we study the evolving electric vehicle innovation network of Finland. The analysis is built on combining the theoretical aspects of Strategic Niche Management and Technology Innovation Systems. Based on the literature we develop a framework for analyzing the development of innovation networks. The framework contains four steps. The first step is the identification and analysis of the main actors and their activities. The second step is the identification and analysis of the main events affecting the development of the industry. This step is based on the use of event structure analysis. The third step consists of the analysis of development of the architecture of the system while the fourth step deals with the description and analysis of the niche and innovation system development processes in a combined manner. The data consists of interviews, policy and consultation papers, newspaper articles, press releases and other enterprise publications and of private databases containing financial information of the enterprises. Based on the theoretical framework, the four separate, but complementing qualitative analyses were made. The electric vehicle niche has evolved through the interaction of private and public sector actors. The involvement of public sector affected strongly on the evolution of the system arenas and was an important event for the resource mobilization of the industry. As with other Finnish industries, the importance of the international dimension

  4. The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

    Directory of Open Access Journals (Sweden)

    David A Garfield

    2013-10-01

    Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

  5. A rapid protection switching method in carrier ethernet ring networks

    Science.gov (United States)

    Yuan, Liang; Ji, Meng

    2008-11-01

    Abstract: Ethernet is the most important Local Area Network (LAN) technology since more than 90% data traffic in access layer is carried on Ethernet. From 10M to 10G, the improving Ethernet technology can be not only used in LAN, but also a good choice for MAN even WAN. MAN are always constructed in ring topology because the ring network could provide resilient path protection by using less resource (fibre or cable) than other network topologies. In layer 2 data networks, spanning tree protocol (STP) is always used to protect transmit link and preventing the formation of logic loop in networks. However, STP cannot guarantee the efficiency of service convergence when link fault happened. In fact, convergent time of networks with STP is about several minutes. Though Rapid Spanning Tree Protocol (RSTP) and Multi-Spanning Tree Protocol (MSTP) improve the STP technology, they still need a couple of seconds to achieve convergence, and can not provide sub-50ms protection switching. This paper presents a novel rapid ring protection method (RRPM) for carrier Ethernet. Unlike other link-fault detection method, it adopts distributed algorithm to detect link fault rapidly (sub-50ms). When networks restore from link fault, it can revert to the original working state. RRPM can provide single ring protection and interconnected ring protection without the formation of super loop. In normal operation, the master node blocks the secondary port for all non-RRPM Ethernet frames belonging to the given RRPM Ring, thereby avoiding a loop in the ring. When link fault happens, the node on which the failure happens moves from the "ring normal" state to the "ring fault" state. It also sends "link down" frame immediately to other nodes and blocks broken port and flushes its forwarding database. Those who receive "link down" frame will flush forwarding database and master node should unblock its secondary port. When the failure restores, the whole ring will revert to the normal state. That is

  6. Slowly evolving connectivity in recurrent neural networks: I. The extreme dilution regime

    International Nuclear Information System (INIS)

    Wemmenhove, B; Skantzos, N S; Coolen, A C C

    2004-01-01

    We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the 'condensed' pattern are locally stable, so the associative memory character of our model is preserved

  7. Identification of dual-tropic HIV-1 using evolved neural networks.

    Science.gov (United States)

    Fogel, Gary B; Lamers, Susanna L; Liu, Enoch S; Salemi, Marco; McGrath, Michael S

    2015-11-01

    Blocking the binding of the envelope HIV-1 protein to immune cells is a popular concept for development of anti-HIV therapeutics. R5 HIV-1 binds CCR5, X4 HIV-1 binds CXCR4, and dual-tropic HIV-1 can bind either coreceptor for cellular entry. R5 viruses are associated with early infection and over time can evolve to X4 viruses that are associated with immune failure. Dual-tropic HIV-1 is less studied; however, it represents functional antigenic intermediates during the transition of R5 to X4 viruses. Viral tropism is linked partly to the HIV-1 envelope V3 domain, where the amino acid sequence helps dictate the receptor a particular virus will target; however, using V3 sequence information to identify dual-tropic HIV-1 isolates has remained difficult. Our goal in this study was to elucidate features of dual-tropic HIV-1 isolates that assist in the biological understanding of dual-tropism and develop an approach for their detection. Over 1559 HIV-1 subtype B sequences with known tropisms were analyzed. Each sequence was represented by 73 structural, biochemical and regional features. These features were provided to an evolved neural network classifier and evaluated using balanced and unbalanced data sets. The study resolved R5X4 viruses from R5 with an accuracy of 81.8% and from X4 with an accuracy of 78.8%. The approach also identified a set of V3 features (hydrophobicity, structural and polarity) that are associated with tropism transitions. The ability to distinguish R5X4 isolates will improve computational tropism decisions for R5 vs. X4 and assist in HIV-1 research and drug development efforts. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. Fast mapping rapidly integrates information into existing memory networks.

    Science.gov (United States)

    Coutanche, Marc N; Thompson-Schill, Sharon L

    2014-12-01

    Successful learning involves integrating new material into existing memory networks. A learning procedure known as fast mapping (FM), thought to simulate the word-learning environment of children, has recently been linked to distinct neuroanatomical substrates in adults. This idea has suggested the (never-before tested) hypothesis that FM may promote rapid incorporation into cortical memory networks. We test this hypothesis here in 2 experiments. In our 1st experiment, we introduced 50 participants to 16 unfamiliar animals and names through FM or explicit encoding (EE) and tested participants on the training day, and again after sleep. Learning through EE produced strong declarative memories, without immediate lexical competition, as expected from slow-consolidation models. Learning through FM, however, led to almost immediate lexical competition, which continued to the next day. Additionally, the learned words began to prime related concepts on the day following FM (but not EE) training. In a 2nd experiment, we replicated the lexical integration results and determined that presenting an already-known item during learning was crucial for rapid integration through FM. The findings presented here indicate that learned items can be integrated into cortical memory networks at an accelerated rate through fast mapping. The retrieval of a related known concept, in order to infer the target of the FM question, is critical for this effect. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  9. Supply Networks and Value Creation in High Innovation and Strong Network Externalities Industry

    Directory of Open Access Journals (Sweden)

    Fernando Claro Tomaselli

    2013-12-01

    Full Text Available The rapid developing product and service markets and developments in information technologies have accelerated growth in outsourcing of peripheral activities and critical business as well, enhancing the importance of network supply chain management. This paper analyzes the dynamics of supply chain management and the creation of value in an industry with strong network effects and constantly introduction of disruptive technologies, the videogame industry. This industry evolves at a high velocity, with a lifecycle of five to six years for consoles, which features a new generation of consoles, where new companies and technologies appear and disappear at each generation.

  10. Identification and prediction of dynamic systems using an interactively recurrent self-evolving fuzzy neural network.

    Science.gov (United States)

    Lin, Yang-Yin; Chang, Jyh-Yeong; Lin, Chin-Teng

    2013-02-01

    This paper presents a novel recurrent fuzzy neural network, called an interactively recurrent self-evolving fuzzy neural network (IRSFNN), for prediction and identification of dynamic systems. The recurrent structure in an IRSFNN is formed as an external loops and internal feedback by feeding the rule firing strength of each rule to others rules and itself. The consequent part in the IRSFNN is composed of a Takagi-Sugeno-Kang (TSK) or functional-link-based type. The proposed IRSFNN employs a functional link neural network (FLNN) to the consequent part of fuzzy rules for promoting the mapping ability. Unlike a TSK-type fuzzy neural network, the FLNN in the consequent part is a nonlinear function of input variables. An IRSFNNs learning starts with an empty rule base and all of the rules are generated and learned online through a simultaneous structure and parameter learning. An on-line clustering algorithm is effective in generating fuzzy rules. The consequent update parameters are derived by a variable-dimensional Kalman filter algorithm. The premise and recurrent parameters are learned through a gradient descent algorithm. We test the IRSFNN for the prediction and identification of dynamic plants and compare it to other well-known recurrent FNNs. The proposed model obtains enhanced performance results.

  11. Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks

    International Nuclear Information System (INIS)

    Amanifard, N.; Nariman-Zadeh, N.; Farahani, M.H.; Khalkhali, A.

    2008-01-01

    Over the past 15 years there have been several research efforts to capture the stall inception nature in axial flow compressors. However previous analytical models could not explain the formation of short-length-scale stall cells. This paper provides a new model based on evolved GMDH neural network for transient evolution of multiple short-length-scale stall cells in an axial compressor. Genetic Algorithms (GAs) are also employed for optimal design of connectivity configuration of such GMDH-type neural networks. In this way, low-pass filter (LPF) pressure trace near the rotor leading edge is modelled with respect to the variation of pressure coefficient, flow rate coefficient, and number of rotor rotations which are defined as inputs

  12. Rapid divergence and convergence of life-history in experimentally evolved Drosophila melanogaster.

    Science.gov (United States)

    Burke, Molly K; Barter, Thomas T; Cabral, Larry G; Kezos, James N; Phillips, Mark A; Rutledge, Grant A; Phung, Kevin H; Chen, Richard H; Nguyen, Huy D; Mueller, Laurence D; Rose, Michael R

    2016-09-01

    Laboratory selection experiments are alluring in their simplicity, power, and ability to inform us about how evolution works. A longstanding challenge facing evolution experiments with metazoans is that significant generational turnover takes a long time. In this work, we present data from a unique system of experimentally evolved laboratory populations of Drosophila melanogaster that have experienced three distinct life-history selection regimes. The goal of our study was to determine how quickly populations of a certain selection regime diverge phenotypically from their ancestors, and how quickly they converge with independently derived populations that share a selection regime. Our results indicate that phenotypic divergence from an ancestral population occurs rapidly, within dozens of generations, regardless of that population's evolutionary history. Similarly, populations sharing a selection treatment converge on common phenotypes in this same time frame, regardless of selection pressures those populations may have experienced in the past. These patterns of convergence and divergence emerged much faster than expected, suggesting that intermediate evolutionary history has transient effects in this system. The results we draw from this system are applicable to other experimental evolution projects, and suggest that many relevant questions can be sufficiently tested on shorter timescales than previously thought. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

  13. UMTS rapid response real-time seismic networks: implementation and strategies at INGV

    Science.gov (United States)

    Govoni, Aladino; Margheriti, Lucia; Moretti, Milena; Lauciani, Valentino; Sensale, Gianpaolo; Bucci, Augusto; Criscuoli, Fabio

    2015-04-01

    The benefits of portable real-time seismic networks are several and well known. During the management of a temporary experiment from the real-time data it is possible to detect and fix rapidly problems with power supply, time synchronization, disk failures and, most important, seismic signal quality degradation due to unexpected noise sources or sensor alignment/tampering. This usually minimizes field maintenance trips and maximizes both the quantity and the quality of the acquired data. When the area of the temporary experiment is not well monitored by the local permanent network, the real-time data from the temporary experiment can be fed to the permanent network monitoring system improving greatly both the real-time hypocentral locations and the final revised bulletin. All these benefits apply also in case of seismic crises when rapid deployment stations can significantly contribute to the aftershock analysis. Nowadays data transmission using meshed radio networks or satellite systems is not a big technological problem for a permanent seismic network where each site is optimized for the device power consumption and is usually installed by properly specialized technicians that can configure transmission devices and align antennas. This is not usually practical for temporary networks and especially for rapid response networks where the installation time is the main concern. These difficulties are substantially lowered using the now widespread UMTS technology for data transmission. A small (but sometimes power hungry) properly configured device with an omnidirectional antenna must be added to the station assembly. All setups are usually configured before deployment and this allows for an easy installation also by untrained personnel. We describe here the implementation of a UMTS based portable seismic network for both temporary experiments and rapid response applications developed at INGV. The first field experimentation of this approach dates back to the 2009 L

  14. Towards resolving Lamiales relationships: insights from rapidly evolving chloroplast sequences

    Directory of Open Access Journals (Sweden)

    Heubl Günther

    2010-11-01

    Full Text Available Abstract Background In the large angiosperm order Lamiales, a diverse array of highly specialized life strategies such as carnivory, parasitism, epiphytism, and desiccation tolerance occur, and some lineages possess drastically accelerated DNA substitutional rates or miniaturized genomes. However, understanding the evolution of these phenomena in the order, and clarifying borders of and relationships among lamialean families, has been hindered by largely unresolved trees in the past. Results Our analysis of the rapidly evolving trnK/matK, trnL-F and rps16 chloroplast regions enabled us to infer more precise phylogenetic hypotheses for the Lamiales. Relationships among the nine first-branching families in the Lamiales tree are now resolved with very strong support. Subsequent to Plocospermataceae, a clade consisting of Carlemanniaceae plus Oleaceae branches, followed by Tetrachondraceae and a newly inferred clade composed of Gesneriaceae plus Calceolariaceae, which is also supported by morphological characters. Plantaginaceae (incl. Gratioleae and Scrophulariaceae are well separated in the backbone grade; Lamiaceae and Verbenaceae appear in distant clades, while the recently described Linderniaceae are confirmed to be monophyletic and in an isolated position. Conclusions Confidence about deep nodes of the Lamiales tree is an important step towards understanding the evolutionary diversification of a major clade of flowering plants. The degree of resolution obtained here now provides a first opportunity to discuss the evolution of morphological and biochemical traits in Lamiales. The multiple independent evolution of the carnivorous syndrome, once in Lentibulariaceae and a second time in Byblidaceae, is strongly supported by all analyses and topological tests. The evolution of selected morphological characters such as flower symmetry is discussed. The addition of further sequence data from introns and spacers holds promise to eventually obtain a

  15. Towards resolving Lamiales relationships: insights from rapidly evolving chloroplast sequences

    Science.gov (United States)

    2010-01-01

    Background In the large angiosperm order Lamiales, a diverse array of highly specialized life strategies such as carnivory, parasitism, epiphytism, and desiccation tolerance occur, and some lineages possess drastically accelerated DNA substitutional rates or miniaturized genomes. However, understanding the evolution of these phenomena in the order, and clarifying borders of and relationships among lamialean families, has been hindered by largely unresolved trees in the past. Results Our analysis of the rapidly evolving trnK/matK, trnL-F and rps16 chloroplast regions enabled us to infer more precise phylogenetic hypotheses for the Lamiales. Relationships among the nine first-branching families in the Lamiales tree are now resolved with very strong support. Subsequent to Plocospermataceae, a clade consisting of Carlemanniaceae plus Oleaceae branches, followed by Tetrachondraceae and a newly inferred clade composed of Gesneriaceae plus Calceolariaceae, which is also supported by morphological characters. Plantaginaceae (incl. Gratioleae) and Scrophulariaceae are well separated in the backbone grade; Lamiaceae and Verbenaceae appear in distant clades, while the recently described Linderniaceae are confirmed to be monophyletic and in an isolated position. Conclusions Confidence about deep nodes of the Lamiales tree is an important step towards understanding the evolutionary diversification of a major clade of flowering plants. The degree of resolution obtained here now provides a first opportunity to discuss the evolution of morphological and biochemical traits in Lamiales. The multiple independent evolution of the carnivorous syndrome, once in Lentibulariaceae and a second time in Byblidaceae, is strongly supported by all analyses and topological tests. The evolution of selected morphological characters such as flower symmetry is discussed. The addition of further sequence data from introns and spacers holds promise to eventually obtain a fully resolved plastid tree of

  16. HIV-TRACE (Transmission Cluster Engine): a tool for large scale molecular epidemiology of HIV-1 and other rapidly evolving pathogens.

    Science.gov (United States)

    Kosakovsky Pond, Sergei L; Weaver, Steven; Leigh Brown, Andrew J; Wertheim, Joel O

    2018-01-31

    In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoeleather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, i.e., on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from github.com/veg/hivtrace, along with the accompanying result visualization module from github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens. © The Author 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. The apolipoprotein L family of programmed cell death and immunity genes rapidly evolved in primates at discrete sites of host-pathogen interactions.

    Science.gov (United States)

    Smith, Eric E; Malik, Harmit S

    2009-05-01

    Apolipoprotein L1 (APOL1) is a human protein that confers immunity to Trypanosoma brucei infections but can be countered by a trypanosome-encoded antagonist SRA. APOL1 belongs to a family of programmed cell death genes whose proteins can initiate host apoptosis or autophagic death. We report here that all six members of the APOL gene family (APOL1-6) present in humans have rapidly evolved in simian primates. APOL6, furthermore, shows evidence of an adaptive sweep during recent human evolution. In each APOL gene tested, we found rapidly evolving codons in or adjacent to the SRA-interacting protein domain (SID), which is the domain of APOL1 that interacts with SRA. In APOL6, we also found a rapidly changing 13-amino-acid cluster in the membrane-addressing domain (MAD), which putatively functions as a pH sensor and regulator of cell death. We predict that APOL genes are antagonized by pathogens by at least two distinct mechanisms: SID antagonists, which include SRA, that interact with the SID of various APOL proteins, and MAD antagonists that interact with the MAD hinge base of APOL6. These antagonists either block or prematurely cause APOL-mediated programmed cell death of host cells to benefit the infecting pathogen. These putative interactions must occur inside host cells, in contrast to secreted APOL1 that trafficks to the trypanosome lysosome. Hence, the dynamic APOL gene family appears to be an important link between programmed cell death of host cells and immunity to pathogens.

  18. Can multilayer brain networks be a real step forward?. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

    Science.gov (United States)

    Buldú, Javier M.; Papo, David

    2018-03-01

    Over the last two decades Network Science has become one of the most active fields in science, whose growth has been supported by four fundamental pillars: statistical physics, nonlinear dynamics, graph theory and Big Data [1]. Initially concerned with analyzing the structure of networks, Network Science rapidly turned its attention, focused on the implications of network topology, on the dynamics of and processes unfolding on networked systems, greatly improving our understanding of diffusion, synchronization, epidemics and information transmission in complex systems [2]. The network approach typically considered complex systems as evolving in a vacuum; however real networks are generally not isolated systems, but are in continuous and evolving contact with other networks, with which they interact in multiple qualitative different and typically time-varying ways. These systems can then be represented as a collection of subsystems with connectivity layers, which are simply collapsed when considering the traditional monolayer representation. Surprisingly, such an "unpacking" of layers has proven to bear profound consequences on the structural and dynamical properties of networks, leading for instance to counter-intuitive synchronization phenomena, where maximization synchronization is achieved through strategies opposite of those maximizing synchronization in isolated networks [3].

  19. MANAGING GLOBAL OPERATIONS NETWORKS IN MOTION

    DEFF Research Database (Denmark)

    Slepniov, Dmitrij; Jørgensen, Claus; Sørensen, Brian Vejrum

    2008-01-01

    capabilities and intensified need for transfer, assimilation and augmentation of activities and know-how within the network. Based on these the paper highlights some organisational effects and managerial challenges the companies face regarding rapid changes in their networks configurations and capabilities.......Most industrial companies are, for reasons related to cost, market access or knowledge, working with some aspect of offshore operations. This may take form of captive operations or through outsourcing of activities overseas. With this trend, global operations networks are emerging resulting...... in corporate strategic repositioning, re-configurations of sites, and changes to the underlying capabilities. The paper is based on cases of 3 Danish companies and their global supply networks. These networks are not in a steady state, they evolve as a consequence of the ongoing co-evolution between the focal...

  20. Smooth and Controlled Recovery Planning of Disruptions in Rapid Transit Networks

    NARCIS (Netherlands)

    Cadarso, L.; Marin, A.; Maroti, G.

    2015-01-01

    This paper studies the disruption management problem of rapid transit rail networks. We consider an integrated model for the recovery of the timetable and the rolling stock schedules. We propose a new approach to deal with large-scale disruptions: we limit the number of simultaneous schedule changes

  1. Natural selection promotes antigenic evolvability.

    Science.gov (United States)

    Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin

    2013-01-01

    The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.

  2. Natural selection promotes antigenic evolvability.

    Directory of Open Access Journals (Sweden)

    Christopher J Graves

    Full Text Available The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish

  3. WSC-07: Evolving the Web Services Challenge

    NARCIS (Netherlands)

    Blake, M. Brian; Cheung, William K.W.; Jaeger, Michael C.; Wombacher, Andreas

    Service-oriented architecture (SOA) is an evolving architectural paradigm where businesses can expose their capabilities as modular, network-accessible software services. By decomposing capabilities into modular services, organizations can share their offerings at multiple levels of granularity

  4. An Evolving Identity: How Chronic Care Is Transforming What it Means to Be a Physician.

    Science.gov (United States)

    Bogetz, Alyssa L; Bogetz, Jori F

    2015-12-01

    Physician identity and the professional role physicians play in health care is rapidly evolving. Over 130 million adults and children in the USA have complex and chronic diseases, each of which is shaped by aspects of the patient's social, psychological, and economic status. These patients have lifelong health care needs that require the ongoing care of multiple health care providers, access to community services, and the involvement of patients' family support networks. To date, physician professional identity formation has centered on autonomy, authority, and the ability to "heal." These notions of identity may be counterproductive in chronic disease care, which demands interdependency between physicians, their patients, and teams of multidisciplinary health care providers. Medical educators can prepare trainees for practice in the current health care environment by providing training that legitimizes and reinforces a professional identity that emphasizes this interdependency. This commentary outlines the important challenges related to this change and suggests potential strategies to reframe professional identity to better match the evolving role of physicians today.

  5. In-silico studies of neutral drift for functional protein interaction networks

    Science.gov (United States)

    Ali, Md Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    We have developed a minimal physically-motivated model of protein-protein interaction networks. Our system consists of two classes of enzymes, activators (e.g. kinases) and deactivators (e.g. phosphatases), and the enzyme-mediated activation/deactivation rates are determined by sequence-dependent binding strengths between enzymes and their targets. The network is evolved by introducing random point mutations in the binding sequences where we assume that each new mutation is either fixed or entirely lost. We apply this model to studies of neutral drift in networks that yield oscillatory dynamics, where we start, for example, with a relatively simple network and allow it to evolve by adding nodes and connections while requiring that dynamics be conserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. Surprisingly, in addition to this redistribution time we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains.

  6. Rational design of HIV vaccines and microbicides: report of the EUROPRISE network annual conference 2010

    NARCIS (Netherlands)

    Brinckmann, Sarah; Da Costa, Kelly; van Gils, Marit J.; Hallengärd, David; Klein, Katja; Madeira, Luisa; Mainetti, Lara; Palma, Paolo; Raue, Katharina; Reinhart, David; Reudelsterz, Marc; Ruffin, Nicolas; Seifried, Janna; Schäfer, Katrein; Sheik-Khalil, Enas; Sköld, Annette; Uchtenhagen, Hannes; Vabret, Nicolas; Ziglio, Serena; Scarlatti, Gabriella; Shattock, Robin; Wahren, Britta; Gotch, Frances

    2011-01-01

    Novel, exciting intervention strategies to prevent infection with HIV have been tested in the past year, and the field is rapidly evolving. EUROPRISE is a network of excellence sponsored by the European Commission and concerned with a wide range of activities including integrated developmental

  7. Emerging trends in evolving networks: Recent behaviour dominant and non-dominant model

    Science.gov (United States)

    Abbas, Khushnood; Shang, Mingsheng; Luo, Xin; Abbasi, Alireza

    2017-10-01

    Novel phenomenon receives similar attention as popular one. Therefore predicting novelty is as important as popularity. Emergence is the side effect of competition and ageing in evolving systems. Recent behaviour or recent link gain in networks plays an important role in emergence. We exploited this wisdom and came up with two models considering different scenarios and systems. Where recent behaviour dominates over total behaviour (total link gain) in the first one, and recent behaviour is as important as total behaviour for future link gain in the second one. It supposes that random walker walks on a network and can jump to any node, the probability of jumping or making a connection to other node is based on which node is recently more active or receiving more links. In our assumption, the random walker can also jump to the node which is already popular but recently not popular. We are able to predict emerging nodes which are generally suppressed under preferential attachment effect. To show the performance of our model we have conducted experiments on four real data sets namely, MovieLens, Netflix, Facebook and Arxiv High Energy Physics paper citation. For testing our model we used four information retrieval indices namely Precision, Novelty, Area Under Receiving Operating Characteristic (AUC) and Kendal's rank correlation coefficient. We have used four benchmark models for validating our proposed models. Although our model does not perform better in all the cases but, it has theoretical significance in working better for recent behaviour dominated systems.

  8. The network evolves | IDRC - International Development Research ...

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

    2011-07-08

    Jul 8, 2011 ... For the 19 young scholars brought together by the Poverty Research Network, the rewards have been substantial. Lu Ming, who describes his experience with the group as “just fantastic,” likens the network to a bridge – connecting China to Canada, and linking researchers to each other and to scholars ...

  9. Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network.

    Science.gov (United States)

    Liu, Yu-Ting; Lin, Yang-Yin; Wu, Shang-Lin; Chuang, Chun-Hsiang; Lin, Chin-Teng

    2016-02-01

    This paper proposes a generalized prediction system called a recurrent self-evolving fuzzy neural network (RSEFNN) that employs an on-line gradient descent learning rule to address the electroencephalography (EEG) regression problem in brain dynamics for driving fatigue. The cognitive states of drivers significantly affect driving safety; in particular, fatigue driving, or drowsy driving, endangers both the individual and the public. For this reason, the development of brain-computer interfaces (BCIs) that can identify drowsy driving states is a crucial and urgent topic of study. Many EEG-based BCIs have been developed as artificial auxiliary systems for use in various practical applications because of the benefits of measuring EEG signals. In the literature, the efficacy of EEG-based BCIs in recognition tasks has been limited by low resolutions. The system proposed in this paper represents the first attempt to use the recurrent fuzzy neural network (RFNN) architecture to increase adaptability in realistic EEG applications to overcome this bottleneck. This paper further analyzes brain dynamics in a simulated car driving task in a virtual-reality environment. The proposed RSEFNN model is evaluated using the generalized cross-subject approach, and the results indicate that the RSEFNN is superior to competing models regardless of the use of recurrent or nonrecurrent structures.

  10. Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux.

    Science.gov (United States)

    Lee, Jonghwan; Jiang, James Y; Wu, Weicheng; Lesage, Frederic; Boas, David A

    2014-04-01

    We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation.

  11. Inferring Structure and Forecasting Dynamics on Evolving Networks

    Science.gov (United States)

    2016-01-05

    Graphs ........................................................................................................................ 23 7. Sacred Values...5) Team Formation; (6) Games of Graphs; (7) Sacred Values and Legitimacy in Network Interactions; (8) Network processes in Geo-Social Context. 1...Authority, Cooperation and Competition in Religious Networks Key Papers: McBride 2015a [72] and McBride 2015b [73] McBride (2015a) examines

  12. Sex as a strategy against rapidly evolving parasites.

    Science.gov (United States)

    Auld, Stuart K J R; Tinkler, Shona K; Tinsley, Matthew C

    2016-12-28

    Why is sex ubiquitous when asexual reproduction is much less costly? Sex disrupts coadapted gene complexes; it also causes costs associated with mate finding and the production of males who do not themselves bear offspring. Theory predicts parasites select for host sex, because genetically variable offspring can escape infection from parasites adapted to infect the previous generations. We examine this using a facultative sexual crustacean, Daphnia magna, and its sterilizing bacterial parasite, Pasteuria ramosa We obtained sexually and asexually produced offspring from wild-caught hosts and exposed them to contemporary parasites or parasites isolated from the same population one year later. We found rapid parasite adaptation to replicate within asexual but not sexual offspring. Moreover, sexually produced offspring were twice as resistant to infection as asexuals when exposed to parasites that had coevolved alongside their parents (i.e. the year two parasite). This fulfils the requirement that the benefits of sex must be both large and rapid for sex to be favoured by selection. © 2016 The Author(s).

  13. Resilience of Networked Infrastructure with Evolving Component Conditions: Pavement Network Application

    DEFF Research Database (Denmark)

    Levenberg, Eyal; Miller-Hooks, Elise; Asadabadi, Ali

    2017-01-01

    This paper deals with quantifying the resilience of a network of pavements. Calculations were carried out by modeling network performance under a set of possible damage-meteorological scenarios with known probability of occurrence. Resilience evaluation was performed a priori while accounting...

  14. Evolvability Is an Evolved Ability: The Coding Concept as the Arch-Unit of Natural Selection.

    Science.gov (United States)

    Janković, Srdja; Ćirković, Milan M

    2016-03-01

    Physical processes that characterize living matter are qualitatively distinct in that they involve encoding and transfer of specific types of information. Such information plays an active part in the control of events that are ultimately linked to the capacity of the system to persist and multiply. This algorithmicity of life is a key prerequisite for its Darwinian evolution, driven by natural selection acting upon stochastically arising variations of the encoded information. The concept of evolvability attempts to define the total capacity of a system to evolve new encoded traits under appropriate conditions, i.e., the accessible section of total morphological space. Since this is dependent on previously evolved regulatory networks that govern information flow in the system, evolvability itself may be regarded as an evolved ability. The way information is physically written, read and modified in living cells (the "coding concept") has not changed substantially during the whole history of the Earth's biosphere. This biosphere, be it alone or one of many, is, accordingly, itself a product of natural selection, since the overall evolvability conferred by its coding concept (nucleic acids as information carriers with the "rulebook of meanings" provided by codons, as well as all the subsystems that regulate various conditional information-reading modes) certainly played a key role in enabling this biosphere to survive up to the present, through alterations of planetary conditions, including at least five catastrophic events linked to major mass extinctions. We submit that, whatever the actual prebiotic physical and chemical processes may have been on our home planet, or may, in principle, occur at some time and place in the Universe, a particular coding concept, with its respective potential to give rise to a biosphere, or class of biospheres, of a certain evolvability, may itself be regarded as a unit (indeed the arch-unit) of natural selection.

  15. Incremental Frequent Subgraph Mining on Large Evolving Graphs

    KAUST Repository

    Abdelhamid, Ehab; Canim, Mustafa; Sadoghi, Mohammad; Bhatta, Bishwaranjan; Chang, Yuan-Chi; Kalnis, Panos

    2017-01-01

    , such as social networks, utilize large evolving graphs. Mining these graphs using existing techniques is infeasible, due to the high computational cost. In this paper, we propose IncGM+, a fast incremental approach for continuous frequent subgraph mining problem

  16. Collaborative Services for Customized Production in Networked Companies

    OpenAIRE

    Fornasiero , Rosanna; Bastos , João; Azevedo , Américo; Zangiacomi , Andrea; Coscia , Eva

    2013-01-01

    Part 12: Services II; International audience; Increasingly, consumer demand of fashionable products is arising as significant challenge for company managers. In order to respond to this demand, companies are asked to supply small series of innovative and fashionable goods of high quality, affordable price and eco-compatibility in short periods of time and with high service levels. As a result of these rapidly evolving challenges, companies are forming collaborative networks in order to design...

  17. EvoCommander: A Novel Game Based on Evolving and Switching Between Artificial Brains

    DEFF Research Database (Denmark)

    Jallov, D.; Risi, S.; Togelius, J.

    2016-01-01

    Neuroevolution (i.e. evolving artificial neural networks (ANNs) through evolutionary algorithms) has shown promise in evolving agents and robot controllers, which display complex behaviours and can adapt to their environments. These properties are also relevant to video games, since they can...

  18. Evaluation and testing methodology for evolving entertainment systems

    NARCIS (Netherlands)

    Jurgelionis, A.; Bellotti, F.; IJsselsteijn, W.A.; Kort, de Y.A.W.; Bernhaupt, R.; Tscheligi, M.

    2007-01-01

    This paper presents a testing and evaluation methodology for evolving pervasive gaming and multimedia systems. We introduce the Games@Large system, a complex gaming and multimedia architecture comprised of a multitude of elements: heterogeneous end user devices, wireless and wired network

  19. Entropy of dynamical social networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

    2012-02-01

    Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

  20. Lack of evolvability in self-sustaining autocatalytic networks constraints metabolism-first scenarios for the origin of life.

    Science.gov (United States)

    Vasas, Vera; Szathmáry, Eörs; Santos, Mauro

    2010-01-26

    A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first "living" systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where self-reproducing and evolving proto-metabolic networks are assumed to have predated self-replicating genes. Recent theoretical work shows that "compositional genomes" (i.e., the counts of different molecular species in an assembly) are able to propagate compositional information and can provide a setup on which natural selection acts. Accordingly, if we stick to the notion of replicator as an entity that passes on its structure largely intact in successive replications, those macromolecular aggregates could be dubbed "ensemble replicators" (composomes) and quite different from the more familiar genes and memes. In sharp contrast with template-dependent replication dynamics, we demonstrate here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and, therefore, the system lacks evolvability (i.e., it cannot substantially depart from the asymptotic steady-state solution already built-in in the dynamical equations). We conclude that this fundamental limitation of ensemble replicators cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.

  1. Rapid response systems.

    Science.gov (United States)

    Lyons, Patrick G; Edelson, Dana P; Churpek, Matthew M

    2018-07-01

    Rapid response systems are commonly employed by hospitals to identify and respond to deteriorating patients outside of the intensive care unit. Controversy exists about the benefits of rapid response systems. We aimed to review the current state of the rapid response literature, including evolving aspects of afferent (risk detection) and efferent (intervention) arms, outcome measurement, process improvement, and implementation. Articles written in English and published in PubMed. Rapid response systems are heterogeneous, with important differences among afferent and efferent arms. Clinically meaningful outcomes may include unexpected mortality, in-hospital cardiac arrest, length of stay, cost, and processes of care at end of life. Both positive and negative interventional studies have been published, although the two largest randomized trials involving rapid response systems - the Medical Early Response and Intervention Trial (MERIT) and the Effect of a Pediatric Early Warning System on All-Cause Mortality in Hospitalized Pediatric Patients (EPOCH) trial - did not find a mortality benefit with these systems, albeit with important limitations. Advances in monitoring technologies, risk assessment strategies, and behavioral ergonomics may offer opportunities for improvement. Rapid responses may improve some meaningful outcomes, although these findings remain controversial. These systems may also improve care for patients at the end of life. Rapid response systems are expected to continue evolving with novel developments in monitoring technologies, risk prediction informatics, and work in human factors. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. The rapidly evolving centromere-specific histone has stringent functional requirements in Arabidopsis thaliana.

    Science.gov (United States)

    Ravi, Maruthachalam; Kwong, Pak N; Menorca, Ron M G; Valencia, Joel T; Ramahi, Joseph S; Stewart, Jodi L; Tran, Robert K; Sundaresan, Venkatesan; Comai, Luca; Chan, Simon W-L

    2010-10-01

    Centromeres control chromosome inheritance in eukaryotes, yet their DNA structure and primary sequence are hypervariable. Most animals and plants have megabases of tandem repeats at their centromeres, unlike yeast with unique centromere sequences. Centromere function requires the centromere-specific histone CENH3 (CENP-A in human), which replaces histone H3 in centromeric nucleosomes. CENH3 evolves rapidly, particularly in its N-terminal tail domain. A portion of the CENH3 histone-fold domain, the CENP-A targeting domain (CATD), has been previously shown to confer kinetochore localization and centromere function when swapped into human H3. Furthermore, CENP-A in human cells can be functionally replaced by CENH3 from distantly related organisms including Saccharomyces cerevisiae. We have used cenh3-1 (a null mutant in Arabidopsis thaliana) to replace endogenous CENH3 with GFP-tagged variants. A H3.3 tail domain-CENH3 histone-fold domain chimera rescued viability of cenh3-1, but CENH3's lacking a tail domain were nonfunctional. In contrast to human results, H3 containing the A. thaliana CATD cannot complement cenh3-1. GFP-CENH3 from the sister species A. arenosa functionally replaces A. thaliana CENH3. GFP-CENH3 from the close relative Brassica rapa was targeted to centromeres, but did not complement cenh3-1, indicating that kinetochore localization and centromere function can be uncoupled. We conclude that CENH3 function in A. thaliana, an organism with large tandem repeat centromeres, has stringent requirements for functional complementation in mitosis.

  3. High-resolution method for evolving complex interface networks

    Science.gov (United States)

    Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

    2018-04-01

    In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

  4. Can We Recognize an Innovation? Perspective from an Evolving Network Model

    Science.gov (United States)

    Jain, Sanjay; Krishna, Sandeep

    "Innovations" are central to the evolution of societies and the evolution of life. But what constitutes an innovation? We can often agree after the event, when its consequences and impact over a long term are known, whether something was an innovation, and whether it was a "big" innovation or a "minor" one. But can we recognize an innovation "on the fly" as it appears? Successful entrepreneurs often can. Is it possible to formalize that intuition? We discuss this question in the setting of a mathematical model of evolving networks. The model exhibits self-organization , growth, stasis, and collapse of a complex system with many interacting components, reminiscent of real-world phenomena. A notion of "innovation" is formulated in terms of graph-theoretic constructs and other dynamical variables of the model. A new node in the graph gives rise to an innovation, provided it links up "appropriately" with existing nodes; in this view innovation necessarily depends upon the existing context. We show that innovations, as defined by us, play a major role in the birth, growth, and destruction of organizational structures. Furthermore, innovations can be categorized in terms of their graph-theoretic structure as they appear. Different structural classes of innovation have potentially different qualitative consequences for the future evolution of the system, some minor and some major. Possible general lessons from this specific model are briefly discussed.

  5. De novo ORFs in Drosophila are important to organismal fitness and evolved rapidly from previously non-coding sequences.

    Directory of Open Access Journals (Sweden)

    Josephine A Reinhardt

    Full Text Available How non-coding DNA gives rise to new protein-coding genes (de novo genes is not well understood. Recent work has revealed the origins and functions of a few de novo genes, but common principles governing the evolution or biological roles of these genes are unknown. To better define these principles, we performed a parallel analysis of the evolution and function of six putatively protein-coding de novo genes described in Drosophila melanogaster. Reconstruction of the transcriptional history of de novo genes shows that two de novo genes emerged from novel long non-coding RNAs that arose at least 5 MY prior to evolution of an open reading frame. In contrast, four other de novo genes evolved a translated open reading frame and transcription within the same evolutionary interval suggesting that nascent open reading frames (proto-ORFs, while not required, can contribute to the emergence of a new de novo gene. However, none of the genes arose from proto-ORFs that existed long before expression evolved. Sequence and structural evolution of de novo genes was rapid compared to nearby genes and the structural complexity of de novo genes steadily increases over evolutionary time. Despite the fact that these genes are transcribed at a higher level in males than females, and are most strongly expressed in testes, RNAi experiments show that most of these genes are essential in both sexes during metamorphosis. This lethality suggests that protein coding de novo genes in Drosophila quickly become functionally important.

  6. On the Rapid Rise of Social Networking Sites: New Findings and Policy Implications

    Science.gov (United States)

    Livingstone, Sonia; Brake, David R

    2010-01-01

    Social networking sites have been rapidly adopted by children and, especially, teenagers and young people worldwide, enabling new opportunities for the presentation of the self, learning, construction of a wide circle of relationships, and the management of privacy and intimacy. On the other hand, there are also concerns that social networking…

  7. Rapid-response Sensor Networks Leveraging Open Standards and the Internet of Things

    Science.gov (United States)

    Bermudez, L. E.; Lieberman, J. E.; Lewis, L.; Botts, M.; Liang, S.

    2016-12-01

    New sensor technologies provide an unparalleled capability to collect large numbers of diverse observations about the world around us. Networks of such sensors are especially effective for capturing and analyzing unexpected, fast moving events if they can be deployed with a minimum of time, effort, and cost. A rapid-response sensing and processing capability is extremely important in quickly unfolding events not only to collect data for future research.but also to support response efforts that may be needed by providing up-to-date knowledge of the situation. A recent pilot activity coordinated by the Open Geospatial Consortium combined Sensor Web Enablement (SWE) standards with Internet of Things (IoT) practices to understand better how to set up rapid-response sensor networks in comparable event situations involving accidents or disasters. The networks included weather and environmental sensors, georeferenced UAV and PTZ imagery collectors, and observations from "citizen sensors", as well as virtual observations generated by predictive models. A key feature of each "SWE-IoT" network was one or more Sensor Hubs that connected local, often proprietary sensor device protocols to a common set of standard SWE data types and standard Web interfaces on an IP-based internetwork. This IoT approach provided direct, common, interoperable access to all sensor readings from anywhere on the internetwork of sensors, Hubs, and applications. Sensor Hubs also supported an automated discovery protocol in which activated Hubs registered themselves with a canonical catalog service. As each sensor (wireless or wired) was activated within range of an authorized Hub, it registered itself with that Hub, which in turn registered the sensor and its capabilities with the catalog. Sensor Hub functions were implemented in a range of component types, from personal devices such as smartphones and Raspberry Pi's to full cloud-based sensor services platforms. Connected into a network

  8. An Analysis of Quality of Service (QoS In Live Video Streaming Using Evolved HSPA Network Media

    Directory of Open Access Journals (Sweden)

    Achmad Zakaria Azhar

    2016-10-01

    Full Text Available Evolved High Speed Packet Access (HSPA+ is a mobile telecommunication system technology and the evolution of HSPA technology. This technology has a packet data based service with downlink speeds up to 21.1 Mbps and uplink speed up to 11.5 Mbps on the bandwidth 5MHz. This technology is expected to fulfill and support the needs for information that involves all aspects of multimedia such as video and audio, especially live video streaming. By utilizing this technology it will facilitate communicating the information, for example to monitoring the situation of the house, the news coverage at some certain area, and other events in real time. This thesis aims to identify and test the Quality of Service (QoS performance on the network that is used for live video streaming with the parameters of throughput, delay, jitter and packet loss. The software used for monitoring the data traffic of the live video streaming network is wireshark network analyzer. From the test results it is obtained that the average throughput of provider B is 5,295 Kbps bigger than the provider A, the average delay of provider B is 0.618 ms smaller than the provider A, the average jitter of provider B is 0.420 ms smaller than the provider A and the average packet loss of provider B is 0.451% smaller than the provider A.

  9. Epidemic dynamics on a risk-based evolving social network

    Science.gov (United States)

    Antwi, Shadrack; Shaw, Leah

    2013-03-01

    Social network models have been used to study how behavior affects the dynamics of an infection in a population. Motivated by HIV, we consider how a trade-off between benefits and risks of sexual connections determine network structure and disease prevalence. We define a stochastic network model with formation and breaking of links as changes in sexual contacts. Each node has an intrinsic benefit its neighbors derive from connecting to it. Nodes' infection status is not apparent to others, but nodes with more connections (higher degree) are assumed more likely to be infected. The probability to form and break links is determined by a payoff computed from the benefit and degree-dependent risk. The disease is represented by a SI (susceptible-infected) model. We study network and epidemic evolution via Monte Carlo simulation and analytically predict the behavior with a heterogeneous mean field approach. The dependence of network connectivity and infection threshold on parameters is determined, and steady state degree distribution and epidemic levels are obtained. We also study a situation where system-wide infection levels alter perception of risk and cause nodes to adjust their behavior. This is a case of an adaptive network, where node status feeds back to change network geometry.

  10. The utility of dermoscopy in the diagnosis of evolving lesions of vitiligo

    Directory of Open Access Journals (Sweden)

    Sarvesh S Thatte

    2014-01-01

    Full Text Available Background: Early lesions of vitiligo can be confused with various other causes of hypopigmentation and depigmentation. Few workers have utilized dermoscopy for the diagnosis of evolving lesions of vitiligo. Aim: To analyze the dermoscopic findings of evolving lesions in diagnosed cases of vitiligo and to correlate them histopathologically. Methods: Dermoscopy of evolving lesions in 30 diagnosed cases of vitiligo was performed using both polarized light and ultraviolet light. Result: On polarized light examination, the pigmentary network was found to be reduced in 12 (40% of 30 patients, absent in 9 (30%, and reversed in 6 (20% patients; 2 patients (6.7% showed perifollicular hyperpigmentation and 1 (3.3% had perilesional hyperpigmentation. A diffuse white glow was demonstrable in 27 (90% of 30 patients on ultraviolet light examination. Melanocytes were either reduced in number or absent in 12 (40% of 30 patients on histopathology. Conclusion: Pigmentary network changes, and perifollicular and perilesional hyperpigmentation on polarized light examination, and a diffuse white glow on ultraviolet light examination were noted in evolving vitiligo lesions. Histopathological examination was comparatively less reliable. Dermoscopy appears to be better than routine histopathology in the diagnosis of evolving lesions of vitiligo and can obviate the need for a skin biopsy.

  11. Money Laundering Detection Framework to Link the Disparate and Evolving Schemes

    Directory of Open Access Journals (Sweden)

    Murad Mehmet

    2013-09-01

    Full Text Available Money launderers hide traces of their transactions with the involvement of entities that participate in sophisticated schemes. Money laundering detection requires unraveling concealed connections among multiple but seemingly unrelated human money laundering networks, ties among actors of those schemes, and amounts of funds transferred among those entities. The link among small networks, either financial or social, is the primary factor that facilitates money laundering. Hence, the analysis of relations among money laundering networks is required to present the full structure of complex schemes. We propose a framework that uses sequence matching, case-based analysis, social network analysis, and complex event processing to detect money laundering. Our framework captures an ongoing single scheme as an event, and associations among such ongoing sequence of events to capture complex relationships among evolving money laundering schemes. The framework can detect associated multiple money laundering networks even in the absence of some evidence. We validated the accuracy of detecting evolving money laundering schemes using a multi-phases test methodology. Our test used data generated from real-life cases, and extrapolated to generate more data from real-life schemes generator that we implemented.

  12. Specificity and evolvability in eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Pedro Beltrao

    2007-02-01

    Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

  13. Autonomous Agent-Based Systems and Their Applications in Fluid Dynamics, Particle Separation, and Co-evolving Networks

    Science.gov (United States)

    Graeser, Oliver

    This thesis comprises three parts, reporting research results in Fluid Dynamics (Part I), Particle Separation (Part II) and Co-evolving Networks (Part III). Part I deals with the simulation of fluid dynamics using the lattice-Boltzmann method. Microfluidic devices often feature two-dimensional, repetitive arrays. Flows through such devices are pressure-driven and confined by solid walls. We have defined new adaptive generalised periodic boundary conditions to represent the effects of outer solid walls, and are thus able to exploit the periodicity of the array by simulating the flow through one unit cell in lieu of the entire device. The so-calculated fully developed flow describes the flow through the entire array accurately, but with computational requirements that are reduced according to the dimensions of the array. Part II discusses the problem of separating macromolecules like proteins or DNA coils. The reliable separation of such molecules is a crucial task in molecular biology. The use of Brownian ratchets as mechanisms for the separation of such particles has been proposed and discussed during the last decade. Pressure-driven flows have so far been dismissed as possible driving forces for Brownian ratchets, as they do not generate ratchet asymmetry. We propose a microfluidic design that uses pressure-driven flows to create asymmetry and hence allows particle separation. The dependence of the asymmetry on various factors of the microfluidic geometry is discussed. We further exemplify the feasibility of our approach using Brownian dynamics simulations of particles of different sizes in such a device. The results show that ratchet-based particle separation using flows as the driving force is possible. Simulation results and ratchet theory predictions are in excellent agreement. Part III deals with the co-evolution of networks and dynamic models. A group of agents occupies the nodes of a network, which defines the relationship between these agents. The

  14. Networks in biological systems: An investigation of the Gene Ontology as an evolving network

    International Nuclear Information System (INIS)

    Coronnello, C; Tumminello, M; Micciche, S; Mantegna, R.N.

    2009-01-01

    Many biological systems can be described as networks where different elements interact, in order to perform biological processes. We introduce a network associated with the Gene Ontology. Specifically, we construct a correlation-based network where the vertices are the terms of the Gene Ontology and the link between each two terms is weighted on the basis of the number of genes that they have in common. We analyze a filtered network obtained from the correlation-based network and we characterize its evolution over different releases of the Gene Ontology.

  15. A local-world node deleting evolving network model

    International Nuclear Information System (INIS)

    Gu Yuying; Sun Jitao

    2008-01-01

    A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p a decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k max . Hence, the expanding local-world can compensate the infection of the node deleting

  16. A local-world node deleting evolving network model

    Energy Technology Data Exchange (ETDEWEB)

    Gu Yuying [Department of Mathematics, Tongji University, Shanghai 200092 (China); Sun Jitao [Department of Mathematics, Tongji University, Shanghai 200092 (China)], E-mail: sunjt@sh163.net

    2008-06-16

    A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p{sub a} decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k{sub max}. Hence, the expanding local-world can compensate the infection of the node deleting.

  17. Characterizing 3-D flow velocity in evolving pore networks driven by CaCO3 precipitation and dissolution

    Science.gov (United States)

    Chojnicki, K. N.; Yoon, H.; Martinez, M. J.

    2015-12-01

    Understanding reactive flow in geomaterials is important for optimizing geologic carbon storage practices, such as using pore space efficiently. Flow paths can be complex in large degrees of geologic heterogeneities across scales. In addition, local heterogeneity can evolve as reactive transport processes alter the pore-scale morphology. For example, dissolved carbon dioxide may react with minerals in fractured rocks, confined aquifers, or faults, resulting in heterogeneous cementation (and/or dissolution) and evolving flow conditions. Both path and flow complexities are important and poorly characterized, making it difficult to determine their evolution with traditional 2-D transport models. Here we characterize the development of 3-D pore-scale flow with an evolving pore configuration due to calcium carbonate (CaCO3) precipitation and dissolution. A simple pattern of a microfluidic pore network is used initially and pore structures will become more complex due to precipitation and dissolution processes. At several stages of precipitation and dissolution, we directly visualize 3-D velocity vectors using micro particle image velocimetry and a laser scanning confocal microscope. Measured 3-D velocity vectors are then compared to 3-D simulated flow fields which will be used to simulate reactive transport. Our findings will highlight the importance of the 3-D flow dynamics and its impact on estimating reactive surface area over time. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. This material is based upon work supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001114.

  18. Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

    Science.gov (United States)

    Borges, Rafael R.; Borges, Fernando S.; Lameu, Ewandson L.; Protachevicz, Paulo R.; Iarosz, Kelly C.; Caldas, Iberê L.; Viana, Ricardo L.; Macau, Elbert E. N.; Baptista, Murilo S.; Grebogi, Celso; Batista, Antonio M.

    2017-12-01

    Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.

  19. Evolving Neural Turing Machines for Reward-based Learning

    DEFF Research Database (Denmark)

    Greve, Rasmus Boll; Jacobsen, Emil Juul; Risi, Sebastian

    2016-01-01

    An unsolved problem in neuroevolution (NE) is to evolve artificial neural networks (ANN) that can store and use information to change their behavior online. While plastic neural networks have shown promise in this context, they have difficulties retaining information over longer periods of time...... version of the double T-Maze, a complex reinforcement-like learning problem. In the T-Maze learning task the agent uses the memory bank to display adaptive behavior that normally requires a plastic ANN, thereby suggesting a complementary and effective mechanism for adaptive behavior in NE....

  20. The genotype-phenotype map of an evolving digital organism.

    Directory of Open Access Journals (Sweden)

    Miguel A Fortuna

    2017-02-01

    Full Text Available To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences, which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

  1. The genotype-phenotype map of an evolving digital organism.

    Science.gov (United States)

    Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

    2017-02-01

    To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

  2. Evolving fuzzy rules for relaxed-criteria negotiation.

    Science.gov (United States)

    Sim, Kwang Mong

    2008-12-01

    In the literature on automated negotiation, very few negotiation agents are designed with the flexibility to slightly relax their negotiation criteria to reach a consensus more rapidly and with more certainty. Furthermore, these relaxed-criteria negotiation agents were not equipped with the ability to enhance their performance by learning and evolving their relaxed-criteria negotiation rules. The impetus of this work is designing market-driven negotiation agents (MDAs) that not only have the flexibility of relaxing bargaining criteria using fuzzy rules, but can also evolve their structures by learning new relaxed-criteria fuzzy rules to improve their negotiation outcomes as they participate in negotiations in more e-markets. To this end, an evolutionary algorithm for adapting and evolving relaxed-criteria fuzzy rules was developed. Implementing the idea in a testbed, two kinds of experiments for evaluating and comparing EvEMDAs (MDAs with relaxed-criteria rules that are evolved using the evolutionary algorithm) and EMDAs (MDAs with relaxed-criteria rules that are manually constructed) were carried out through stochastic simulations. Empirical results show that: 1) EvEMDAs generally outperformed EMDAs in different types of e-markets and 2) the negotiation outcomes of EvEMDAs generally improved as they negotiated in more e-markets.

  3. Fundamentals of wireless sensor networks theory and practice

    CERN Document Server

    Dargie, Waltenegus

    2010-01-01

    In this book, the authors describe the fundamental concepts and practical aspects of wireless sensor networks. The book provides a comprehensive view to this rapidly evolving field, including its many novel applications, ranging from protecting civil infrastructure to pervasive health monitoring. Using detailed examples and illustrations, this book provides an inside track on the current state of the technology. The book is divided into three parts. In Part I, several node architectures, applications and operating systems are discussed. In Part II, the basic architectural frameworks, including

  4. Biobanks in the United States: how to identify an undefined and rapidly evolving population.

    Science.gov (United States)

    Boyer, Gregory J; Whipple, Warren; Cadigan, R Jean; Henderson, Gail E

    2012-12-01

    As part of a larger organizational study, we sought to survey biobanks in the United States. However, we encountered two problems with this population. First, no common definition of biobanks exists. Second, no census is available of these facilities from which to sample in order to implement a survey. In light of these problems, we employed a multifaceted approach using electronic searches of PubMed, RePORTER, and Google. In addition, we systematically searched for biobanks housed within universities that have NIH-designated Clinical and Translational Science Awards (CTSA). We expanded this part of the search by looking for biobanks among all members of the American Association of Medical Colleges (AAMC). Finally, we added banks to our database found previously by other researchers and banks found via correspondence with our colleagues. Our search strategy produced a database of 624 biobanks for which we were able to confirm contact information in order to conduct our online survey. Another 140 biobanks were identified but did not respond to our requests to confirm their existence or contact information. In order to maximize both the uniqueness of banks found and the greatest return on effort for each search, we suggest targeting resources that are already organized. In our work, these included the CTSA, AAMC, and part of the Google searches. We contend that our search provides a model for analysis of new fields of research and/or rapidly evolving industries. Furthermore, our approach demonstrates that with the appropriate tools it is possible to develop a systematic and comprehensive database to investigate undefined populations.

  5. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

    International Nuclear Information System (INIS)

    Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

    2012-01-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

  6. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

    Science.gov (United States)

    Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

    2012-10-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

  7. Convolutional Neural Network for Multi-Category Rapid Serial Visual Presentation BCI

    Directory of Open Access Journals (Sweden)

    Ran eManor

    2015-12-01

    Full Text Available Brain computer interfaces rely on machine learning algorithms to decode the brain's electrical activity into decisions. For example, in rapid serial visual presentation (RSVP tasks, the subject is presented with a continuous stream of images containing rare target images among standard images, while the algorithm has to detect brain activity associated with target images. Here, we continue our previous work, presenting a deep neural network model for the use of single trial EEG classification in RSVP tasks. Deep neural networks have shown state of the art performance in computer vision and speech recognition and thus have great promise for other learning tasks, like classification of EEG samples. In our model, we introduce a novel spatio-temporal regularization for EEG data to reduce overfitting. We show improved classification performance compared to our earlier work on a five categories RSVP experiment. In addition, we compare performance on data from different sessions and validate the model on a public benchmark data set of a P300 speller task. Finally, we discuss the advantages of using neural network models compared to manually designing feature extraction algorithms.

  8. Reconfigurable network systems and software-defined networking

    OpenAIRE

    Zilberman, N.; Watts, P. M.; Rotsos, C.; Moore, A. W.

    2015-01-01

    Modern high-speed networks have evolved from relatively static networks to highly adaptive networks facilitating dynamic reconfiguration. This evolution has influenced all levels of network design and management, introducing increased programmability and configuration flexibility. This influence has extended from the lowest level of physical hardware interfaces to the highest level of network management by software. A key representative of this evolution is the emergence of software-defined n...

  9. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Hansen, Jonas; Roetter, Daniel Enrique Lucani; Krigslund, Jeppe

    2015-01-01

    Software defined networking has garnered large attention due to its potential to virtualize services in the Internet, introducing flexibility in the buffering, scheduling, processing, and routing of data in network routers. SDN breaks the deadlock that has kept Internet network protocols stagnant...... for decades, while applications and physical links have evolved. This article advocates for the use of SDN to bring about 5G network services by incorporating network coding (NC) functionalities. The latter constitutes a major leap forward compared to the state-of-the- art store and forward Internet paradigm...

  10. Partially satisfied to fully satisfied transitions in co-evolving inverse voter model and possible scaling behavior

    International Nuclear Information System (INIS)

    Choi, C.W.; Xu, C.; Hui, P.M.

    2015-01-01

    Understanding co-evolving networks characterized by the mutual influence of agents' actions and network structure remains a challenge. We study a co-evolving inverse voter model in which agents adapt to achieve a preferred environment with more opposite-opinion neighbors by rewiring their connections and switching opinion. Numerical studies reveal a transition from a dynamic partially satisfied phase to a frozen fully satisfied phase as the rewiring probability is varied. A simple mean field theory is shown to capture the behavior only qualitatively. An improved mean field theory carrying a longer spatial correlation gives better results. Motivated by numerical results in networks of different degrees and mean field results, we propose a scaling variable that combines the rewiring probability and mean degree in a special form. The scaling variable is shown to work well in analyzing data corresponding to different networks and different rewiring probabilities. An application is to predict the results for networks of different degrees based solely on results obtained from networks of one degree. Studying scaling behavior provides an alternative path for understanding co-evolving agent-based dynamical systems, especially in light of the trade-off between complexity of a theory and its accuracy. - Highlights: • Identified key features and phase transitions in coevolving inverse voter model. • Constructed a better theory incorporating longer spatial correlation. • Proposed scaling variable and illustrated possible scaling behavior. • Used scaling behavior to predict results of IVM in a different network.

  11. The Evolving Wide Area Network Infrastructure in the LHC era

    CERN Multimedia

    CERN. Geneva

    2004-01-01

    The global network is more than ever taking its role as the great "enabler" for many branches of science and research. Foremost amongst such science drivers is of course the LHC/LCG programme, although there are several other sectors with growing demands of the network. Common to all of these is the realisation that a straightforward over provisioned best efforts wide area IP service is probably not enough for the future. This talk will summarise the needs of several science sectors, and the advances being made to exploit the current best efforts infrastructure. It will then describe current projects aimed as provisioning "better than best efforts" services (such bandwidth on demand), the global optical R&D testbeds and the strategy of the research network providers to move towards hybrid multi-service networks for the next generation of the global wide area production network.

  12. Evolving Stochastic Learning Algorithm based on Tsallis entropic index

    Science.gov (United States)

    Anastasiadis, A. D.; Magoulas, G. D.

    2006-03-01

    In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time-dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method.

  13. The evolving network structure of US airline system during 1990-2010

    Science.gov (United States)

    Lin, Jingyi; Ban, Yifang

    2014-09-01

    This paper analyzes the growth and evolution of topological features of the US airline network over a 20-year period. It captures the change in the network system from different dimensions of complex networks such as centrality distribution and various structural properties of the network over time. We first illustrate the results of a set of measures, including degree, strength, betweenness centrality, and clustering structure. The geographic features of airport systems, spatial distance and network efficiency are also discussed in this section. In order to further capture the dynamics of the system, this paper also explores the correlation between different measures, and investigates various interactions inside the network. Overall this study offers a novel approach to understanding the growth and evolution of real physical networks.

  14. Benefits of Self-Organizing Networks (SON for Mobile Operators

    Directory of Open Access Journals (Sweden)

    Olav Østerbø

    2012-01-01

    Full Text Available Self-Organizing Networks (SON is a collection of functions for automatic configuration, optimization, diagnostisation and healing of cellular networks. It is considered to be a necessity in future mobile networks and operations due to the increased cost pressure. The main drivers are essentially to reduce CAPEX and OPEX, which would otherwise increase dramatically due to increased number of network parameters that has to be monitored and set, the rapidly increasing numbers of base stations in the network and parallel operation of 2G, 3G and Evolved Packet Core (EPC infrastructures. This paper presents evaluations on the use of some of the most important SON components. Mobile networks are getting more complex to configure, optimize and maintain. Many SON functions will give cost savings and performance benefits from the very beginning of a network deployment and these should be prioritized now. But even if many functions are already available and can give large benefits, the field is still in its infancy and more advanced functions are either not yet implemented or have immature implementations. It is therefore necessary to have a strategy for how and when different SON functions should be introduced in mobile networks.

  15. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  16. Exploring the Requisite Skills and Competencies of Pharmacists Needed for Success in an Evolving Health Care Environment.

    Science.gov (United States)

    McLaughlin, Jacqueline E; Bush, Antonio A; Rodgers, Philip T; Scott, Mollie Ashe; Zomorodi, Meg; Pinelli, Nicole R; Roth, Mary T

    2017-08-01

    Objective. To identify and describe the core competencies and skills considered essential for success of pharmacists in today's rapidly evolving health care environment. Methods. Six breakout groups of 15-20 preceptors, pharmacists, and partners engaged in a facilitated discussion about the qualities and characteristics relevant to the success of a pharmacy graduate. Data were analyzed using qualitative methods. Peer-debriefing, multiple coders, and member-checking were used to promote trustworthiness of findings. Results. Eight overarching themes were identified: critical thinking and problem solving; collaboration across networks and leading by influence; agility and adaptability; initiative and entrepreneurialism; effective oral and written communication; accessing and analyzing information; curiosity and imagination; and self-awareness. Conclusion. This study is an important step toward understanding how to best prepare pharmacy students for the emerging health care needs of society.

  17. Evolution Characteristics of the Network Core in the Facebook

    OpenAIRE

    Liu, Jian-Guo; Ren, Zhuo-Ming; Guo, Qiang; Chen, Duan-Bing

    2014-01-01

    Statistical properties of the static networks have been extensively studied. However, online social networks are evolving dynamically, understanding the evolving characteristics of the core is one of major concerns in online social networks. In this paper, we empirically investigate the evolving characteristics of the Facebook core. Firstly, we separate the Facebook-link(FL) and Facebook-wall(FW) datasets into 28 snapshots in terms of timestamps. By employing the k-core decomposition method t...

  18. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  19. Network evolution of body plans.

    Directory of Open Access Journals (Sweden)

    Koichi Fujimoto

    Full Text Available One of the major goals in evolutionary developmental biology is to understand the relationship between gene regulatory networks and the diverse morphologies and their functionalities. Are the diversities solely triggered by random events, or are they inevitable outcomes of an interplay between evolving gene networks and natural selection? Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band development, respectively. Moreover, a combination of both is found in intermediate germ-band development. Regulatory genes relevant for stripe formation are evolutionarily conserved among arthropods, therefore the differences in the observed traits are thought to have originated from how the genes are wired. To reveal the basic differences in the network structure, we have numerically evolved hundreds of gene regulatory networks that produce striped patterns of gene expression. By analyzing the topologies of the generated networks, we show that the characteristics of stripe formation in long and short germ-band development are determined by Feed-Forward Loops (FFLs and negative Feed-Back Loops (FBLs respectively, and those of intermediate germ-band development are determined by the interconnections between FFL and negative FBL. Network architectures, gene expression patterns and knockout responses exhibited by the artificially evolved networks agree with those reported in the fly Drosophila melanogaster and the beetle Tribolium castaneum. For other arthropod species, principal network architectures that remain largely unknown are predicted. Our results suggest that the emergence of the three modes of body segmentation in arthropods is an inherent property of the evolving networks.

  20. Strings as perturbations of evolving spin networks

    International Nuclear Information System (INIS)

    Smolin, Lee

    2000-01-01

    One step in the construction of a background independent formulation of string theory is detailed, in which it is shown how perturbative strings may arise as small fluctuations around histories in a formulation of non-perturbative dynamics of spin networks due to Markopoulou. In this formulation the dynamics of spin network states and their generalizations is described in terms of histories which have discrete analogues of the causal structure and many fingered time of Lorentzian spacetimes. Perturbations of these histories turn out to be described in terms of spin systems defined on 2-dimensional timelike surfaces embedded in the discrete spacetime. When the history has a classical limit which is Minkowski spacetime, the action of the perturbation theory is given to leading order by the spacetime area of the surface, as in bosonic string theory. This map between a non-perturbative formulation of quantum gravity and a 1+1 dimensional theory generalizes to a large class of theories in which the group SU(2) i s extended to any quantum group or supergroup. It is argued that a necessary condition for the non-perturbative theory to have a good classical limit is that the resulting 1+1 dimensional theory defines a consistent and stable perturbative string theory

  1. Popularity and Novelty Dynamics in Evolving Networks.

    Science.gov (United States)

    Abbas, Khushnood; Shang, Mingsheng; Abbasi, Alireza; Luo, Xin; Xu, Jian Jun; Zhang, Yu-Xia

    2018-04-20

    Network science plays a big role in the representation of real-world phenomena such as user-item bipartite networks presented in e-commerce or social media platforms. It provides researchers with tools and techniques to solve complex real-world problems. Identifying and predicting future popularity and importance of items in e-commerce or social media platform is a challenging task. Some items gain popularity repeatedly over time while some become popular and novel only once. This work aims to identify the key-factors: popularity and novelty. To do so, we consider two types of novelty predictions: items appearing in the popular ranking list for the first time; and items which were not in the popular list in the past time window, but might have been popular before the recent past time window. In order to identify the popular items, a careful consideration of macro-level analysis is needed. In this work we propose a model, which exploits item level information over a span of time to rank the importance of the item. We considered ageing or decay effect along with the recent link-gain of the items. We test our proposed model on four various real-world datasets using four information retrieval based metrics.

  2. Competing edge networks

    International Nuclear Information System (INIS)

    Parsons, Mark; Grindrod, Peter

    2012-01-01

    We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails. -- Highlights: ► A model for edgewise-competing evolving network pairs is introduced. ► Defined competition equations yield to a mean field analysis. ► Multiple equilibrium states and different bifurcation types can occur. ► The system is sensitive to sparse initial conditions and near unstable equilibriums.

  3. Evolving approaches to the ethical management of genomic data.

    Science.gov (United States)

    McEwen, Jean E; Boyer, Joy T; Sun, Kathie Y

    2013-06-01

    The ethical landscape in the field of genomics is rapidly shifting. Plummeting sequencing costs, along with ongoing advances in bioinformatics, now make it possible to generate an enormous volume of genomic data about vast numbers of people. The informational richness, complexity, and frequently uncertain meaning of these data, coupled with evolving norms surrounding the sharing of data and samples and persistent privacy concerns, have generated a range of approaches to the ethical management of genomic information. As calls increase for the expanded use of broad or even open consent, and as controversy grows about how best to handle incidental genomic findings, these approaches, informed by normative analysis and empirical data, will continue to evolve alongside the science. Published by Elsevier Ltd.

  4. Evolvable mathematical models: A new artificial Intelligence paradigm

    Science.gov (United States)

    Grouchy, Paul

    We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

  5. Evolving networks and the development of neural systems

    International Nuclear Information System (INIS)

    Johnson, Samuel; Marro, J; Torres, Joaquín J

    2010-01-01

    It is now generally assumed that the heterogeneity of most networks in nature probably arises via preferential attachment of some sort. However, the origin of various other topological features, such as degree–degree correlations and related characteristics, is often not clear, and they may arise from specific functional conditions. We show how it is possible to analyse a very general scenario in which nodes can gain or lose edges according to any (e.g., nonlinear) function of local and/or global degree information. Applying our method to two rather different examples of brain development—synaptic pruning in humans and the neural network of the worm C. Elegans—we find that simple biologically motivated assumptions lead to very good agreement with experimental data. In particular, many nontrivial topological features of the worm's brain arise naturally at a critical point

  6. Online social networking: a primer for radiology.

    Science.gov (United States)

    Prasanna, Prasanth M; Seagull, F Jacob; Nagy, Paul

    2011-10-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-communication is effective? What are the potential benefits and pitfalls of this form of communication? Physicians are exploring how social networking might provide a forum for interacting with their patients, and advance collaborative patient care. Several organizations and institutions have set forth policies to address these questions and more. Though still in its infancy, this form of media has the power to revolutionize the way physicians interact with their patients and fellow health care workers. In the end, physicians must ask what value is added by engaging patients or other health care providers in a social networking format. Social networks may flourish in health care as a means of distributing information to patients or serve mainly as support groups among patients. Physicians must tread a narrow path to bring value to interactions in these networks while limiting their exposure to unwanted liability.

  7. A roadmap for evolving towards optical intra-data-center networks

    DEFF Research Database (Denmark)

    Dittmann, Lars; Fagertun, Anna Manolova; Kamchevska, Valerija

    2016-01-01

    The first part of this paper focuses on presenting an updated view on the state of the art in data center networks. The European project COSIGN has provided industrial optical data center network roadmaps, strategies and a techno-economic analysis of the involved industrial partners’ value propos...

  8. Nonsynonymous substitution rate (Ka is a relatively consistent parameter for defining fast-evolving and slow-evolving protein-coding genes

    Directory of Open Access Journals (Sweden)

    Wang Lei

    2011-02-01

    Full Text Available Abstract Background Mammalian genome sequence data are being acquired in large quantities and at enormous speeds. We now have a tremendous opportunity to better understand which genes are the most variable or conserved, and what their particular functions and evolutionary dynamics are, through comparative genomics. Results We chose human and eleven other high-coverage mammalian genome data–as well as an avian genome as an outgroup–to analyze orthologous protein-coding genes using nonsynonymous (Ka and synonymous (Ks substitution rates. After evaluating eight commonly-used methods of Ka and Ks calculation, we observed that these methods yielded a nearly uniform result when estimating Ka, but not Ks (or Ka/Ks. When sorting genes based on Ka, we noticed that fast-evolving and slow-evolving genes often belonged to different functional classes, with respect to species-specificity and lineage-specificity. In particular, we identified two functional classes of genes in the acquired immune system. Fast-evolving genes coded for signal-transducing proteins, such as receptors, ligands, cytokines, and CDs (cluster of differentiation, mostly surface proteins, whereas the slow-evolving genes were for function-modulating proteins, such as kinases and adaptor proteins. In addition, among slow-evolving genes that had functions related to the central nervous system, neurodegenerative disease-related pathways were enriched significantly in most mammalian species. We also confirmed that gene expression was negatively correlated with evolution rate, i.e. slow-evolving genes were expressed at higher levels than fast-evolving genes. Our results indicated that the functional specializations of the three major mammalian clades were: sensory perception and oncogenesis in primates, reproduction and hormone regulation in large mammals, and immunity and angiotensin in rodents. Conclusion Our study suggests that Ka calculation, which is less biased compared to Ks and Ka

  9. Rapid self-organised initiation of ad hoc sensor networks close above the percolation threshold

    Science.gov (United States)

    Korsnes, Reinert

    2010-07-01

    This work shows potentials for rapid self-organisation of sensor networks where nodes collaborate to relay messages to a common data collecting unit (sink node). The study problem is, in the sense of graph theory, to find a shortest path tree spanning a weighted graph. This is a well-studied problem where for example Dijkstra’s algorithm provides a solution for non-negative edge weights. The present contribution shows by simulation examples that simple modifications of known distributed approaches here can provide significant improvements in performance. Phase transition phenomena, which are known to take place in networks close to percolation thresholds, may explain these observations. An initial method, which here serves as reference, assumes the sink node starts organisation of the network (tree) by transmitting a control message advertising its availability for its neighbours. These neighbours then advertise their current cost estimate for routing a message to the sink. A node which in this way receives a message implying an improved route to the sink, advertises its new finding and remembers which neighbouring node the message came from. This activity proceeds until there are no more improvements to advertise to neighbours. The result is a tree network for cost effective transmission of messages to the sink (root). This distributed approach has potential for simple improvements which are of interest when minimisation of storage and communication of network information are a concern. Fast organisation of the network takes place when the number k of connections for each node ( degree) is close above its critical value for global network percolation and at the same time there is a threshold for the nodes to decide to advertise network route updates.

  10. Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

    Science.gov (United States)

    Crowell, B. W.; Bock, Y.; Squibb, M. B.

    2010-12-01

    Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

  11. Co-evolution of the brand effect and competitiveness in evolving networks

    Science.gov (United States)

    Guo, Jin-Li

    2014-07-01

    The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes' properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.

  12. Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It

    DEFF Research Database (Denmark)

    Mengistu, Henok; Lehman, Joel Anthony; Clune, Jeff

    2016-01-01

    of evolvable digital phenotypes. Although some types of selection in evolutionary computation indirectly encourage evolvability, one unexplored possibility is to directly select for evolvability. To do so, we estimate an individual's future potential for diversity by calculating the behavioral diversity of its...... immediate offspring, and select organisms with increased offspring variation. While the technique is computationally expensive, we hypothesized that direct selection would better encourage evolvability than indirect methods. Experiments in two evolutionary robotics domains confirm this hypothesis: in both...... domains, such Evolvability Search produces solutions with higher evolvability than those produced with Novelty Search or traditional objective-based search algorithms. Further experiments demonstrate that the higher evolvability produced by Evolvability Search in a training environment also generalizes...

  13. Evolving neural networks for strategic decision-making problems.

    Science.gov (United States)

    Kohl, Nate; Miikkulainen, Risto

    2009-04-01

    Evolution of neural networks, or neuroevolution, has been a successful approach to many low-level control problems such as pole balancing, vehicle control, and collision warning. However, certain types of problems-such as those involving strategic decision-making-have remained difficult for neuroevolution to solve. This paper evaluates the hypothesis that such problems are difficult because they are fractured: The correct action varies discontinuously as the agent moves from state to state. A method for measuring fracture using the concept of function variation is proposed and, based on this concept, two methods for dealing with fracture are examined: neurons with local receptive fields, and refinement based on a cascaded network architecture. Experiments in several benchmark domains are performed to evaluate how different levels of fracture affect the performance of neuroevolution methods, demonstrating that these two modifications improve performance significantly. These results form a promising starting point for expanding neuroevolution to strategic tasks.

  14. Empirical Models of Social Learning in a Large, Evolving Network.

    Directory of Open Access Journals (Sweden)

    Ayşe Başar Bener

    Full Text Available This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1 attraction homophily causes individuals to form ties on the basis of attribute similarity, 2 aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3 social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  15. Co-evolution of the brand effect and competitiveness in evolving networks

    International Nuclear Information System (INIS)

    Guo Jin-Li

    2014-01-01

    The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes' properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model. (general)

  16. Stochastic Geometry Analysis of Ultra Dense Network and TRSC Green Communication Strategy

    Directory of Open Access Journals (Sweden)

    Guoqiang Wang

    2017-12-01

    Full Text Available In recent years, with the rapid development of wireless communication, the traditional cellular with isomorphic and regular structure has been unable to meet the increasing number of users and business needs involving data of big volume. The trend is evolving into Ultra Dense Network (UDN architecture which is covered by cellular of irregular complex structure. In UDN, the spatial distribution of the base station plays an important role in the interference and performance evaluation of the whole cellular network, and the concept of green communication has also been put on agenda. In this paper, stochastic geometry theory is used to model UDN and to analyze the key performance of interference and wireless network. Moreover, a green communication strategy called TRSC is proposed, which is aimed at saving energy and reducing the signal interference among cells to a certain extent.

  17. Whole-genome sequencing of a laboratory-evolved yeast strain

    Directory of Open Access Journals (Sweden)

    Dunham Maitreya J

    2010-02-01

    Full Text Available Abstract Background Experimental evolution of microbial populations provides a unique opportunity to study evolutionary adaptation in response to controlled selective pressures. However, until recently it has been difficult to identify the precise genetic changes underlying adaptation at a genome-wide scale. New DNA sequencing technologies now allow the genome of parental and evolved strains of microorganisms to be rapidly determined. Results We sequenced >93.5% of the genome of a laboratory-evolved strain of the yeast Saccharomyces cerevisiae and its ancestor at >28× depth. Both single nucleotide polymorphisms and copy number amplifications were found, with specific gains over array-based methodologies previously used to analyze these genomes. Applying a segmentation algorithm to quantify structural changes, we determined the approximate genomic boundaries of a 5× gene amplification. These boundaries guided the recovery of breakpoint sequences, which provide insights into the nature of a complex genomic rearrangement. Conclusions This study suggests that whole-genome sequencing can provide a rapid approach to uncover the genetic basis of evolutionary adaptations, with further applications in the study of laboratory selections and mutagenesis screens. In addition, we show how single-end, short read sequencing data can provide detailed information about structural rearrangements, and generate predictions about the genomic features and processes that underlie genome plasticity.

  18. Rapid response learning of brand logo priming: Evidence that brand priming is not dominated by rapid response learning.

    Science.gov (United States)

    Boehm, Stephan G; Smith, Ciaran; Muench, Niklas; Noble, Kirsty; Atherton, Catherine

    2017-08-31

    Repetition priming increases the accuracy and speed of responses to repeatedly processed stimuli. Repetition priming can result from two complementary sources: rapid response learning and facilitation within perceptual and conceptual networks. In conceptual classification tasks, rapid response learning dominates priming of object recognition, but it does not dominate priming of person recognition. This suggests that the relative engagement of network facilitation and rapid response learning depends on the stimulus domain. Here, we addressed the importance of the stimulus domain for rapid response learning by investigating priming in another domain, brands. In three experiments, participants performed conceptual decisions for brand logos. Strong priming was present, but it was not dominated by rapid response learning. These findings add further support to the importance of the stimulus domain for the relative importance of network facilitation and rapid response learning, and they indicate that brand priming is more similar to person recognition priming than object recognition priming, perhaps because priming of both brands and persons requires individuation.

  19. Evolution characteristics of the network core in the Facebook.

    Directory of Open Access Journals (Sweden)

    Jian-Guo Liu

    Full Text Available Statistical properties of the static networks have been extensively studied. However, online social networks are evolving dynamically, understanding the evolving characteristics of the core is one of major concerns in online social networks. In this paper, we empirically investigate the evolving characteristics of the Facebook core. Firstly, we separate the Facebook-link(FL and Facebook-wall(FW datasets into 28 snapshots in terms of timestamps. By employing the k-core decomposition method to identify the core of each snapshot, we find that the core sizes of the FL and FW networks approximately contain about 672 and 373 nodes regardless of the exponential growth of the network sizes. Secondly, we analyze evolving topological properties of the core, including the k-core value, assortative coefficient, clustering coefficient and the average shortest path length. Empirical results show that nodes in the core are getting more interconnected in the evolving process. Thirdly, we investigate the life span of nodes belonging to the core. More than 50% nodes stay in the core for more than one year, and 19% nodes always stay in the core from the first snapshot. Finally, we analyze the connections between the core and the whole network, and find that nodes belonging to the core prefer to connect nodes with high k-core values, rather than the high degrees ones. This work could provide new insights into the online social network analysis.

  20. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  1. Rapidly evolving zona pellucida domain proteins are a major component of the vitelline envelope of abalone eggs

    Science.gov (United States)

    Aagaard, Jan E.; Yi, Xianhua; MacCoss, Michael J.; Swanson, Willie J.

    2006-01-01

    Proteins harboring a zona pellucida (ZP) domain are prominent components of vertebrate egg coats. Although less well characterized, the egg coat of the non-vertebrate marine gastropod abalone (Haliotis spp.) is also known to contain a ZP domain protein, raising the possibility of a common molecular basis of metazoan egg coat structures. Egg coat proteins from vertebrate as well as non-vertebrate taxa have been shown to evolve under positive selection. Studied most extensively in the abalone system, coevolution between adaptively diverging egg coat and sperm proteins may contribute to the rapid development of reproductive isolation. Thus, identifying the pattern of evolution among egg coat proteins is important in understanding the role these genes may play in the speciation process. The purpose of the present study is to characterize the constituent proteins of the egg coat [vitelline envelope (VE)] of abalone eggs and to provide preliminary evidence regarding how selection has acted on VE proteins during abalone evolution. A proteomic approach is used to match tandem mass spectra of peptides from purified VE proteins with abalone ovary EST sequences, identifying 9 of 10 ZP domain proteins as components of the VE. Maximum likelihood models of codon evolution suggest positive selection has acted among a subset of amino acids for 6 of these genes. This work provides further evidence of the prominence of ZP proteins as constituents of the egg coat, as well as the prominent role of positive selection in diversification of these reproductive proteins. PMID:17085584

  2. Interconnection Structures, Management and Routing Challenges in Cloud-Service Data Center Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Ahmad Nahar Quttoum

    2018-01-01

    Full Text Available Today’s data center networks employ expensive networking equipments in associated structures that were not designed to meet the increasing requirements of the current large-scale data center services. Limitations that vary between reliability, resource utilization, and high costs are challenging. The era of cloud computing represents a promise to enable large-scale data centers. Computing platforms of such cloud service data centers consist of large number of commodity low-price servers that, with a theme of virtualization on top, can meet the performance of the expensive high-level servers at only a fraction of the price. Recently, the research in data center networks started to evolve rapidly. This opened the path for addressing many of its design and management challenges, these like scalability, reliability, bandwidth capacities, virtual machines’ migration, and cost. Bandwidth resource fragmentation limits the network agility, and leads to low utilization rates, not only for the bandwidth resources, but also for the servers that run the applications. With Traffic Engineering methods, managers of such networks can adapt for rapid changes in the network traffic among their servers, this can help to provide better resource utilization and lower costs. The market is going through exciting changes, and the need to run demanding-scale services drives the work toward cloud networks. These networks that are enabled by the notation of autonomic management, and the availability of commodity low-price network equipments. This work provides the readers with a survey that presents the management challenges, design and operational constraints of the cloud-service data center networks

  3. Sensationalistic journalism and tales of snakebite: are rattlesnakes rapidly evolving more toxic venom?

    Science.gov (United States)

    Hayes, William K; Mackessy, Stephen P

    2010-03-01

    Recent reports in the lay press have suggested that bites by rattlesnakes in the last several years have been more severe than those in the past. The explanation, often citing physicians, is that rattlesnakes are evolving more toxic venom, perhaps in response to anthropogenic causes. We suggest that other explanations are more parsimonious, including factors dependent on the snake and factors associated with the bite victim's response to envenomation. Although bites could become more severe from an increased proportion of bites from larger or more provoked snakes (ie, more venom injected), the venom itself evolves much too slowly to explain the severe symptoms occasionally seen. Increased snakebite severity could also result from a number of demographic changes in the victim profile, including age and body size, behavior toward the snake (provocation), anatomical site of bite, clothing, and general health including asthma prevalence and sensitivity to foreign antigens. Clinical management of bites also changes perpetually, rendering comparisons of snakebite severity over time tenuous. Clearly, careful study taking into consideration many factors will be essential to document temporal changes in snakebite severity or venom toxicity. Presently, no published evidence for these changes exists. The sensationalistic coverage of these atypical bites and accompanying speculation is highly misleading and can produce many detrimental results, such as inappropriate fear of the outdoors and snakes, and distraction from proven snakebite management needs, including a consistent supply of antivenom, adequate health care, and training. We urge healthcare providers to avoid propagating misinformation about snakes and snakebites. Copyright (c) 2010 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

  4. Network Enabled - Unresolved Residual Analysis and Learning (NEURAL)

    Science.gov (United States)

    Temple, D.; Poole, M.; Camp, M.

    Since the advent of modern computational capacity, machine learning algorithms and techniques have served as a method through which to solve numerous challenging problems. However, for machine learning methods to be effective and robust, sufficient data sets must be available; specifically, in the space domain, these are generally difficult to acquire. Rapidly evolving commercial space-situational awareness companies boast the capability to collect hundreds of thousands nightly observations of resident space objects (RSOs) using a ground-based optical sensor network. This provides the ability to maintain custody of and characterize thousands of objects persistently. With this information available, novel deep learning techniques can be implemented. The technique discussed in this paper utilizes deep learning to make distinctions between nightly data collects with and without maneuvers. Implementation of these techniques will allow the data collected from optical ground-based networks to enable well informed and timely the space domain decision making.

  5. Role of norepinephrine in the regulation of rapid eye movement sleep

    Indian Academy of Sciences (India)

    Sleep and wakefulness are instinctive behaviours that are present across the animal species. Rapid eye movement (REM) sleep is a unique biological phenomenon expressed during sleep. It evolved about 300 million years ago and is noticed in the more evolved animal species. Although it has been objectively identified ...

  6. Neural network and parton two fireball model for pseudo-rapidity distribution in proton-proton collision

    International Nuclear Information System (INIS)

    El-Bakry, M.Y.

    2000-01-01

    Pseudo-Rapidity distribution of created pions from proton-proton (p-p) interaction has been studied in the framework of artificial neural network (ANN) and the parton two fireball model (PTFM). The predicted distributions from the ANN based model and the parton two fireball model is compared with the corresponding experimental results. The ANN model has proved better matching for experimental data specially at high energies where the conventional two fireball model representation deteriorates

  7. Rapid evolution of a marsh tidal creek network in response to sea level rise.

    Science.gov (United States)

    Hughes, Z. J.; Fitzgerald, D. M.; Mahadevan, A.; Wilson, C. A.; Pennings, S. C.

    2008-12-01

    In the Santee River Delta (SRD), South Carolina, tidal creeks are extending rapidly onto the marsh platform. A time-series of aerial photographs establishes that these channels were initiated in the 1950's and are headward eroding at a rate of 1.9 m /yr. Short-term trends in sea level show an average relative sea level rise (RSLR) of 4.6 mm/yr over a 20-year tide gauge record from nearby Winyah Bay and Charleston Harbor (1975-1995). Longer-term (85-year) records in Charleston suggest a rate of 3.2 mm/yr. RSLR in the SRD is likely even higher as sediment cores reveal that the marsh is predominantly composed of fine-grained sediment, making it highly susceptible to compaction and subsidence. Furthermore, loss in elevation will have been exacerbated by the decrease in sediment supply due to the damming of the Santee River in 1939. The rapid rate of headward erosion indicates that the marsh platform is in disequilibrium; unable to keep pace with RSLR through accretionary processes and responding to an increased volume and frequency of inundation through the extension of the drainage network. The observed tidal creeks show no sinuosity and a distinctive morphology associated with their young age and biological mediation during their evolution. Feedbacks between tidal flow, vegetation and infauna play a strong role in the morphological development of the creeks. The creek heads are characterized by a region denuded of vegetation, the edges of which are densely populated and burrowed by Uca Pugnax (fiddler crab). Crab burrowing destabilizes sediment, destroys rooting and impacts drainage. Measured infiltration rates are three orders of magnitude higher in the burrowed regions than in a control area (1000 ml/min and 0.6 ml/min respectively). Infiltration of oxygenated water enhances decomposition of organic matter and root biomass is reduced within the creek head (marsh=4.3 kg/m3, head=0.6 kg/m3). These processes lead to the removal and collapse of the soils, producing

  8. A platform for rapid prototyping of synthetic gene networks in mammalian cells

    Science.gov (United States)

    Duportet, Xavier; Wroblewska, Liliana; Guye, Patrick; Li, Yinqing; Eyquem, Justin; Rieders, Julianne; Rimchala, Tharathorn; Batt, Gregory; Weiss, Ron

    2014-01-01

    Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines. PMID:25378321

  9. Analysis of expression in the Anopheles gambiae developing testes reveals rapidly evolving lineage-specific genes in mosquitoes

    Directory of Open Access Journals (Sweden)

    Krzywinski Jaroslaw

    2009-07-01

    Full Text Available Abstract Background Male mosquitoes do not feed on blood and are not involved in delivery of pathogens to humans. Consequently, they are seldom the subjects of research, which results in a very poor understanding of their biology. To gain insights into male developmental processes we sought to identify genes transcribed exclusively in the reproductive tissues of male Anopheles gambiae pupae. Results Using a cDNA subtraction strategy, five male-specifically or highly male-biased expressed genes were isolated, four of which remain unannotated in the An. gambiae genome. Spatial and temporal expression patterns suggest that each of these genes is involved in the mid-late stages of spermatogenesis. Their sequences are rapidly evolving; however, two genes possess clear homologs in a wide range of taxa and one of these probably acts in a sperm motility control mechanism conserved in many organisms, including humans. The other three genes have no match to sequences from non-mosquito taxa, thus can be regarded as orphans. RNA in situ hybridization demonstrated that one of the orphans is transcribed in spermatids, which suggests its involvement in sperm maturation. Two other orphans have unknown functions. Expression analysis of orthologs of all five genes indicated that male-biased transcription was not conserved in the majority of cases in Aedes and Culex. Conclusion Discovery of testis-expressed orphan genes in mosquitoes opens new prospects for the development of innovative control methods. The orphan encoded proteins may represent unique targets of selective anti-mosquito sterilizing agents that will not affect non-target organisms.

  10. Analysis of expression in the Anopheles gambiae developing testes reveals rapidly evolving lineage-specific genes in mosquitoes.

    Science.gov (United States)

    Krzywinska, Elzbieta; Krzywinski, Jaroslaw

    2009-07-06

    Male mosquitoes do not feed on blood and are not involved in delivery of pathogens to humans. Consequently, they are seldom the subjects of research, which results in a very poor understanding of their biology. To gain insights into male developmental processes we sought to identify genes transcribed exclusively in the reproductive tissues of male Anopheles gambiae pupae. Using a cDNA subtraction strategy, five male-specifically or highly male-biased expressed genes were isolated, four of which remain unannotated in the An. gambiae genome. Spatial and temporal expression patterns suggest that each of these genes is involved in the mid-late stages of spermatogenesis. Their sequences are rapidly evolving; however, two genes possess clear homologs in a wide range of taxa and one of these probably acts in a sperm motility control mechanism conserved in many organisms, including humans. The other three genes have no match to sequences from non-mosquito taxa, thus can be regarded as orphans. RNA in situ hybridization demonstrated that one of the orphans is transcribed in spermatids, which suggests its involvement in sperm maturation. Two other orphans have unknown functions. Expression analysis of orthologs of all five genes indicated that male-biased transcription was not conserved in the majority of cases in Aedes and Culex. Discovery of testis-expressed orphan genes in mosquitoes opens new prospects for the development of innovative control methods. The orphan encoded proteins may represent unique targets of selective anti-mosquito sterilizing agents that will not affect non-target organisms.

  11. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    Science.gov (United States)

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-04-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  12. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    Directory of Open Access Journals (Sweden)

    Kai Olav Ellefsen

    2015-04-01

    Full Text Available A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand. To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1 that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2 that one benefit of the modularity ubiquitous in the brains of natural animals

  13. Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills

    Science.gov (United States)

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-01-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  14. Regional and inter–regional effects in evolving climate network

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Vejmelka, Martin; Donner, R.; Marwan, N.; Kurths, J.; Paluš, Milan

    2014-01-01

    Roč. 16, - (2014), EGU2014-13557 ISSN 1607-7962. [EGU General Assembly /11./. 27.04.2014-02.05.2014, Vienna] Institutional support: RVO:67985807 Keywords : causality * climate * nonlinearity * transfer entropy * network * stability Subject RIV: BB - Applied Statistics, Operational Research

  15. Dynamic synchronization of a time-evolving optical network of chaotic oscillators.

    Science.gov (United States)

    Cohen, Adam B; Ravoori, Bhargava; Sorrentino, Francesco; Murphy, Thomas E; Ott, Edward; Roy, Rajarshi

    2010-12-01

    We present and experimentally demonstrate a technique for achieving and maintaining a global state of identical synchrony of an arbitrary network of chaotic oscillators even when the coupling strengths are unknown and time-varying. At each node an adaptive synchronization algorithm dynamically estimates the current strength of the net coupling signal to that node. We experimentally demonstrate this scheme in a network of three bidirectionally coupled chaotic optoelectronic feedback loops and we present numerical simulations showing its application in larger networks. The stability of the synchronous state for arbitrary coupling topologies is analyzed via a master stability function approach. © 2010 American Institute of Physics.

  16. [Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

    Science.gov (United States)

    Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

    2015-10-01

    To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

  17. An oxygen-rich dust disk surrounding an evolved star in the Red Rectangle

    NARCIS (Netherlands)

    Waters, LBFM; Waelkens, C; van Winckel, H; Molster, FJ; Tielens, AGGM; van Loon, JT; Morris, PW; Cami, J; Bouwman, J; de Koter, A; de Jong, T; de Graauw, T

    1998-01-01

    The Red Rectangle(1) is the prototype of a class of carbon-rich reflection nebulae surrounding low-mass stars in the final stages of evolution. The central star of this nebula has ejected most of its layers (during the red-giant phase), which now form the surrounding cloud, and is rapidly evolving

  18. Absence of Rapid Propagation through the Purkinje Network as a Potential Cause of Line Block in the Human Heart with Left Bundle Branch Block.

    Science.gov (United States)

    Okada, Jun-Ichi; Washio, Takumi; Nakagawa, Machiko; Watanabe, Masahiro; Kadooka, Yoshimasa; Kariya, Taro; Yamashita, Hiroshi; Yamada, Yoko; Momomura, Shin-Ichi; Nagai, Ryozo; Hisada, Toshiaki; Sugiura, Seiryo

    2018-01-01

    Background: Cardiac resynchronization therapy is an effective device therapy for heart failure patients with conduction block. However, a problem with this invasive technique is the nearly 30% of non-responders. A number of studies have reported a functional line of block of cardiac excitation propagation in responders. However, this can only be detected using non-contact endocardial mapping. Further, although the line of block is considered a sign of responders to therapy, the mechanism remains unclear. Methods: Herein, we created two patient-specific heart models with conduction block and simulated the propagation of excitation based on a cellmodel of electrophysiology. In one model with a relatively narrow QRS width (176 ms), we modeled the Purkinje network using a thin endocardial layer with rapid conduction. To reproduce a wider QRS complex (200 ms) in the second model, we eliminated the Purkinje network, and we simulated the endocardial mapping by solving the inverse problem according to the actual mapping system. Results: We successfully observed the line of block using non-contact mapping in the model without the rapid propagation of excitation through the Purkinje network, although the excitation in the wall propagated smoothly. This model of slow conduction also reproduced the characteristic properties of the line of block, including dense isochronal lines and fractionated local electrocardiograms. Further, simulation of ventricular pacing from the lateral wall shifted the location of the line of block. By contrast, in the model with the Purkinje network, propagation of excitation in the endocardial map faithfully followed the actual propagation in the wall, without showing the line of block. Finally, switching the mode of propagation between the two models completely reversed these findings. Conclusions: Our simulation data suggest that the absence of rapid propagation of excitation through the Purkinje network is the major cause of the functional line

  19. Mobile networks architecture

    CERN Document Server

    Perez, Andre

    2013-01-01

    This book explains the evolutions of architecture for mobiles and summarizes the different technologies:- 2G: the GSM (Global System for Mobile) network, the GPRS (General Packet Radio Service) network and the EDGE (Enhanced Data for Global Evolution) evolution;- 3G: the UMTS (Universal Mobile Telecommunications System) network and the HSPA (High Speed Packet Access) evolutions:- HSDPA (High Speed Downlink Packet Access),- HSUPA (High Speed Uplink Packet Access),- HSPA+;- 4G: the EPS (Evolved Packet System) network.The telephone service and data transmission are the

  20. Invasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species

    Science.gov (United States)

    Simpson, Annie; Jarnevich, Catherine S.; Madsen, John; Westbrooks, Randy G.; Fournier, Christine; Mehrhoff, Les; Browne, Michael; Graham, Jim; Sellers, Elizabeth A.

    2009-01-01

    Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MidSouth) generate occurrence data at local and regional levels within the United States, which are shared through the US National Institute of Invasive Species Science. The Inter-American Biodiversity Information Network's Invasives Information Network (I3N), facilitates cooperation on sharing invasive species occurrence data throughout the Western Hemisphere. The I3N and other national and regional networks expose their data globally via the Global Invasive Species Information Network (GISIN). International and interdisciplinary cooperation on data sharing strengthens cooperation on strategies and responses to invasions. However, limitations to effective collaboration among invasive species networks leading to successful early detection and rapid response to invasive species include: lack of interoperability; data accessibility; funding; and technical expertise. This paper proposes various solutions to these obstacles at different geographic levels and briefly describes success stories from the invasive species information networks mentioned above. Using biological informatics to facilitate global information sharing is especially critical in invasive species science, as research has shown that one of the best indicators of the invasiveness of a species is whether it has been invasive elsewhere. Data must also be shared across disciplines because natural history information (e.g. diet, predators, habitat requirements, etc.) about a species in its native range is vital for effective prevention, detection, and rapid response to an invasion. Finally, it has been our

  1. The US-CMS Tier-1 Center Network Evolving toward 100Gbps

    International Nuclear Information System (INIS)

    Bobyshev, A; DeMar, P

    2011-01-01

    Fermilab hosts the US Tier-1 Center for the LHC's Compact Muon Collider (CMS) experiment. The Tier-1s are the central points for the processing and movement of LHC data. They sink raw data from the Tier-0 at CERN, process and store it locally, and then distribute the processed data to Tier-2s for simulation studies and analysis. The Fermilab Tier-1 Center is the largest of the CMS Tier-1s, accounting for roughly 35% of the experiment's Tier-1 computing and storage capacity. Providing capacious, resilient network services, both in terms of local network infrastructure and off-site data movement capabilities, presents significant challenges. This article will describe the current architecture, status, and near term plans for network support of the US-CMS Tier-1 facility.

  2. Incremental Frequent Subgraph Mining on Large Evolving Graphs

    KAUST Repository

    Abdelhamid, Ehab

    2017-08-22

    Frequent subgraph mining is a core graph operation used in many domains, such as graph data management and knowledge exploration, bioinformatics and security. Most existing techniques target static graphs. However, modern applications, such as social networks, utilize large evolving graphs. Mining these graphs using existing techniques is infeasible, due to the high computational cost. In this paper, we propose IncGM+, a fast incremental approach for continuous frequent subgraph mining problem on a single large evolving graph. We adapt the notion of “fringe” to the graph context, that is the set of subgraphs on the border between frequent and infrequent subgraphs. IncGM+ maintains fringe subgraphs and exploits them to prune the search space. To boost the efficiency, we propose an efficient index structure to maintain selected embeddings with minimal memory overhead. These embeddings are utilized to avoid redundant expensive subgraph isomorphism operations. Moreover, the proposed system supports batch updates. Using large real-world graphs, we experimentally verify that IncGM+ outperforms existing methods by up to three orders of magnitude, scales to much larger graphs and consumes less memory.

  3. Evolving cell models for systems and synthetic biology.

    Science.gov (United States)

    Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

    2010-03-01

    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

  4. Energy Efficient Evolution of Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Mogensen, Preben

    2011-01-01

    options for how to evolve their networks, allowing them to carry the expected increase in traffic. The best solution is generally selected based on two main criteria, performance and cost. However, pushed by a variety of environmental and energy challenges, MNOs are now also showing interest...... in understanding the impact that different options can have on the energy consumption of their networks. This paper investigates the possible energy gains of evolving a mobile network through a joint pico deployment and macro upgrade solution over a period of 8 years. Besides the network energy consumption, energy...... efficiency in Mbps/kWh is also analyzed. Furthermore, a cost analysis is carried out, to give a more complete picture of the different options being considered. Focusing on the last year of the evolution analysis, results show that deploying more pico sites reduces the energy consumption of the network...

  5. Motif formation and industry specific topologies in the Japanese business firm network

    Science.gov (United States)

    Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako

    2017-05-01

    Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

  6. Biomimetic molecular design tools that learn, evolve, and adapt

    Science.gov (United States)

    2017-01-01

    A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

  7. Biomimetic molecular design tools that learn, evolve, and adapt

    Directory of Open Access Journals (Sweden)

    David A Winkler

    2017-06-01

    Full Text Available A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

  8. Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits.

    Science.gov (United States)

    Milano, Nicola; Nolfi, Stefano

    2016-01-01

    We demonstrate how the need to cope with operational faults enables evolving circuits to find more fit solutions. The analysis of the results obtained in different experimental conditions indicates that, in absence of faults, evolution tends to select circuits that are small and have low phenotypic variability and evolvability. The need to face operation faults, instead, drives evolution toward the selection of larger circuits that are truly robust with respect to genetic variations and that have a greater level of phenotypic variability and evolvability. Overall our results indicate that the need to cope with operation faults leads to the selection of circuits that have a greater probability to generate better circuits as a result of genetic variation with respect to a control condition in which circuits are not subjected to faults.

  9. Networks in ATLAS

    Science.gov (United States)

    McKee, Shawn; ATLAS Collaboration

    2017-10-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

  10. Rapidly rotating single late-type giants: New FK Comae stars?

    Science.gov (United States)

    Fekel, Francis C.

    1986-01-01

    A group of rapidly rotating single late-type giants was found from surveys of chromospherically active stars. These stars have V sin I's ranging from 6 to 46 km/sec, modest ultraviolet emission line fluxes, and strong H alpha absorption lines. Although certainly chromospherically active, their characteristics are much less extreme than those of FK Com and one or two other similar systems. One possible explanation for the newly identified systems is that they have evolved from stars similar to FK Com. The chromospheric activity and rotation of single giant stars like FK Com would be expected to decrease with time as they do in single dwarfs. Alternatively, this newly identified group may have evolved from single rapidly rotating A, or early F stars.

  11. Information filtering in evolving online networks

    Science.gov (United States)

    Chen, Bo-Lun; Li, Fen-Fen; Zhang, Yong-Jun; Ma, Jia-Lin

    2018-02-01

    Recommender systems use the records of users' activities and profiles of both users and products to predict users' preferences in the future. Considerable works towards recommendation algorithms have been published to solve the problems such as accuracy, diversity, congestion, cold-start, novelty, coverage and so on. However, most of these research did not consider the temporal effects of the information included in the users' historical data. For example, the segmentation of the training set and test set was completely random, which was entirely different from the real scenario in recommender systems. More seriously, all the objects are treated as the same, regardless of the new, the popular or obsoleted products, so do the users. These data processing methods always lose useful information and mislead the understanding of the system's state. In this paper, we detailed analyzed the difference of the network structure between the traditional random division method and the temporal division method on two benchmark data sets, Netflix and MovieLens. Then three classical recommendation algorithms, Global Ranking method, Collaborative Filtering and Mass Diffusion method, were employed. The results show that all these algorithms became worse in all four key indicators, ranking score, precision, popularity and diversity, in the temporal scenario. Finally, we design a new recommendation algorithm based on both users' and objects' first appearance time in the system. Experimental results showed that the new algorithm can greatly improve the accuracy and other metrics.

  12. Urban MEMS based seismic network for post-earthquakes rapid disaster assessment

    Science.gov (United States)

    D'Alessandro, Antonino; Luzio, Dario; D'Anna, Giuseppe

    2014-05-01

    Life losses following disastrous earthquake depends mainly by the building vulnerability, intensity of shaking and timeliness of rescue operations. In recent decades, the increase in population and industrial density has significantly increased the exposure to earthquakes of urban areas. The potential impact of a strong earthquake on a town center can be reduced by timely and correct actions of the emergency management centers. A real time urban seismic network can drastically reduce casualties immediately following a strong earthquake, by timely providing information about the distribution of the ground shaking level. Emergency management centers, with functions in the immediate post-earthquake period, could be use this information to allocate and prioritize resources to minimize loss of human life. However, due to the high charges of the seismological instrumentation, the realization of an urban seismic network, which may allow reducing the rate of fatalities, has not been achieved. Recent technological developments in MEMS (Micro Electro-Mechanical Systems) technology could allow today the realization of a high-density urban seismic network for post-earthquakes rapid disaster assessment, suitable for the earthquake effects mitigation. In the 1990s, MEMS accelerometers revolutionized the automotive-airbag system industry and are today widely used in laptops, games controllers and mobile phones. Due to their great commercial successes, the research into and development of MEMS accelerometers are actively pursued around the world. Nowadays, the sensitivity and dynamics of these sensors are such to allow accurate recording of earthquakes with moderate to strong magnitude. Due to their low cost and small size, the MEMS accelerometers may be employed for the realization of high-density seismic networks. The MEMS accelerometers could be installed inside sensitive places (high vulnerability and exposure), such as schools, hospitals, public buildings and places of

  13. Weighted Scaling in Non-growth Random Networks

    International Nuclear Information System (INIS)

    Chen Guang; Yang Xuhua; Xu Xinli

    2012-01-01

    We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in non-growth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its total number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scale-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

  14. Preface: evolving rotifers, evolving science: Proceedings of the XIV International Rotifer Symposium

    Czech Academy of Sciences Publication Activity Database

    Devetter, Miloslav; Fontaneto, D.; Jersabek, Ch.D.; Welch, D.B.M.; May, L.; Walsh, E.J.

    2017-01-01

    Roč. 796, č. 1 (2017), s. 1-6 ISSN 0018-8158 Institutional support: RVO:60077344 Keywords : evolving rotifers * 14th International Rotifer Symposium * evolving science Subject RIV: EG - Zoology OBOR OECD: Zoology Impact factor: 2.056, year: 2016

  15. Link prediction in multiplex online social networks

    Science.gov (United States)

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  16. Emerging subspecialties in neurology: deep brain stimulation and electrical neuro-network modulation.

    Science.gov (United States)

    Hassan, Anhar; Okun, Michael S

    2013-01-29

    Deep brain stimulation (DBS) is a surgical therapy that involves the delivery of an electrical current to one or more brain targets. This technology has been rapidly expanding to address movement, neuropsychiatric, and other disorders. The evolution of DBS has created a niche for neurologists, both in the operating room and in the clinic. Since DBS is not always deep, not always brain, and not always simply stimulation, a more accurate term for this field may be electrical neuro-network modulation (ENM). Fellowships will likely in future years evolve their scope to include other technologies, and other nervous system regions beyond typical DBS therapy.

  17. A Hybrid Communications Network Simulation-Independent Toolkit

    National Research Council Canada - National Science Library

    Dines, David M

    2008-01-01

    .... Evolving a grand design of the enabling network will require a flexible evaluation platform to try and select the right combination of network strategies and protocols in the realms of topology control and routing...

  18. Fermentation performance of engineered and evolved xylose-fermenting Saccharomyces cerevisiae strains

    DEFF Research Database (Denmark)

    Sonderegger, M.; Jeppsson, M.; Larsson, C.

    2004-01-01

    Lignocellulose hydrolysate is an abundant substrate for bioethanol production. The ideal microorganism for such a fermentation process should combine rapid and efficient conversion of the available carbon sources to ethanol with high tolerance to ethanol and to inhibitory components in the hydrol......Lignocellulose hydrolysate is an abundant substrate for bioethanol production. The ideal microorganism for such a fermentation process should combine rapid and efficient conversion of the available carbon sources to ethanol with high tolerance to ethanol and to inhibitory components...... in the hydrolysate. A particular biological problem are the pentoses, which are not naturally metabolized by the main industrial ethanol producer Saccharomyces cerevisiae. Several recombinant, mutated, and evolved xylose fermenting S. cerevisiae strains have been developed recently. We compare here the fermentation...

  19. Sharing network resources

    CERN Document Server

    Parekh, Abhay

    2014-01-01

    Resource Allocation lies at the heart of network control. In the early days of the Internet the scarcest resource was bandwidth, but as the network has evolved to become an essential utility in the lives of billions, the nature of the resource allocation problem has changed. This book attempts to describe the facets of resource allocation that are most relevant to modern networks. It is targeted at graduate students and researchers who have an introductory background in networking and who desire to internalize core concepts before designing new protocols and applications. We start from the fun

  20. Competing edge networks

    Science.gov (United States)

    Parsons, Mark; Grindrod, Peter

    2012-06-01

    We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails.

  1. Network evolution: rewiring and signatures of conservation in signaling.

    Directory of Open Access Journals (Sweden)

    Mark G F Sun

    Full Text Available The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3 domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.

  2. Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks.

    Directory of Open Access Journals (Sweden)

    Jeewoen Shin

    2015-10-01

    Full Text Available Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability--the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. We consider a two-species model of coevolution involving one host and one parasite population. By using two interacting species, key model parameters that determine the fitness landscapes become emergent properties of the model, avoiding the need to impose these parameters externally. In our study, parasites are modeled on species such as cuckoos where mimicry of the host phenotype confers high fitness to the parasite but lower fitness to the host. Here, frequent phenotype changes are favored as each population continually adapts to the other population. Sensitivity evolves at the network level such that point mutations can induce large phenotype changes. Crucially, the sensitive points of the network are broadly distributed throughout the network and continually relocate. Each time sensitive points in the network are mutated, new ones appear to take their place. We have therefore named this phenomenon "whack-a-mole" sensitivity, after a popular fun park game. We predict that this type of sensitivity will evolve under conditions of strong directional selection, an observation that helps interpret existing experimental evidence, for example, during the emergence of bacterial antibiotic resistance.

  3. The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics.

    Science.gov (United States)

    Turcotte, Martin M; Reznick, David N; Hare, J Daniel

    2011-11-01

    Rapid evolution challenges the assumption that evolution is too slow to impact short-term ecological dynamics. This insight motivates the study of 'Eco-Evolutionary Dynamics' or how evolution and ecological processes reciprocally interact on short time scales. We tested how rapid evolution impacts concurrent population dynamics using an aphid (Myzus persicae) and an undomesticated host (Hirschfeldia incana) in replicated wild populations. We manipulated evolvability by creating non-evolving (single clone) and potentially evolving (two-clone) aphid populations that contained genetic variation in intrinsic growth rate. We observed significant evolution in two-clone populations whether or not they were exposed to predators and competitors. Evolving populations grew up to 42% faster and attained up to 67% higher density, compared with non-evolving control populations but only in treatments exposed to competitors and predators. Increased density also correlates with relative fitness of competing clones suggesting a full eco-evolutionary dynamic cycle defined as reciprocal interactions between evolution and density. © 2011 Blackwell Publishing Ltd/CNRS.

  4. RapidIO as a multi-purpose interconnect

    Science.gov (United States)

    Baymani, Simaolhoda; Alexopoulos, Konstantinos; Valat, Sébastien

    2017-10-01

    RapidIO (http://rapidio.org/) technology is a packet-switched high-performance fabric, which has been under active development since 1997. Originally meant to be a front side bus, it developed into a system level interconnect which is today used in all 4G/LTE base stations world wide. RapidIO is often used in embedded systems that require high reliability, low latency and scalability in a heterogeneous environment - features that are highly interesting for several use cases, such as data analytics and data acquisition (DAQ) networks. We will present the results of evaluating RapidIO in a data analytics environment, from setup to benchmark. Specifically, we will share the experience of running ROOT and Hadoop on top of RapidIO. To demonstrate the multi-purpose characteristics of RapidIO, we will also present the results of investigating RapidIO as a technology for high-speed DAQ networks using a generic multi-protocol event-building emulation tool. In addition we will present lessons learned from implementing native ports of CERN applications to RapidIO.

  5. Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks.

    Science.gov (United States)

    Kasabov, Nikola K; Doborjeh, Maryam Gholami; Doborjeh, Zohreh Gholami

    2017-04-01

    This paper introduces a new methodology for dynamic learning, visualization, and classification of functional magnetic resonance imaging (fMRI) as spatiotemporal brain data. The method is based on an evolving spatiotemporal data machine of evolving spiking neural networks (SNNs) exemplified by the NeuCube architecture [1]. The method consists of several steps: mapping spatial coordinates of fMRI data into a 3-D SNN cube (SNNc) that represents a brain template; input data transformation into trains of spikes; deep, unsupervised learning in the 3-D SNNc of spatiotemporal patterns from data; supervised learning in an evolving SNN classifier; parameter optimization; and 3-D visualization and model interpretation. Two benchmark case study problems and data are used to illustrate the proposed methodology-fMRI data collected from subjects when reading affirmative or negative sentences and another one-on reading a sentence or seeing a picture. The learned connections in the SNNc represent dynamic spatiotemporal relationships derived from the fMRI data. They can reveal new information about the brain functions under different conditions. The proposed methodology allows for the first time to analyze dynamic functional and structural connectivity of a learned SNN model from fMRI data. This can be used for a better understanding of brain activities and also for online generation of appropriate neurofeedback to subjects for improved brain functions. For example, in this paper, tracing the 3-D SNN model connectivity enabled us for the first time to capture prominent brain functional pathways evoked in language comprehension. We found stronger spatiotemporal interaction between left dorsolateral prefrontal cortex and left temporal while reading a negated sentence. This observation is obviously distinguishable from the patterns generated by either reading affirmative sentences or seeing pictures. The proposed NeuCube-based methodology offers also a superior classification accuracy

  6. Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

    Energy Technology Data Exchange (ETDEWEB)

    Rossi, R; Gallagher, B; Neville, J; Henderson, K

    2011-11-11

    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 our 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.

  7. On Backbone Structure for a Future Multipurpose Network

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Cuevas, Ruben; Riaz, M. Tahir

    2008-01-01

    Telecommunications are evolving towards the unification of services and infrastructures. This unification must be achieved at the highest hierarchical level for a complete synergy of services. Therefore, one of the requirements is a multipurpose backbone network capable of supporting all the curr......Telecommunications are evolving towards the unification of services and infrastructures. This unification must be achieved at the highest hierarchical level for a complete synergy of services. Therefore, one of the requirements is a multipurpose backbone network capable of supporting all...

  8. Collateral damage: rapid exposure-induced evolution of pesticide resistance leads to increased susceptibility to parasites.

    Science.gov (United States)

    Jansen, Mieke; Stoks, Robby; Coors, Anja; van Doorslaer, Wendy; de Meester, Luc

    2011-09-01

    Although natural populations may evolve resistance to anthropogenic stressors such as pollutants, this evolved resistance may carry costs. Using an experimental evolution approach, we exposed different Daphnia magna populations in outdoor containers to the carbamate pesticide carbaryl and control conditions, and assessed the resulting populations for both their resistance to carbaryl as well as their susceptibility to infection by the widespread bacterial microparasite Pasteuria ramosa. Our results show that carbaryl selection led to rapid evolution of carbaryl resistance with seemingly no cost when assessed in a benign environment. However, carbaryl-resistant populations were more susceptible to parasite infection than control populations. Exposure to both stressors reveals a synergistic effect on sterilization rate by P. ramosa, but this synergism did not evolve under pesticide selection. Assessing costs of rapid adaptive evolution to anthropogenic stress in a semi-natural context may be crucial to avoid too optimistic predictions for the fitness of the evolving populations. © 2011 The Author(s).

  9. Rational design of HIV vaccines and microbicides: report of the EUROPRISE network annual conference 2010

    Directory of Open Access Journals (Sweden)

    Uchtenhagen Hannes

    2011-04-01

    Full Text Available Abstract Novel, exciting intervention strategies to prevent infection with HIV have been tested in the past year, and the field is rapidly evolving. EUROPRISE is a network of excellence sponsored by the European Commission and concerned with a wide range of activities including integrated developmental research on HIV vaccines and microbicides from discovery to early clinical trials. A central and timely theme of the network is the development of the unique concept of co-usage of vaccines and microbicides. This review, prepared by the PhD students of the network captures much of the research ongoing between the partners. The network is in its 5th year and involves over 50 institutions from 13 European countries together with 3 industrial partners; GSK, Novartis and Sanofi-Pasteur. EUROPRISE is involved in 31 separate world-wide trials of Vaccines and Microbicides including 6 in African countries (Tanzania, Mozambique, South Africa, Kenya, Malawi, Rwanda, and is directly supporting clinical trials including MABGEL, a gp140-hsp70 conjugate trial and HIVIS, vaccine trials in Europe and Africa.

  10. Rational design of HIV vaccines and microbicides: report of the EUROPRISE network annual conference 2010.

    Science.gov (United States)

    Brinckmann, Sarah; da Costa, Kelly; van Gils, Marit J; Hallengärd, David; Klein, Katja; Madeira, Luisa; Mainetti, Lara; Palma, Paolo; Raue, Katharina; Reinhart, David; Reudelsterz, Marc; Ruffin, Nicolas; Seifried, Janna; Schäfer, Katrein; Sheik-Khalil, Enas; Sköld, Annette; Uchtenhagen, Hannes; Vabret, Nicolas; Ziglio, Serena; Scarlatti, Gabriella; Shattock, Robin; Wahren, Britta; Gotch, Frances

    2011-04-12

    Novel, exciting intervention strategies to prevent infection with HIV have been tested in the past year, and the field is rapidly evolving. EUROPRISE is a network of excellence sponsored by the European Commission and concerned with a wide range of activities including integrated developmental research on HIV vaccines and microbicides from discovery to early clinical trials. A central and timely theme of the network is the development of the unique concept of co-usage of vaccines and microbicides. This review, prepared by the PhD students of the network captures much of the research ongoing between the partners. The network is in its 5th year and involves over 50 institutions from 13 European countries together with 3 industrial partners; GSK, Novartis and Sanofi-Pasteur. EUROPRISE is involved in 31 separate world-wide trials of Vaccines and Microbicides including 6 in African countries (Tanzania, Mozambique, South Africa, Kenya, Malawi, Rwanda), and is directly supporting clinical trials including MABGEL, a gp140-hsp70 conjugate trial and HIVIS, vaccine trials in Europe and Africa.

  11. Higher rates of sex evolve in spatially heterogeneous environments.

    Science.gov (United States)

    Becks, Lutz; Agrawal, Aneil F

    2010-11-04

    The evolution and maintenance of sexual reproduction has puzzled biologists for decades. Although this field is rich in hypotheses, experimental evidence is scarce. Some important experiments have demonstrated differences in evolutionary rates between sexual and asexual populations; other experiments have documented evolutionary changes in phenomena related to genetic mixing, such as recombination and selfing. However, direct experiments of the evolution of sex within populations are extremely rare (but see ref. 12). Here we use the rotifer, Brachionus calyciflorus, which is capable of both sexual and asexual reproduction, to test recent theory predicting that there is more opportunity for sex to evolve in spatially heterogeneous environments. Replicated experimental populations of rotifers were maintained in homogeneous environments, composed of either high- or low-quality food habitats, or in heterogeneous environments that consisted of a mix of the two habitats. For populations maintained in either type of homogeneous environment, the rate of sex evolves rapidly towards zero. In contrast, higher rates of sex evolve in populations experiencing spatially heterogeneous environments. The data indicate that the higher level of sex observed under heterogeneity is not due to sex being less costly or selection against sex being less efficient; rather sex is sufficiently advantageous in heterogeneous environments to overwhelm its inherent costs. Counter to some alternative theories for the evolution of sex, there is no evidence that genetic drift plays any part in the evolution of sex in these populations.

  12. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

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

  13. Measuring the Accuracy of Simple Evolving Connectionist System with Varying Distance Formulas

    Science.gov (United States)

    Al-Khowarizmi; Sitompul, O. S.; Suherman; Nababan, E. B.

    2017-12-01

    Simple Evolving Connectionist System (SECoS) is a minimal implementation of Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network architecture of the SECoS could be built based on the given input. In this study, the activation value for the SECoS learning process, which is commonly calculated using normalized Hamming distance, is also calculated using normalized Manhattan distance and normalized Euclidean distance in order to compare the smallest error value and best learning rate obtained. The accuracy of measurement resulted by the three distance formulas are calculated using mean absolute percentage error. In the training phase with several parameters, such as sensitivity threshold, error threshold, first learning rate, and second learning rate, it was found that normalized Euclidean distance is more accurate than both normalized Hamming distance and normalized Manhattan distance. In the case of beta fibrinogen gene -455 G/A polymorphism patients used as training data, the highest mean absolute percentage error value is obtained with normalized Manhattan distance compared to normalized Euclidean distance and normalized Hamming distance. However, the differences are very small that it can be concluded that the three distance formulas used in SECoS do not have a significant effect on the accuracy of the training results.

  14. Network Restoration for Next-Generation Communication and Computing Networks

    Directory of Open Access Journals (Sweden)

    B. S. Awoyemi

    2018-01-01

    Full Text Available Network failures are undesirable but inevitable occurrences for most modern communication and computing networks. A good network design must be robust enough to handle sudden failures, maintain traffic flow, and restore failed parts of the network within a permissible time frame, at the lowest cost achievable and with as little extra complexity in the network as possible. Emerging next-generation (xG communication and computing networks such as fifth-generation networks, software-defined networks, and internet-of-things networks have promises of fast speeds, impressive data rates, and remarkable reliability. To achieve these promises, these complex and dynamic xG networks must be built with low failure possibilities, high network restoration capacity, and quick failure recovery capabilities. Hence, improved network restoration models have to be developed and incorporated in their design. In this paper, a comprehensive study on network restoration mechanisms that are being developed for addressing network failures in current and emerging xG networks is carried out. Open-ended problems are identified, while invaluable ideas for better adaptation of network restoration to evolving xG communication and computing paradigms are discussed.

  15. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

  16. Home networking architecture for IPv6

    OpenAIRE

    Arkko, Jari; Weil, Jason; Troan, Ole; Brandt, Anders

    2012-01-01

    This text describes evolving networking technology within increasingly large residential home networks. The goal of this document is to define an architecture for IPv6-based home networking while describing the associated principles, considerations and requirements. The text briefly highlights the specific implications of the introduction of IPv6 for home networking, discusses the elements of the architecture, and suggests how standard IPv6 mechanisms and addressing can be employed in home ne...

  17. Enabling framework for service-oriented collaborative networks

    NARCIS (Netherlands)

    Sargolzaei, M.

    2018-01-01

    In today's economy, collaboration and co-development among organizations has evolved from the traditional format of static supply chains to the dynamic formation of federated organization networks. Networking among business partners has proven to yield lower costs, higher quality, larger

  18. A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Lihui Jiang

    2015-07-01

    Full Text Available Interference alignment (IA is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs when the signal-to-noise ratio (SNR is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.

  19. A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks.

    Science.gov (United States)

    Jiang, Lihui; Wu, Zhilu; Ren, Guanghui; Wang, Gangyi; Zhao, Nan

    2015-07-29

    Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.

  20. Rapid evolution meets invasive species control: The potential for pesticide resistance in sea lamprey

    Science.gov (United States)

    Dunlop, Erin S.; McLaughlin, Robert L.; Adams, Jean V.; Jones, Michael L.; Birceanu, Oana; Christie, Mark R.; Criger, Lori A.; Hinderer, Julia L.M.; Hollingworth, Robert M.; Johnson, Nicholas; Lantz, Stephen R.; Li, Weiming; Miller, James R.; Morrison, Bruce J.; Mota-Sanchez, David; Muir, Andrew M.; Sepulveda, Maria S.; Steeves, Todd B.; Walter, Lisa; Westman, Erin; Wirgin, Isaac; Wilkie, Michael P.

    2018-01-01

    Rapid evolution of pest, pathogen and wildlife populations can have undesirable effects; for example, when insects evolve resistance to pesticides or fishes evolve smaller body size in response to harvest. A destructive invasive species in the Laurentian Great Lakes, the sea lamprey (Petromyzon marinus) has been controlled with the pesticide 3-trifluoromethyl-4-nitrophenol (TFM) since the 1950s. We evaluated the likelihood of sea lamprey evolving resistance to TFM by (1) reviewing sea lamprey life history and control; (2) identifying physiological and behavioural resistance strategies; (3) estimating the strength of selection from TFM; (4) assessing the timeline for evolution; and (5) analyzing historical toxicity data for evidence of resistance. The number of sea lamprey generations exposed to TFM was within the range observed for fish populations where rapid evolution has occurred. Mortality from TFM was estimated as 82-90%, suggesting significant selective pressure. However, 57 years of toxicity data revealed no increase in lethal concentrations of TFM. Vigilance and the development of alternative controls are required to prevent this aquatic invasive species from evolving strategies to evade control.

  1. Carrier ethernet network control plane based on the Next Generation Network

    DEFF Research Database (Denmark)

    Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert

    2008-01-01

    This paper contributes on presenting a step towards the realization of Carrier Ethernet control plane based on the next generation network (NGN). Specifically, transport MPLS (T-MPLS) is taken as the transport technology in Carrier Ethernet. It begins with providing an overview of the evolving...... architecture of the next generation network (NGN). As an essential candidate among the NGN transport technologies, the definition of Carrier Ethernet (CE) is also introduced here. The second part of this paper depicts the contribution on the T-MPLS based Carrier Ethernet network with control plane based on NGN...... at illustrating the improvement of the Carrier Ethernet network with the NGN control plane....

  2. Evolving the Evolving: Territory, Place and Rewilding in the California Delta

    Directory of Open Access Journals (Sweden)

    Brett Milligan

    2017-10-01

    Full Text Available Current planning and legislation in California’s Sacramento-San Joaquin Delta call for the large-scale ecological restoration of aquatic and terrestrial habitats. These ecological mandates have emerged in response to the region’s infrastructural transformation and the Delta’s predominant use as the central logistical hub in the state’s vast water conveyance network. Restoration is an attempt to recover what was externalized by the logic and abstractions of this logistical infrastructure. However, based on findings from our research, which examined how people are using restored and naturalized landscapes in the Delta and how these landscapes are currently planned for, we argue that as mitigatory response, restoration planning continues some of the same spatial abstractions and inequities by failing to account for the Delta as an urbanized, cultural and unique place. In interpreting how these conditions have come to be, we give attention to a pluralistic landscape approach and a coevolutionary reading of planning, policy, science and landscapes to discuss the conservation challenges presented by “Delta as an Evolving Place”. We suggest that for rewilding efforts to be successful in the Delta, a range of proactive, opportunistic, grounded and participatory tactics will be required to shift towards a more socio-ecological approach.

  3. Ageing as a price of cooperation and complexity: self-organization of complex systems causes the gradual deterioration of constituent networks.

    Science.gov (United States)

    Kiss, Huba J M; Mihalik, Agoston; Nánási, Tibor; Ory, Bálint; Spiró, Zoltán; Soti, Csaba; Csermely, Peter

    2009-06-01

    The network concept is increasingly used for the description of complex systems. Here, we summarize key aspects of the evolvability and robustness of the hierarchical network set of macromolecules, cells, organisms and ecosystems. Listing the costs and benefits of cooperation as a necessary behaviour to build this network hierarchy, we outline the major hypothesis of the paper: the emergence of hierarchical complexity needs cooperation leading to the ageing (i.e. gradual deterioration) of the constituent networks. A stable environment develops cooperation leading to over-optimization, and forming an 'always-old' network, which accumulates damage, and dies in an apoptosis-like process. A rapidly changing environment develops competition forming a 'forever-young' network, which may suffer an occasional over-perturbation exhausting system resources, and causing death in a necrosis-like process. Giving a number of examples we demonstrate how cooperation evokes the gradual accumulation of damage typical to ageing. Finally, we show how various forms of cooperation and consequent ageing emerge as key elements in all major steps of evolution from the formation of protocells to the establishment of the globalized, modern human society.

  4. Accelerating networks

    International Nuclear Information System (INIS)

    Smith, David M D; Onnela, Jukka-Pekka; Johnson, Neil F

    2007-01-01

    Evolving out-of-equilibrium networks have been under intense scrutiny recently. In many real-world settings the number of links added per new node is not constant but depends on the time at which the node is introduced in the system. This simple idea gives rise to the concept of accelerating networks, for which we review an existing definition and-after finding it somewhat constrictive-offer a new definition. The new definition provided here views network acceleration as a time dependent property of a given system as opposed to being a property of the specific algorithm applied to grow the network. The definition also covers both unweighted and weighted networks. As time-stamped network data becomes increasingly available, the proposed measures may be easily applied to such empirical datasets. As a simple case study we apply the concepts to study the evolution of three different instances of Wikipedia, namely, those in English, German, and Japanese, and find that the networks undergo different acceleration regimes in their evolution

  5. Shape-Shifting Droplet Networks.

    Science.gov (United States)

    Zhang, T; Wan, Duanduan; Schwarz, J M; Bowick, M J

    2016-03-11

    We consider a three-dimensional network of aqueous droplets joined by single lipid bilayers to form a cohesive, tissuelike material. The droplets in these networks can be programed to have distinct osmolarities so that osmotic gradients generate internal stresses via local fluid flows to cause the network to change shape. We discover, using molecular dynamics simulations, a reversible folding-unfolding process by adding an osmotic interaction with the surrounding environment which necessarily evolves dynamically as the shape of the network changes. This discovery is the next important step towards osmotic robotics in this system. We also explore analytically and numerically how the networks become faceted via buckling and how quasi-one-dimensional networks become three dimensional.

  6. Towards an Erlang formula for multiclass networks

    NARCIS (Netherlands)

    Jonckheere, M.; Mairesse, J.

    2010-01-01

    Consider a multiclass stochastic network with state-dependent service rates and arrival rates describing bandwidth-sharing mechanisms as well as admission control and/or load balancing schemes. Given Poisson arrival and exponential service requirements, the number of customers in the network evolves

  7. A performance based evaluation of SIP signalling across converged networks

    NARCIS (Netherlands)

    Oredope, A.; Liotta, A.

    2007-01-01

    As wireless networks evolves towards the 3G and 4G architectures the mobile core networks provides a platform for all-IP convergence of mobile and fixed networks allowing for better integration of the Internet and cellular networks, providing better quality of service, charging mechanisms and

  8. Overlay networks toward information networking

    CERN Document Server

    Tarkoma, Sasu

    2010-01-01

    With their ability to solve problems in massive information distribution and processing, while keeping scaling costs low, overlay systems represent a rapidly growing area of R&D with important implications for the evolution of Internet architecture. Inspired by the author's articles on content based routing, Overlay Networks: Toward Information Networking provides a complete introduction to overlay networks. Examining what they are and what kind of structures they require, the text covers the key structures, protocols, and algorithms used in overlay networks. It reviews the current state of th

  9. Radiology online: information, education, and networking--a summary of the 2012 Intersociety Committee Summer Conference.

    Science.gov (United States)

    Dodd, Gerald D; Naeger, David M

    2013-05-01

    The "new online" (Web 2.0) world is evolving rapidly, and the digital information, education, and networking resources available to radiologists have exploded over the past 2 decades. The 2012 Intersociety Committee Summer Conference attendees explored the online resources that have been produced by societies, universities, and commercial entities. Specific attention was given to identifying the best products and packaging them in tablet computers for use by residents and practicing radiologists. The key functions of social networking websites and the possible roles they can play in radiology were explored as well. It was the consensus of the attendees that radiologic digital resources and portable electronic devices have matured to the point that they should become an integral part of our educational programs and clinical practice. Copyright © 2013 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  10. Rapid serial visual presentation design for cognition

    CERN Document Server

    Spence, Robert

    2013-01-01

    A powerful new image presentation technique has evolved over the last twenty years, and its value demonstrated through its support of many and varied common tasks. Conceptually, Rapid Serial Visual Presentation (RSVP) is basically simple, exemplified in the physical world by the rapid riffling of the pages of a book in order to locate a known image. Advances in computation and graphics processing allow RSVP to be applied flexibly and effectively to a huge variety of common tasks such as window shopping, video fast-forward and rewind, TV channel selection and product browsing. At its heart is a

  11. A rapid method for assessing social versus independent interest in health issues: a case study of 'bird flu' and 'swine flu'.

    Science.gov (United States)

    Bentley, R Alexander; Ormerod, Paul

    2010-08-01

    Effective communication strategies regarding health issues are affected by the way in which the public obtain their knowledge, particularly whether people become interested independently, or through their social networks. This is often investigated through localized ethnography or surveys. In rapidly-evolving situations, however, there may also be a need for swift, case-specific assessment as a guide to initial strategy development. With this aim, we analyze real-time online data, provided by the new 'Google Trends' tool, concerning Internet search frequency for health-related issues. To these data we apply a simple model to characterise the effective degree of social transmission versus decisions made individually. As case examples, we explore two rapidly-evolved issues, namely the world-wide interest in avian influenza, or 'bird flu', in 2005, and in H1N1, or 'swine flu', from late April to early May 2009. The 2005 'bird flu' scare demonstrated almost pure imitation for two months initially, followed by a spike of independent decision that corresponded with an announcement by US president George Bush. For 'swine flu' in 2009, imitation was the more prevalent throughout. Overall, the results show how interest in health scares can spread primarily by social means, and that engaging more independent decisions at the population scale may require a dramatic announcement to push a populace over the 'tipping point'. Copyright 2010 Elsevier Ltd. All rights reserved.

  12. How partnership behaviour evolves in networks : path dependency, social figuration and life events

    NARCIS (Netherlands)

    Romme, A.G.L.; Akkermans, H.A.

    2008-01-01

    Networks have become the dominant life form in many organizational settings. Most studies of relationships in networks focus on the dyadic interaction between two agents. However, work on enactment, sensemaking, path dependency, and social figuration processes (e.g. by Weick and Elias) suggests

  13. Basal metabolic rate can evolve independently of morphological and behavioural traits.

    Science.gov (United States)

    Mathot, K J; Martin, K; Kempenaers, B; Forstmeier, W

    2013-09-01

    Quantitative genetic analyses of basal metabolic rate (BMR) can inform us about the evolvability of the trait by providing estimates of heritability, and also of genetic correlations with other traits that may constrain the ability of BMR to respond to selection. Here, we studied a captive population of zebra finches (Taeniopygia guttata) in which selection lines for male courtship rate have been established. We measure BMR in these lines to see whether selection on male sexual activity would change BMR as a potentially correlated trait. We find that the genetic correlation between courtship rate and BMR is practically zero, indicating that the two traits can evolve independently of each other. Interestingly, we find that the heritability of BMR in our population (h(2)=0.45) is markedly higher than was previously reported for a captive zebra finch population from Norway. A comparison of the two studies shows that additive genetic variance in BMR has been largely depleted in the Norwegian population, especially the genetic variance in BMR that is independent of body mass. In our population, the slope of BMR increase with body mass differs not only between the sexes but also between the six selection lines, which we tentatively attribute to genetic drift and/or founder effects being strong in small populations. Our study therefore highlights two things. First, the evolvability of BMR may be less constrained by genetic correlations and lack of independent genetic variation than previously described. Second, genetic drift in small populations can rapidly lead to different evolvabilities across populations.

  14. Evaluation of Advertising Campaigns on Social Media Networks

    Directory of Open Access Journals (Sweden)

    Jurgita Raudeliūnienė

    2018-03-01

    Full Text Available As the virtual environment is constantly changing, not only users’ informational and knowledge needs but also the means and channels of communication with customers applied by organizations change. There is a noticeable trend to move more and more advertising campaigns to social media networks because of the opportunities they provide to organizations and users, which results in the ever-increasing popularity of social media networks and a number of their users. Such a transition is explained by one of the main objectives organizations have: to inform their customers in an appropriate way and receive feedback on social media networks, which is difficult when traditional advertising channels and means are applied. Since advertising campaigns on social media networks are evolving rapidly, their assessment factors and methods, which receive controversial opinions in both scientific literature and practice, change too. Researchers assess and interpret the factors that influence the effectiveness of advertising campaigns on social media networks differently. Thus, a problem arises: how should we evaluate which approach is more capable of accurately and fully reflecting and conveying reality? In this research, this problem is studied by connecting approaches of different researchers. These approaches are linked to the effectiveness assessment of advertising campaigns on social media network aspects. To achieve the objective of this study, such research methods as analysis of scientific literature, multiple criteria and expert assessment (a structured survey and an interview were applied. During the study, out of 39 primary assessment factors, eight primary factors that influence the effectiveness of advertising campaigns on social media networks were identified: sales, content reach, traffic to website, impressions, frequency, relevance score, leads and audience growth.

  15. Network Understanding of Herb Medicine via Rapid Identification of Ingredient-Target Interactions

    Science.gov (United States)

    Zhang, Hai-Ping; Pan, Jian-Bo; Zhang, Chi; Ji, Nan; Wang, Hao; Ji, Zhi-Liang

    2014-01-01

    Today, herb medicines have become the major source for discovery of novel agents in countermining diseases. However, many of them are largely under-explored in pharmacology due to the limitation of current experimental approaches. Therefore, we proposed a computational framework in this study for network understanding of herb pharmacology via rapid identification of putative ingredient-target interactions in human structural proteome level. A marketing anti-cancer herb medicine in China, Yadanzi (Brucea javanica), was chosen for mechanistic study. Total 7,119 ingredient-target interactions were identified for thirteen Yadanzi active ingredients. Among them, about 29.5% were estimated to have better binding affinity than their corresponding marketing drug-target interactions. Further Bioinformatics analyses suggest that simultaneous manipulation of multiple proteins in the MAPK signaling pathway and the phosphorylation process of anti-apoptosis may largely answer for Yadanzi against non-small cell lung cancers. In summary, our strategy provides an efficient however economic solution for systematic understanding of herbs' power.

  16. Learning and structure of neuronal networks

    Indian Academy of Sciences (India)

    We study the effect of learning dynamics on network topology. Firstly, a network of discrete dynamical systems is considered for this purpose and the coupling strengths are made to evolve according to a temporal learning rule that is based on the paradigm of spike-time-dependent plasticity (STDP). This incorporates ...

  17. Opinion dynamics on an adaptive random network

    Science.gov (United States)

    Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.

    2009-04-01

    We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.

  18. A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas

    OpenAIRE

    Wang, Haohan; Raj, Bhiksha

    2015-01-01

    This report will show the history of deep learning evolves. It will trace back as far as the initial belief of connectionism modelling of brain, and come back to look at its early stage realization: neural networks. With the background of neural network, we will gradually introduce how convolutional neural network, as a representative of deep discriminative models, is developed from neural networks, together with many practical techniques that can help in optimization of neural networks. On t...

  19. Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.

    Science.gov (United States)

    Fogelmark, Karl; Peterson, Carsten; Troein, Carl

    2016-01-01

    Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.

  20. MUPBED - interworking challenges in a multi-domain and multi-technology network environment

    DEFF Research Database (Denmark)

    Foisel, Hans-Martin; Spaeth, Jan; Cavazzoni, Carlo

    2007-01-01

    Todays data transport networks are evolving continuously towards customer oriented and application aware networks. This evolution happens in Europe in a highly diverse network environment, covering multiple network domains, layers, technologies, control and management approaches. In this paper...

  1. Large scale network-centric distributed systems

    CERN Document Server

    Sarbazi-Azad, Hamid

    2014-01-01

    A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

  2. Evolution of competitive ability: an adaptation speed vs. accuracy tradeoff rooted in gene network size.

    Science.gov (United States)

    Malcom, Jacob W

    2011-04-25

    Ecologists have increasingly come to understand that evolutionary change on short time-scales can alter ecological dynamics (and vice-versa), and this idea is being incorporated into community ecology research programs. Previous research has suggested that the size and topology of the gene network underlying a quantitative trait should constrain or facilitate adaptation and thereby alter population dynamics. Here, I consider a scenario in which two species with different genetic architectures compete and evolve in fluctuating environments. An important trade-off emerges between adaptive accuracy and adaptive speed, driven by the size of the gene network underlying the ecologically-critical trait and the rate of environmental change. Smaller, scale-free networks confer a competitive advantage in rapidly-changing environments, but larger networks permit increased adaptive accuracy when environmental change is sufficiently slow to allow a species time to adapt. As the differences in network characteristics increase, the time-to-resolution of competition decreases. These results augment and refine previous conclusions about the ecological implications of the genetic architecture of quantitative traits, emphasizing a role of adaptive accuracy. Along with previous work, in particular that considering the role of gene network connectivity, these results provide a set of expectations for what we may observe as the field of ecological genomics develops.

  3. A rapidly evolving secretome builds and patterns a sea shell

    Directory of Open Access Journals (Sweden)

    Green Kathryn

    2006-11-01

    Full Text Available Abstract Background Instructions to fabricate mineralized structures with distinct nanoscale architectures, such as seashells and coral and vertebrate skeletons, are encoded in the genomes of a wide variety of animals. In mollusks, the mantle is responsible for the extracellular production of the shell, directing the ordered biomineralization of CaCO3 and the deposition of architectural and color patterns. The evolutionary origins of the ability to synthesize calcified structures across various metazoan taxa remain obscure, with only a small number of protein families identified from molluskan shells. The recent sequencing of a wide range of metazoan genomes coupled with the analysis of gene expression in non-model animals has allowed us to investigate the evolution and process of biomineralization in gastropod mollusks. Results Here we show that over 25% of the genes expressed in the mantle of the vetigastropod Haliotis asinina encode secreted proteins, indicating that hundreds of proteins are likely to be contributing to shell fabrication and patterning. Almost 85% of the secretome encodes novel proteins; remarkably, only 19% of these have identifiable homologues in the full genome of the patellogastropod Lottia scutum. The spatial expression profiles of mantle genes that belong to the secretome is restricted to discrete mantle zones, with each zone responsible for the fabrication of one of the structural layers of the shell. Patterned expression of a subset of genes along the length of the mantle is indicative of roles in shell ornamentation. For example, Has-sometsuke maps precisely to pigmentation patterns in the shell, providing the first case of a gene product to be involved in molluskan shell pigmentation. We also describe the expression of two novel genes involved in nacre (mother of pearl deposition. Conclusion The unexpected complexity and evolvability of this secretome and the modular design of the molluskan mantle enables

  4. Formation of a national network for rapid response to device and lead advisories: The Canadian Heart Rhythm Society Device Advisory Committee

    Science.gov (United States)

    Krahn, Andrew D; Simpson, Christopher S; Parkash, Ratika; Yee, Raymond; Champagne, Jean; Healey, Jeffrey S; Cameron, Doug; Thibault, Bernard; Mangat, Iqwal; Tung, Stanley; Sterns, Laurence; Birnie, David H; Exner, Derek V; Sivakumaran, Soori; Davies, Ted; Coutu, Benoit; Crystal, Eugene; Wolfe, Kevin; Verma, Atul; Stephenson, Elizabeth A; Sanatani, Shubhayan; Gow, Robert; Connors, Sean; Paredes, Felix Ayala; Turabian, Mike; Kus, Teresa; Essebag, Vidal; Gardner, Martin

    2009-01-01

    The Canadian Heart Rhythm Society (CHRS) Device Advisory Committee was commissioned to respond to advisories regarding cardiac rhythm device and lead performance on behalf of the CHRS. In the event of an advisory, the Chair uses an e-mail network to disseminate advisory information to Committee members broadly representative of the Canadian device community. A consensus recommendation is prepared by the Committee and made available to all Canadian centres on the CHRS Web site after approval by the CHRS executive. This collaborative approach using an e-mail network has proven very efficient in providing a rapid national response to device advisories. The network is an ideal tool to collect specific data on implanted device system performance and allows for prompt reporting of clinically relevant data to front-line clinicians and patients. PMID:19584969

  5. Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

    Science.gov (United States)

    Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

    2018-05-08

    Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

  6. Rapid identification and classification of Listeria spp. and serotype assignment of Listeria monocytogenes using fourier transform-infrared spectroscopy and artificial neural network analysis

    Science.gov (United States)

    The use of Fourier Transform-Infrared Spectroscopy (FT-IR) in conjunction with Artificial Neural Network software, NeuroDeveloper™ was examined for the rapid identification and classification of Listeria species and serotyping of Listeria monocytogenes. A spectral library was created for 245 strains...

  7. Representative Delay Measurements (RDM: Facing the Challenge of Modern Networks

    Directory of Open Access Journals (Sweden)

    Joachim Fabini

    2015-02-01

    Full Text Available Network access technologies have evolved significantly in the last years. They deploy novel mechanisms like reactive capacity allocation and time-slotted operation to optimize overall network capacity. From a single node's perspective, such optimizations decrease network determinism and measurement repeatability. Evolving application fields like machine to machine (M2M communications or real-time gaming often have strict real-time requirements to operate correctly. Highly accurate delay measurements are necessary to monitor network compliance with application demands or to detect deviations of normal network behavior, which may be caused by network failures, misconfigurations or attacks. This paper analyzes factors that challenge active delay measurements in modern networks. It introduces the Representative Delay Measurement tool (RDM that addresses these factors and proposes solutions that conform to requirements of the recently published RFC7312. Delay measurement results acquired using RDM in live networks confirm that advanced measurement methods can significantly improve the quality of measurement samples by isolating systematic network behavior. The resulting high-quality samples are one prerequisite for accurate statistics that support proper operation of subsequent algorithms and applications.

  8. Finite size effects and symmetry breaking in the evolution of networks of competing Boolean nodes

    International Nuclear Information System (INIS)

    Liu, M; Bassler, K E

    2011-01-01

    Finite size effects on the evolutionary dynamics of Boolean networks are analyzed. In the model considered, Boolean networks evolve via a competition between nodes that punishes those in the majority. Previous studies have found that large networks evolve to a statistical steady state that is both critical and highly canalized, and that the evolution of canalization, which is a form of robustness found in genetic regulatory networks, is associated with a particular symmetry of the evolutionary dynamics. Here, it is found that finite size networks evolve in a fundamentally different way than infinitely large networks do. The symmetry of the evolutionary dynamics of infinitely large networks that selects for canalizing Boolean functions is broken in the evolutionary dynamics of finite size networks. In finite size networks, there is an additional selection for input-inverting Boolean functions that output a value opposite to the majority of input values. The reason for the symmetry breaking in the evolutionary dynamics is found to be due to the need for nodes in finite size networks to behave differently in order to cooperate so that the system collectively performs as efficiently as possible. The results suggest that both finite size effects and symmetry are fundamental for understanding the evolution of real-world complex networks, including genetic regulatory networks.

  9. Undermining and Strengthening Social Networks through Network Modification

    Science.gov (United States)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  10. CERN internal communication is evolving

    CERN Multimedia

    2016-01-01

    CERN news will now be regularly updated on the CERN People page (see here).      Dear readers, All over the world, communication is becoming increasingly instantaneous, with news published in real time on websites and social networks. In order to keep pace with these changes, CERN's internal communication is evolving too. From now on, you will be informed of what’s happening at CERN more often via the “CERN people” page, which will frequently be updated with news. The Bulletin is following this trend too: twice a month, we will compile the most important articles published on the CERN site, with a brand-new layout. You will receive an e-mail every two weeks as soon as this new form of the Bulletin is available. If you have interesting news or stories to share, tell us about them through the form at: https://communications.web.cern.ch/got-story-cern-website​. You can also find out about news from CERN in real time...

  11. Modeling promoter grammars with evolving hidden Markov models

    DEFF Research Database (Denmark)

    Won, Kyoung-Jae; Sandelin, Albin; Marstrand, Troels Torben

    2008-01-01

    MOTIVATION: Describing and modeling biological features of eukaryotic promoters remains an important and challenging problem within computational biology. The promoters of higher eukaryotes in particular display a wide variation in regulatory features, which are difficult to model. Often several...... factors are involved in the regulation of a set of co-regulated genes. If so, promoters can be modeled with connected regulatory features, where the network of connections is characteristic for a particular mode of regulation. RESULTS: With the goal of automatically deciphering such regulatory structures......, we present a method that iteratively evolves an ensemble of regulatory grammars using a hidden Markov Model (HMM) architecture composed of interconnected blocks representing transcription factor binding sites (TFBSs) and background regions of promoter sequences. The ensemble approach reduces the risk...

  12. One Health in social networks and social media.

    Science.gov (United States)

    Mekaru, S R; Brownstein, J S

    2014-08-01

    In the rapidly evolving world of social media, social networks, mobile applications and citizen science, online communities can develop organically and separately from larger or more established organisations. The One Health online community is experiencing expansion from both the bottom up and the top down. In this paper, the authors review social media's strengths and weaknesses, earlier work examining Internet resources for One Health, the current state of One Health in social media (e.g. Facebook, Twitter, YouTube) and online social networking sites (e.g. LinkedIn and ResearchGate), as well as social media in One Health-related citizen science projects. While One Health has a fairly strong presence on websites, its social media presence is more limited and has an uneven geographic distribution. In work following the Stone Mountain Meeting,the One Health Global Network Task Force Report recommended the creation of an online community of practice. Professional social networks as well as the strategic use of social media should be employed in this effort. Finally, One Health-related research projects using volunteers (citizen science) often use social media to enhance their recruitment. Including these researchers in a community of practitioners would take full advantage of their existing social media presence. In conclusion, the interactive nature of social media, combined with increasing global Internet access, provides the One Health community with opportunities to meaningfully expand their community and promote their message.

  13. Link removal for the control of stochastically evolving epidemics over networks: a comparison of approaches.

    Science.gov (United States)

    Enns, Eva A; Brandeau, Margaret L

    2015-04-21

    For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two "preventive" approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two "reactive" approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdös-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdös-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing which

  14. Patterns of the cosmic microwave background from evolving string networks

    International Nuclear Information System (INIS)

    Bouchet, F.R.; Bennett, D.P.; Stebbins, A.

    1988-01-01

    A network of cosmic strings generated in the early Universe may still exist today. As the strings move across the sky, they produce, by gravitational lensing, a characteristic pattern of anisotropies in the temperature of the cosmic microwave background. The observed absence of such anisotropies places constraints on theories in which galaxy formation is seeded by strings, but it is anticipated that the next generation of experiments will detect them. (author)

  15. Network speech systems technology program

    Science.gov (United States)

    Weinstein, C. J.

    1981-09-01

    This report documents work performed during FY 1981 on the DCA-sponsored Network Speech Systems Technology Program. The two areas of work reported are: (1) communication system studies in support of the evolving Defense Switched Network (DSN) and (2) design and implementation of satellite/terrestrial interfaces for the Experimental Integrated Switched Network (EISN). The system studies focus on the development and evaluation of economical and endurable network routing procedures. Satellite/terrestrial interface development includes circuit-switched and packet-switched connections to the experimental wideband satellite network. Efforts in planning and coordination of EISN experiments are reported in detail in a separate EISN Experiment Plan.

  16. Review of Literature on Mentorship Networks in Medicine: Where Are We Now and Where Are We Going?

    Science.gov (United States)

    Mickelson, Jennifer Judith

    Mentorship is imperative in medical training and conceptual frameworks for mentoring continue to evolve. This study is an integrated review of the literature on mentoring networks. A systematic review of the literature on mentoring networks identified 943 articles from multiple databases. 24 relevant articles under went qualitative analysis. An iterative approach was taken to formulate themes, subthemes and codes. Three major themes were identified. The first theme was that group or peer networks meet evolving and dynamic or changing needs through training and career development. A prominent subtheme was identified which was the need for mentees to be the architects or directors of their evolving mentorship networks. The second theme identified was that mentorship networks offered a solution to barriers associated with the dyad model of mentorship. The third theme was the importance of the informality or "voluntary marriages", as distinguished from structured formal programs, to create meaningful mentorship networks. Future directions of study include examining how to empower mentees to facilitate and direct their mentorship networks.

  17. BOOK REVIEW: OPENING SCIENCE, THE EVOLVING GUIDE ...

    Science.gov (United States)

    The way we get our funding, collaborate, do our research, and get the word out has evolved over hundreds of years but we can imagine a more open science world, largely facilitated by the internet. The movement towards this more open way of doing and presenting science is coming, and it is not taking hundreds of years. If you are interested in these trends, and would like to find out more about where this is all headed and what it means to you, consider downloding Opening Science, edited by Sönke Bartling and Sascha Friesike, subtitled The Evolving Guide on How the Internet is Changing Research, Collaboration, and Scholarly Publishing. In 26 chapters by various authors from a range of disciplines the book explores the developing world of open science, starting from the first scientific revolution and bringing us to the next scientific revolution, sometimes referred to as “Science 2.0”. Some of the articles deal with the impact of the changing landscape of how science is done, looking at the impact of open science on Academia, or journal publishing, or medical research. Many of the articles look at the uses, pitfalls, and impact of specific tools, like microblogging (think Twitter), social networking, and reference management. There is lots of discussion and definition of terms you might use or misuse like “altmetrics” and “impact factor”. Science will probably never be completely open, and Twitter will probably never replace the journal article,

  18. Construction of programmable interconnected 3D microfluidic networks

    International Nuclear Information System (INIS)

    Hunziker, Patrick R; Wolf, Marc P; Wang, Xueya; Zhang, Bei; Marsch, Stephan; Salieb-Beugelaar, Georgette B

    2015-01-01

    Microfluidic systems represent a key-enabling platform for novel diagnostic tools for use at the point-of-care in clinical contexts as well as for evolving single cell diagnostics. The design of 3D microfluidic systems is an active field of development, but construction of true interconnected 3D microfluidic networks is still a challenge, in particular when the goal is rapid prototyping, accurate design and flexibility. We report a novel approach for the construction of programmable 3D microfluidic systems consisting of modular 3D template casting of interconnected threads to allow user-programmable flow paths and examine its structural characteristics and its modular function. To overcome problems with thread template casting reported in the literature, low-surface-energy polymer threads were used, that allow solvent-free production. Connected circular channels with excellent roundness and low diameter variability were created. Variable channel termination allowed programming a flow path on-the-fly, thus rendering the resulting 3D microfluidic systems highly customizable even after production. Thus, construction of programmable/reprogrammable fully 3D microfluidic systems by template casting of a network of interconnecting threads is feasible, leads to high-quality and highly reproducible, complex 3D geometries. (paper)

  19. Combating Weapons of Mass Destruction: Models, Complexity, and Algorithms in Complex Dynamic and Evolving Networks

    Science.gov (United States)

    2015-11-01

    Gholamreza, and Ester, Martin. “Modeling the Temporal Dynamics of Social Rating Networks Using Bidirectional Effects of Social Relations and Rating...1.1.2 β-disruptor Problems Besides the homogeneous network model consisting of uniform nodes and bidirectional links, the heterogeneous network model... neural and metabolic networks .” Biological Cybernetics 90 (2004): 311–317. 10.1007/s00422-004-0479-1. URL http://dx.doi.org/10.1007/s00422-004-0479-1 [51

  20. Networks in ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2016-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  1. Networks in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00260714; The ATLAS collaboration

    2017-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  2. Location-aware network operation for cloud radio access network

    KAUST Repository

    Wang, Fanggang; Ruan, Liangzhong; Win, Moe Z.

    2017-01-01

    One of the major challenges in effectively operating a cloud radio access network (C-RAN) is the excessive overhead signaling and computation load that scale rapidly with the size of the network. In this paper, the exploitation of location

  3. Neural networks and their potential application to nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1991-01-01

    A network of artificial neurons, usually called an artificial neural network is a data processing system consisting of a number of highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks exhibit characteristics and capabilities not provided by any other technology. Neural networks may be designed so as to classify an input pattern as one of several predefined types or to create, as needed, categories or classes of system states which can be interpreted by a human operator. Neural networks have the ability to recognize patterns, even when the information comprising these patterns is noisy, sparse, or incomplete. Thus, systems of artificial neural networks show great promise for use in environments in which robust, fault-tolerant pattern recognition is necessary in a real-time mode, and in which the incoming data may be distorted or noisy. The application of neural networks, a rapidly evolving technology used extensively in defense applications, alone or in conjunction with other advanced technologies, to some of the problems of operating nuclear power plants has the potential to enhance the safety, reliability and operability of nuclear power plants. The potential applications of neural networking include, but are not limited to diagnosing specific abnormal conditions, identification of nonlinear dynamics and transients, detection of the change of mode of operation, control of temperature and pressure during start-up, signal validation, plant-wide monitoring using autoassociative neural networks, monitoring of check valves, modeling of the plant thermodynamics, emulation of core reload calculations, analysis of temporal sequences in NRC's ''licensee event reports,'' and monitoring of plant parameters

  4. The topology and dynamics of complex networks

    Science.gov (United States)

    Dezso, Zoltan

    We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.

  5. Robustness and Vulnerability of Networks with Dynamical Dependency Groups.

    Science.gov (United States)

    Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi

    2016-11-28

    The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.

  6. The Role of Functional Interdependencies in Global Operations Networks

    DEFF Research Database (Denmark)

    Slepniov, Dmitrij; Wæhrens, Brian Vejrum

    2011-01-01

    The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gap between these networks means that managing their interfaces in global operations context is becoming strategically...

  7. Vertical Transmission of Social Roles Drives Resilience to Poaching in Elephant Networks.

    Science.gov (United States)

    Goldenberg, Shifra Z; Douglas-Hamilton, Iain; Wittemyer, George

    2016-01-11

    Network resilience to perturbation is fundamental to functionality in systems ranging from synthetic communication networks to evolved social organization [1]. While theoretical work offers insight into causes of network robustness, examination of natural networks can identify evolved mechanisms of resilience and how they are related to the selective pressures driving structure. Female African elephants (Loxodonta africana) exhibit complex social networks with node heterogeneity in which older individuals serve as connectivity hubs [2, 3]. Recent ivory poaching targeting older elephants in a well-studied population has mirrored the targeted removal of highly connected nodes in the theoretical literature that leads to structural collapse [4, 5]. Here we tested the response of this natural network to selective knockouts. We find that the hierarchical network topology characteristic of elephant societies was highly conserved across the 16-year study despite ∼70% turnover in individual composition of the population. At a population level, the oldest available individuals persisted to fill socially central positions in the network. For analyses using known mother-daughter pairs, social positions of daughters during the disrupted period were predicted by those of their mothers in years prior, were unrelated to individual histories of family mortality, and were actively built. As such, daughters replicated the social network roles of their mothers, driving the observed network resilience. Our study provides a rare bridge between network theory and an evolved system, demonstrating social redundancy to be the mechanism by which resilience to perturbation occurred in this socially advanced species. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Natural selection promotes antigenic evolvability

    NARCIS (Netherlands)

    Graves, C.J.; Ros, V.I.D.; Stevenson, B.; Sniegowski, P.D.; Brisson, D.

    2013-01-01

    The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide

  9. Conceptual and methodological biases in network models.

    Science.gov (United States)

    Lamm, Ehud

    2009-10-01

    Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between "program" and "data." The evolutionary significance of the dynamics of trans-generational and interorganism regulatory networks is explored and implications are presented for understanding the evolution of the biological categories development-heredity, plasticity-evolvability, and epigenetic-genetic.

  10. A rapid two step protocol of in vitro propagation of an important ...

    African Journals Online (AJOL)

    chandrakant tiwari

    2013-03-06

    Mar 6, 2013 ... Attempts were made to evolve a rapid in vitro technology ..... Values are given as mean ± standard error (SE) of three replicates; each replicate consisted of 24 .... Seminar on Herbal Conservation, Cultivation, Marketing and.

  11. An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

    Science.gov (United States)

    2012-01-01

    Background Synchronized bursting activity (SBA) is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i) In a network with an excitatory ratio (ER) of 80-90%, its connective ratio (CR) was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii) No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL) motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30%) optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA. PMID:22462685

  12. Scalability analysis of the synchronizability for ring or chain networks with dense clusters

    International Nuclear Information System (INIS)

    Lu, Jun-An; Zhang, Yong; Chen, Juan; Lü, Jinhu

    2014-01-01

    It is well known that most real-world complex networks, such as the Internet and the World Wide Web, are evolving networks. An interesting fundamental question is: how do some important functions or dynamical behaviors of complex networks evolve with increasing network scale? This paper aims at investigating the scalability of the synchronizability for ring or chain networks with dense clusters as the network size increases. We discover some interesting phenomena as follows: (i) the synchronizability of ring or chain networks with clusters decreases with increasing network scale regardless of the inner structures of all communities; (ii) for the same network scale, the network synchronizability decreases more quickly with increasing number of cluster blocks than with increasing number of nodes within the cluster block; (iii) the number of rings or chains has a much more significant influence on the network synchronizability than the size of the rings or chains. Our results indicate that network synchronizability can be maintained with increasing network scale by avoiding ring and chain structures. (paper)

  13. Innovations in scholarly publishing. Evolving trends in research communication in a digital age: examples from the BMJ.

    Science.gov (United States)

    Jain, Anita

    2014-01-01

    As technology and communication evolve rapidly in this digital age, scholarly publishing is also undergoing a makeover to match the diverse needs of researchers and clinicians. The BMJ has been at the forefront of innovating the presentation of research to increase its readabillty and usefulness. This article presents some of recent formats used for research communication at the BMJ.

  14. Disgust: Evolved function and structure

    NARCIS (Netherlands)

    Tybur, J.M.; Lieberman, D.; Kurzban, R.; DeScioli, P.

    2013-01-01

    Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and

  15. APPLICATION OF METHODS OF LOGISTICS AND PROJECT MANAGEMENT FOR THE CONSTRUCTION OF MANAGEMENT MODEL OF BUSINESS PROCESSES IN THE NETWORK

    Directory of Open Access Journals (Sweden)

    Наталія Іванівна ЧУХРАЙ

    2016-02-01

    Full Text Available In terms of the dynamic development of network economy for effective decision-making managers of enterprises should be combined methods of logistics and project management to obtain the positive synergistic effect. It is shown that the basis of objective measures aimed at minimizing transaction costs. Solving this problem is associated with the development of the structural shell of business enterprises, which continue to evolve rapidly. Organization joint coordinated work in the same virtual information field together geographically separated users opens up entirely new possibilities for improving the mechanisms of project management and logistics. It was reviewed the evolution tool of business process and identified key business processes in networks. The analysis of support for business processes in logistics networks contains a list of basic management mechanisms. It was developed the model of economic and mathematical business process management in structural shell business. The semantic content of the objective function is to minimize transaction costs.

  16. Evolvement of Uniformity and Volatility in the Stressed Global Financial Village

    Science.gov (United States)

    Kenett, Dror Y.; Raddant, Matthias; Lux, Thomas; Ben-Jacob, Eshel

    2012-01-01

    Background In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village. Methodology/Principal Findings We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets—U.S., U.K., Germany, Japan, China and India—from January 2000 until December 2010. We found that while the developed “western” markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing “eastern” markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches “identity”—it switches between periods of high meta-correlations with the “western” markets and periods when it behaves more similarly to the “eastern” markets. Conclusions/Significance The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive “financial seismograph” to detect early signs of global financial crises so they can be treated before they develop into worldwide events. PMID:22347444

  17. Assessing the evolving fragility of the global food system

    Science.gov (United States)

    Puma, Michael J.; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

    2015-02-01

    The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18 year study period, we show that the global food system is relatively homogeneous (85% of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90%, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9% (3.8%) for 1992-1996, increasing to 11% (5.7%) for 2005-2009. Over the same intervals, rice losses increase from 8.2% (2.2%) to 14% (5.2%). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

  18. Assessing the evolving fragility of the global food system

    International Nuclear Information System (INIS)

    Puma, Michael J; Bose, Satyajit; Chon, So Young; Cook, Benjamin I

    2015-01-01

    The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992–2009 to analyse the changing properties of the global food system. Over the 18 year study period, we show that the global food system is relatively homogeneous (85% of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90%, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9% (3.8%) for 1992–1996, increasing to 11% (5.7%) for 2005–2009. Over the same intervals, rice losses increase from 8.2% (2.2%) to 14% (5.2%). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity. (letter)

  19. Assessing the Evolving Fragility of the Global Food System

    Science.gov (United States)

    Puma, Michael Joseph; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

    2015-01-01

    The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

  20. ING: INDOOR ROUTING PROTOCOL FOR GREEN HOME NETWORKS

    OpenAIRE

    Kaouthar Sethom; Nozha Al- Ibrahimi; Guy Pujolle

    2011-01-01

    Because of all the innovations in computer communications and digital consumer device technologies,people have had great interest in researching home networking systems. The home is evolving rapidlyinto a smart Mesh networked environment.Moreover, the energy consumption of wireless devices and networks gradually increases to represent asignificant portion of the operational cost, naturally also causing increased equivalent carbonemissions to the environment. Therefore, reducing the energy con...

  1. The thermal dependency of locomotor performance evolves rapidly within an invasive species.

    Science.gov (United States)

    Kosmala, Georgia K; Brown, Gregory P; Christian, Keith A; Hudson, Cameron M; Shine, Richard

    2018-05-01

    Biological invasions can stimulate rapid shifts in organismal performance, via both plasticity and adaptation. We can distinguish between these two proximate mechanisms by rearing offspring from populations under identical conditions and measuring their locomotor abilities in standardized trials. We collected adult cane toads ( Rhinella marina ) from invasive populations that inhabit regions of Australia with different climatic conditions. We bred those toads and raised their offspring under common-garden conditions before testing their locomotor performance. At high (but not low) temperatures, offspring of individuals from a hotter location (northwestern Australia) outperformed offspring of conspecifics from a cooler location (northeastern Australia). This disparity indicates that, within less than 100 years, thermal performance in cane toads has adapted to the novel abiotic challenges that cane toads have encountered during their invasion of tropical Australia.

  2. The structure and resilience of financial market networks.

    Science.gov (United States)

    Peron, Thomas Kaue Dal'Maso; Costa, Luciano da Fontoura; Rodrigues, Francisco A

    2012-03-01

    Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.

  3. The structure and resilience of financial market networks

    Science.gov (United States)

    Kauê Dal'Maso Peron, Thomas; da Fontoura Costa, Luciano; Rodrigues, Francisco A.

    2012-03-01

    Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.

  4. Cognitive Radio Networks for Tactical Wireless Communications

    Science.gov (United States)

    2014-12-01

    exists. Instead, security is an evolving process, as we have seen in the context of WLANs and 2G / 3G networks. New system vulnerabilities continue to...in the network configuration and radio parameters take place due to mobility of platforms, and variation in other users of the RF environment. CRNs...dynamic spectrum access experimentally, and it represents the largest military Mobile Ad hoc Network (MANET) as of today. The WNaN demonstrator has been

  5. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

    Hu Hai-Bo; Chen Jun; Guo Jin-Li

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

  6. Páramo is the world’s fastest evolving and coolest biodiversity hotspot

    Directory of Open Access Journals (Sweden)

    Santiago eMadriñán

    2013-10-01

    Full Text Available Understanding the processes that cause speciation is a key aim of evolutionary biology. Lineages or biomes that exhibit recent and rapid diversification are ideal model systems for determining these processes. Species rich biomes reported to be of relatively recent origin, i.e., since the beginning of the Miocene, include Mediterranean ecosystems such as the California Floristic Province, oceanic islands such as the Hawaiian archipelago and the Neotropical high elevation ecosystem of the Páramos. Páramos constitute grasslands above the forest tree-line (at elevations of c. 2800–4700 m with high species endemism. Organisms that occupy this ecosystem are a likely product of unique adaptations to an extreme environment that evolved during the last three to five million years when the Andes reached an altitude that was capable of sustaining this type of vegetation. We compared net diversification rates of lineages in fast evolving biomes using 73 dated molecular phylogenies. Based on our sample, we demonstrate that average net diversification rates of Páramo plant lineages are faster than those of other reportedly fast evolving hotspots and that the faster evolving lineages are more likely to be found in Páramos than the other hotspots. Páramos therefore represent the ideal model system for studying diversification processes. Most of the speciation events that we observed in the Páramos (144 out of 177 occurred during the Pleistocene possibly due to the effects of species range contraction and expansion that may have resulted from the well-documented climatic changes during that period. Understanding these effects will assist with efforts to determine how future climatic changes will impact plant populations.

  7. Security Issues in Networks with Internet Access

    National Research Council Canada - National Science Library

    Landwehr, Carl E; Goldschlag, David M

    1997-01-01

    .... The principles are illustrated by describing the security issues a hypothetical company faces as the networks that support its operations evolve from strictly private, through a mix of Internet...

  8. Exploring the morphospace of communication efficiency in complex networks.

    Directory of Open Access Journals (Sweden)

    Joaquín Goñi

    Full Text Available Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing", we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion". The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

  9. Network evolution driven by dynamics applied to graph coloring

    International Nuclear Information System (INIS)

    Wu Jian-She; Li Li-Guang; Yu Xin; Jiao Li-Cheng; Wang Xiao-Hua

    2013-01-01

    An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring

  10. Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

    Science.gov (United States)

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

    2017-01-01

    Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

  11. Transhydrogenase promotes the robustness and evolvability of E. coli deficient in NADPH production.

    Directory of Open Access Journals (Sweden)

    Hsin-Hung Chou

    Full Text Available Metabolic networks revolve around few metabolites recognized by diverse enzymes and involved in myriad reactions. Though hub metabolites are considered as stepping stones to facilitate the evolutionary expansion of biochemical pathways, changes in their production or consumption often impair cellular physiology through their system-wide connections. How does metabolism endure perturbations brought immediately by pathway modification and restore hub homeostasis in the long run? To address this question we studied laboratory evolution of pathway-engineered Escherichia coli that underproduces the redox cofactor NADPH on glucose. Literature suggests multiple possibilities to restore NADPH homeostasis. Surprisingly, genetic dissection of isolates from our twelve evolved populations revealed merely two solutions: (1 modulating the expression of membrane-bound transhydrogenase (mTH in every population; (2 simultaneously consuming glucose with acetate, an unfavored byproduct normally excreted during glucose catabolism, in two subpopulations. Notably, mTH displays broad phylogenetic distribution and has also played a predominant role in laboratory evolution of Methylobacterium extorquens deficient in NADPH production. Convergent evolution of two phylogenetically and metabolically distinct species suggests mTH as a conserved buffering mechanism that promotes the robustness and evolvability of metabolism. Moreover, adaptive diversification via evolving dual substrate consumption highlights the flexibility of physiological systems to exploit ecological opportunities.

  12. Transhydrogenase Promotes the Robustness and Evolvability of E. coli Deficient in NADPH Production

    Science.gov (United States)

    Chou, Hsin-Hung; Marx, Christopher J.; Sauer, Uwe

    2015-01-01

    Metabolic networks revolve around few metabolites recognized by diverse enzymes and involved in myriad reactions. Though hub metabolites are considered as stepping stones to facilitate the evolutionary expansion of biochemical pathways, changes in their production or consumption often impair cellular physiology through their system-wide connections. How does metabolism endure perturbations brought immediately by pathway modification and restore hub homeostasis in the long run? To address this question we studied laboratory evolution of pathway-engineered Escherichia coli that underproduces the redox cofactor NADPH on glucose. Literature suggests multiple possibilities to restore NADPH homeostasis. Surprisingly, genetic dissection of isolates from our twelve evolved populations revealed merely two solutions: (1) modulating the expression of membrane-bound transhydrogenase (mTH) in every population; (2) simultaneously consuming glucose with acetate, an unfavored byproduct normally excreted during glucose catabolism, in two subpopulations. Notably, mTH displays broad phylogenetic distribution and has also played a predominant role in laboratory evolution of Methylobacterium extorquens deficient in NADPH production. Convergent evolution of two phylogenetically and metabolically distinct species suggests mTH as a conserved buffering mechanism that promotes the robustness and evolvability of metabolism. Moreover, adaptive diversification via evolving dual substrate consumption highlights the flexibility of physiological systems to exploit ecological opportunities. PMID:25715029

  13. Long-Term Environmental Research Programs - Evolving Capacity for Discovery

    Science.gov (United States)

    Swanson, F. J.

    2008-12-01

    Long-term forestry, watershed, and ecological research sites have become critical, productive nodes for environmental science research and in some cases for work in the social sciences and humanities. The Forest Service's century-old Experimental Forests and Ranges and the National Science Foundation's 28- year-old Long-Term Ecological Research program have been remarkably productive in both basic and applied sciences, including characterization of acid rain and old-growth ecosystems and development of forest, watershed, and range management systems for commercial and other land use objectives. A review of recent developments suggests steps to enhance the function of collections of long-term research sites as interactive science networks. The programs at these sites have evolved greatly, especially over the past few decades, as the questions addressed, disciplines engaged, and degree of science integration have grown. This is well displayed by small, experimental watershed studies, which first were used for applied hydrology studies then more fundamental biogeochemical studies and now examination of complex ecosystem processes; all capitalizing on the legacy of intensive studies and environmental monitoring spanning decades. In very modest ways these collections of initially independent sites have functioned increasingly as integrated research networks addressing inter-site questions by using common experimental designs, being part of a single experiment, and examining long-term data in a common analytical framework. The network aspects include data sharing via publicly-accessible data-harvester systems for climate and streamflow data. The layering of one research or environmental monitoring network upon another facilitates synergies. Changing climate and atmospheric chemistry highlight a need to use these networks as continental-scale observatory systems for assessing the impacts of environmental change on ecological services. To better capitalize on long

  14. Enhancing neural-network performance via assortativity

    International Nuclear Information System (INIS)

    Franciscis, Sebastiano de; Johnson, Samuel; Torres, Joaquin J.

    2011-01-01

    The performance of attractor neural networks has been shown to depend crucially on the heterogeneity of the underlying topology. We take this analysis a step further by examining the effect of degree-degree correlations - assortativity - on neural-network behavior. We make use of a method recently put forward for studying correlated networks and dynamics thereon, both analytically and computationally, which is independent of how the topology may have evolved. We show how the robustness to noise is greatly enhanced in assortative (positively correlated) neural networks, especially if it is the hub neurons that store the information.

  15. Interstitial laser coagulation in the treatment of benign prostatic hyperplasia using a diode laser system: results of an evolving technology

    NARCIS (Netherlands)

    Mårtenson, A. C.; de la Rosette, J. J. M. C. H.

    1999-01-01

    Interstitial laser coagulation (ILC) treatment is a recent technique in the treatment of BPH that is evolving rapidly. The results of a prospective randomised study vs transurethral resection of the prostate (TURP) is presented as well as results of patients treated with a temperature sensing laser

  16. Biodiversity and ecosystem functioning in evolving food webs.

    Science.gov (United States)

    Allhoff, K T; Drossel, B

    2016-05-19

    We use computer simulations in order to study the interplay between biodiversity and ecosystem functioning (BEF) during both the formation and the ongoing evolution of large food webs. A species in our model is characterized by its own body mass, its preferred prey body mass and the width of its potential prey body mass spectrum. On an ecological time scale, population dynamics determines which species are viable and which ones go extinct. On an evolutionary time scale, new species emerge as modifications of existing ones. The network structure thus emerges and evolves in a self-organized manner. We analyse the relation between functional diversity and five community level measures of ecosystem functioning. These are the metabolic loss of the predator community, the total biomasses of the basal and the predator community, and the consumption rates on the basal community and within the predator community. Clear BEF relations are observed during the initial build-up of the networks, or when parameters are varied, causing bottom-up or top-down effects. However, ecosystem functioning measures fluctuate only very little during long-term evolution under constant environmental conditions, despite changes in functional diversity. This result supports the hypothesis that trophic cascades are weaker in more complex food webs. © 2016 The Author(s).

  17. Plant Evolution: A Manufacturing Network Perspective

    DEFF Research Database (Denmark)

    Yang, Cheng; Johansen, John; Boer, Harry

    2009-01-01

    Viewing them as portfolios of products and processes, we aim to address how plants evolve in the context of a manufacturing network and how the evolution of one plant impacts other plants in the same manufacturing network. Based on discussions of ten plants from three Danish companies, we identify...... two different trajectories. Together, these trajectories determine the evolution of a manufacturing network. Factors appearing to affect the two trajectories include competencies built up, transferred or acquired locally, market potential, performance considerations, local, situational factors...

  18. Bose-Einstein Condensation in Complex Networks

    International Nuclear Information System (INIS)

    Bianconi, Ginestra; Barabasi, Albert-Laszlo

    2001-01-01

    The evolution of many complex systems, including the World Wide Web, business, and citation networks, is encoded in the dynamic web describing the interactions between the system's constituents. Despite their irreversible and nonequilibrium nature these networks follow Bose statistics and can undergo Bose-Einstein condensation. Addressing the dynamical properties of these nonequilibrium systems within the framework of equilibrium quantum gases predicts that the 'first-mover-advantage,' 'fit-get-rich,' and 'winner-takes-all' phenomena observed in competitive systems are thermodynamically distinct phases of the underlying evolving networks

  19. Optical network democratization.

    Science.gov (United States)

    Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

    2016-03-06

    The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation. © 2016 The Author(s).

  20. Fractal gene regulatory networks for robust locomotion control of modular robots

    DEFF Research Database (Denmark)

    Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh

    2010-01-01

    Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...

  1. Optical network design and planning

    CERN Document Server

    Simmons, Jane M

    2014-01-01

    This book takes a pragmatic approach to designing state-of-the-art optical networks for backbone, regional, and metro-core networks.   Algorithms and methodologies related to routing, regeneration, wavelength assignment, subrate-traffic grooming, and protection are presented, with an emphasis on optical-bypass-enabled (or all-optical) networks. There are numerous case studies throughout the text to illustrate the concepts, using realistic networks and traffic sets. A full chapter of economic studies offers guidelines as to when and how optical-bypass technology should be deployed. There is also extensive coverage of recent research to provide insight into how optical networks are likely to evolve. The second edition includes new chapters on dynamic optical networking and flexible/elastic optical networks. There is expanded coverage of new physical-layer technology and its impact on network design, along with enhanced coverage of ROADM architectures, including the colorless, directionless, contentionless, a...

  2. Dynamical Networks Characterization of Space Weather Events

    Science.gov (United States)

    Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

    2017-12-01

    Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show

  3. Online professional networks for physicians: risk management.

    Science.gov (United States)

    Hyman, Jon L; Luks, Howard J; Sechrest, Randale

    2012-05-01

    The rapidly developing array of online physician-only communities represents a potential extraordinary advance in the availability of educational and informational resources to physicians. These online communities provide physicians with a new range of controls over the information they process, but use of this social media technology carries some risk. The purpose of this review was to help physicians manage the risks of online professional networking and discuss the potential benefits that may come with such networks. This article explores the risks and benefits of physicians engaging in online professional networking with peers and provides suggestions on risk management. Through an Internet search and literature review, we scrutinized available case law, federal regulatory code, and guidelines of conduct from professional organizations and consultants. We reviewed the OrthoMind.com site as a case example because it is currently the only online social network exclusively for orthopaedic surgeons. Existing case law suggests potential liability for orthopaedic surgeons who engage with patients on openly accessible social network platforms. Current society guidelines in both the United States and Britain provide sensible rules that may mitigate such risks. However, the overall lack of a strong body of legal opinions, government regulations as well as practical experience for most surgeons limit the suitability of such platforms. Closed platforms that are restricted to validated orthopaedic surgeons may limit these downside risks and hence allow surgeons to collaborate with one another both as clinicians and practice owners. Educating surgeons about the pros and cons of participating in these networking platforms is helping them more astutely manage risks and optimize benefits. This evolving online environment of professional interaction is one of few precedents, but the application of risk management strategies that physicians use in daily practice carries over

  4. A network growth model based on the evolutionary ultimatum game

    International Nuclear Information System (INIS)

    Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S

    2012-01-01

    In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)

  5. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

    Directory of Open Access Journals (Sweden)

    Jinjun Tang

    Full Text Available Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN, two learning processes are proposed: (1 a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2 a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE, root mean square error (RMSE, and mean absolute relative error (MARE are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR, instantaneous model (IM, linear model (LM, neural network (NN, and cumulative plots (CP.

  6. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

    Science.gov (United States)

    Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

    2016-01-01

    Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

  7. Evolving technologies drive the new roles of Biomedical Engineering.

    Science.gov (United States)

    Frisch, P H; St Germain, J; Lui, W

    2008-01-01

    Rapidly changing technology coupled with the financial impact of organized health care, has required hospital Biomedical Engineering organizations to augment their traditional operational and business models to increase their role in developing enhanced clinical applications utilizing new and evolving technologies. The deployment of these technology based applications has required Biomedical Engineering organizations to re-organize to optimize the manner in which they provide and manage services. Memorial Sloan-Kettering Cancer Center has implemented a strategy to explore evolving technologies integrating them into enhanced clinical applications while optimally utilizing the expertise of the traditional Biomedical Engineering component (Clinical Engineering) to provide expanded support in technology / equipment management, device repair, preventive maintenance and integration with legacy clinical systems. Specifically, Biomedical Engineering is an integral component of the Medical Physics Department which provides comprehensive and integrated support to the Center in advanced physical, technical and engineering technology. This organizational structure emphasizes the integration and collaboration between a spectrum of technical expertise for clinical support and equipment management roles. The high cost of clinical equipment purchases coupled with the increasing cost of service has driven equipment management responsibilities to include significant business and financial aspects to provide a cost effective service model. This case study details the dynamics of these expanded roles, future initiatives and benefits for Biomedical Engineering and Memorial Sloan Kettering Cancer Center.

  8. Facilitating value co-creation in networks

    DEFF Research Database (Denmark)

    Rasmussen, Mette Apollo

    participants in varied ways come to grasp the meaning of networking. The dissertation draws on insights from the Service-Dominant (S-D) Logic to explain how networks can be seen as spheres for value co-creation. Co-creation as a theoretical construct has evolved from varied streams of service marketing...... of networking. The concept of “imaginative value” (Beckert, 2011) is used to explain the oscillating behaviors observed in the two networks. Imaginative value can be defined as symbolic value that actors ascribe to an object, in this case the network. I argue that the group practices in the networks led......The dissertation investigates through two ethnographic case studies how value co-creation takes place in inter-organizational networks that have been facilitated by a municipality. The contribution of the study to business network research is the emphasis on development phases of networks...

  9. Evolution of the social network of scientific collaborations

    Science.gov (United States)

    Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T.

    2002-08-01

    The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it offers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks.

  10. UMTS rapid response real-time seismic networks: implementation and strategies at INGV

    Science.gov (United States)

    Govoni, A.; Margheriti, L.; Moretti, M.; Lauciani, V.; Sensale, G.; Bucci, A.; Criscuoli, F.

    2015-12-01

    Universal Mobile Telecommunications System (UMTS) and its evolutions are nowadays the most affordable and widespread data communication infrastructure available almost world wide. Moreover the always growing cellular phone market is pushing the development of new devices with higher performances and lower power consumption. All these characteristics make UMTS really useful for the implementation of an "easy to deploy" temporary real-time seismic station. Despite these remarkable features, there are many drawbacks that must be properly taken in account to effectively transmit the seismic data: Internet security, signal and service availability, power consumption. - Internet security: exposing seismological data services and seismic stations to the Internet is dangerous, attack prone and can lead to downtimes in the services, so we setup a dedicated Virtual Private Network (VPN) service to protect all the connected devices. - Signal and service availability: while for temporary experiment a carefull planning and an accurate site selection can minimize the problem, this is not always the case with rapid response networks. Moreover, as with any other leased line, the availability of the UMTS service during a seismic crisis is basically unpredictable. Nowadays in Italy during a major national emergency a Committee of the Italian Civil Defense ensures unified management and coordination of emergency activities. Inside it the telecom companies are committed to give support to the crisis management improving the standards in their communication networks. - Power consumption: it is at least of the order of that of the seismic station and, being related to data flow and signal quality is largely unpredictable. While the most secure option consists in adding a second independent solar power supply to the seismic station, this is not always a very convenient solution since it doubles the cost and doubles the equipment on site. We found that an acceptable trade-off is to add an

  11. A model for evolution of overlapping community networks

    Science.gov (United States)

    Karan, Rituraj; Biswal, Bibhu

    2017-05-01

    A model is proposed for the evolution of network topology in social networks with overlapping community structure. Starting from an initial community structure that is defined in terms of group affiliations, the model postulates that the subsequent growth and loss of connections is similar to the Hebbian learning and unlearning in the brain and is governed by two dominant factors: the strength and frequency of interaction between the members, and the degree of overlap between different communities. The temporal evolution from an initial community structure to the current network topology can be described based on these two parameters. It is possible to quantify the growth occurred so far and predict the final stationary state to which the network is likely to evolve. Applications in epidemiology or the spread of email virus in a computer network as well as finding specific target nodes to control it are envisaged. While facing the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities one faces the most basic questions: how do communities evolve in time? This work aims to address this issue by developing a mathematical model for the evolution of community networks and studying it through computer simulation.

  12. Efficient Network Monitoring for Attack Detection

    OpenAIRE

    Limmer, Tobias

    2011-01-01

    Techniques for network-based intrusion detection have been evolving for years, and the focus of most research is on detection algorithms, although networks are distributed and dynamically managed nowadays. A data processing framework is required that allows to embed multiple detection techniques and to provide data with the needed aggregation levels. Within that framework, this work concentrates on methods that improve the interoperability of intrusion detection techniques and focuses on data...

  13. Applying the sequential neural-network approximation and orthogonal array algorithm to optimize the axial-flow cooling system for rapid thermal processes

    International Nuclear Information System (INIS)

    Hung, Shih-Yu; Shen, Ming-Ho; Chang, Ying-Pin

    2009-01-01

    The sequential neural-network approximation and orthogonal array (SNAOA) were used to shorten the cooling time for the rapid cooling process such that the normalized maximum resolved stress in silicon wafer was always below one in this study. An orthogonal array was first conducted to obtain the initial solution set. The initial solution set was treated as the initial training sample. Next, a back-propagation sequential neural network was trained to simulate the feasible domain to obtain the optimal parameter setting. The size of the training sample was greatly reduced due to the use of the orthogonal array. In addition, a restart strategy was also incorporated into the SNAOA so that the searching process may have a better opportunity to reach a near global optimum. In this work, we considered three different cooling control schemes during the rapid thermal process: (1) downward axial gas flow cooling scheme; (2) upward axial gas flow cooling scheme; (3) dual axial gas flow cooling scheme. Based on the maximum shear stress failure criterion, the other control factors such as flow rate, inlet diameter, outlet width, chamber height and chamber diameter were also examined with respect to cooling time. The results showed that the cooling time could be significantly reduced using the SNAOA approach

  14. Social networks in cardiovascular disease management.

    Science.gov (United States)

    Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

    2010-12-01

    Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

  15. Energy-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaojuan Luo

    2012-01-01

    Full Text Available Based on the complex network theory, a new topological evolving model is proposed. In the evolution of the topology of sensor networks, the energy-aware mechanism is taken into account, and the phenomenon of change of the link and node in the network is discussed. Theoretical analysis and numerical simulation are conducted to explore the topology characteristics and network performance with different node energy distribution. We find that node energy distribution has the weak effect on the degree distribution P(k that evolves into the scale-free state, nodes with more energy carry more connections, and degree correlation is nontrivial disassortative. Moreover, the results show that, when nodes energy is more heterogeneous, the network is better clustered and enjoys higher performance in terms of the network efficiency and the average path length for transmitting data.

  16. Damage spreading on networks: Clustering effects

    Indian Academy of Sciences (India)

    sensitive to statistical fluctuations compared to conventional Monte Carlo ... Theory. We deal with the DS problem on networks based on Ising model with Glauber ... s = {si(t)} evolve in time, we use Glauber dynamics, the transition probability of.

  17. Topology evolution in macromolecular networks

    NARCIS (Netherlands)

    Kryven, I.

    2014-01-01

    Governed by various intermolecular forces, molecular networks tend to evolve from simple to very complex formations that have random structure. This randomness in the connectivity of the basic units can still be captured employing distributional description of the state of the system; the evolution

  18. On the Critical Role of Divergent Selection in Evolvability

    Directory of Open Access Journals (Sweden)

    Joel Lehman

    2016-08-01

    Full Text Available An ambitious goal in evolutionary robotics is to evolve increasingly complex robotic behaviors with minimal human design effort. Reaching this goal requires evolutionary algorithms that can unlock from genetic encodings their latent potential for evolvability. One issue clouding this goal is conceptual confusion about evolvability, which often obscures the aspects of evolvability that are important or desirable. The danger from such confusion is that it may establish unrealistic goals for evolvability that prove unproductive in practice. An important issue separate from conceptual confusion is the common misalignment between selection and evolvability in evolutionary robotics. While more expressive encodings can represent higher-level adaptations (e.g. sexual reproduction or developmental systems that increase long-term evolutionary potential (i.e. evolvability, realizing such potential requires gradients of fitness and evolvability to align. In other words, selection is often a critical factor limiting increasing evolvability. Thus, drawing from a series of recent papers, this article seeks to both (1 clarify and focus the ways in which the term evolvability is used within artificial evolution, and (2 argue for the importance of one type of selection, i.e. divergent selection, for enabling evolvability. The main argument is that there is a fundamental connection between divergent selection and evolvability (on both the individual and population level that does not hold for typical goal-oriented selection. The conclusion is that selection pressure plays a critical role in realizing the potential for evolvability, and that divergent selection in particular provides a principled mechanism for encouraging evolvability in artificial evolution.

  19. Climate in Context - How partnerships evolve in regions

    Science.gov (United States)

    Parris, A. S.

    2014-12-01

    In 2015, NOAA's RISA program will celebrate its 20th year of exploration in the development of usable climate information. In the mid-1990s, a vision emerged to develop interdisciplinary research efforts at the regional scale for several important reasons. Recognizable climate patterns, such as the El Nino Southern Oscillation (ENSO), emerge at the regional level where our understanding of observations and models coalesce. Critical resources for society are managed in a context of regional systems, such as water supply and human populations. Multiple scales of governance (local, state, and federal) with complex institutional relationships can be examined across a region. Climate information (i.e. data, science, research etc) developed within these contexts has greater potential for use. All of this work rests on a foundation of iterative engagement between scientists and decision makers. Throughout these interactions, RISAs have navigated diverse politics, extreme events and disasters, socio-economic and ecological disruptions, and advances in both science and technology. Our understanding of information needs is evolving into a richer understanding of complex institutional, legal, political, and cultural contexts within which people can use science to make informed decisions. The outcome of RISA work includes both cases where climate information was used in decisions and cases where capacity for using climate information and making climate resilient decisions has increased over time. In addition to balancing supply and demand of scientific information, RISAs are engaged in a social process of reconciling climate information use with important drivers of society. Because partnerships are critical for sustained engagement, and because engagement is critically important to the use of science, the rapid development of new capacity in regionally-based science programs focused on providing climate decision support is both needed and challenging. New actors can bolster

  20. Evolved H II regions

    International Nuclear Information System (INIS)

    Churchwell, E.

    1975-01-01

    A probable evolutionary sequence of H II regions based on six distinct types of observed objects is suggested. Two examples which may deviate from this idealized sequence, are discussed. Even though a size-mean density relation of H II regions can be used as a rough indication of whether a nebula is very young or evolved, it is argued that such a relation is not likely to be useful for the quantitative assignment of ages to H II regions. Evolved H II regions appear to fit into one of four structural types: rings, core-halos, smooth structures, and irregular or filamentary structures. Examples of each type are given with their derived physical parameters. The energy balance in these nebulae is considered. The mass of ionized gas in evolved H II regions is in general too large to trace the nebula back to single compact H II regions. Finally, the morphological type of the Galaxy is considered from its H II region content. 2 tables, 2 figs., 29 refs

  1. SkyNet: Modular nuclear reaction network library

    Science.gov (United States)

    Lippuner, Jonas; Roberts, Luke F.

    2017-10-01

    The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.

  2. Transition Towards An Integrated Network Organisation

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum

    2016-01-01

    , with particular attention to the role played by the home base (HB) organisation in this evolution. The research is focused on the intra-organisational global network and uses a longitudinal single-case study. Findings depict the transition as being enabled by the interaction between HB knowledge about......Management of internationally dispersed and networked operations has been in the focus of research attention. However, the existing studies underestimate the incrementality of changes shaping such organisations. This work investigates how organisations evolve into network structures...... the organization, and its reconfiguration decisions. Implications are also discussed regarding process drivers and the role of HB in the network organization....

  3. Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

    Science.gov (United States)

    Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

    2018-02-28

    The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

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

    Directory of Open Access Journals (Sweden)

    Ram Prahlad T

    2008-08-01

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

  5. Evolving Capabilities for Virtual Globes

    Science.gov (United States)

    Glennon, A.

    2006-12-01

    Though thin-client spatial visualization software like Google Earth and NASA World Wind enjoy widespread popularity, a common criticism is their general lack of analytical functionality. This concern, however, is rapidly being addressed; standard and advanced geographic information system (GIS) capabilities are being developed for virtual globes--though not centralized into a single implementation or software package. The innovation is mostly originating from the user community. Three such capabilities relevant to the earth science, education, and emergency management communities are modeling dynamic spatial phenomena, real-time data collection and visualization, and multi-input collaborative databases. Modeling dynamic spatial phenomena has been facilitated through joining virtual globe geometry definitions--like KML--to relational databases. Real-time data collection uses short scripts to transform user-contributed data into a format usable by virtual globe software. Similarly, collaborative data collection for virtual globes has become possible by dynamically referencing online, multi-person spreadsheets. Examples of these functions include mapping flows within a karst watershed, real-time disaster assessment and visualization, and a collaborative geyser eruption spatial decision support system. Virtual globe applications will continue to evolve further analytical capabilities, more temporal data handling, and from nano to intergalactic scales. This progression opens education and research avenues in all scientific disciplines.

  6. Rapid prototyping for biomedical engineering: current capabilities and challenges.

    Science.gov (United States)

    Lantada, Andrés Díaz; Morgado, Pilar Lafont

    2012-01-01

    A new set of manufacturing technologies has emerged in the past decades to address market requirements in a customized way and to provide support for research tasks that require prototypes. These new techniques and technologies are usually referred to as rapid prototyping and manufacturing technologies, and they allow prototypes to be produced in a wide range of materials with remarkable precision in a couple of hours. Although they have been rapidly incorporated into product development methodologies, they are still under development, and their applications in bioengineering are continuously evolving. Rapid prototyping and manufacturing technologies can be of assistance in every stage of the development process of novel biodevices, to address various problems that can arise in the devices' interactions with biological systems and the fact that the design decisions must be tested carefully. This review focuses on the main fields of application for rapid prototyping in biomedical engineering and health sciences, as well as on the most remarkable challenges and research trends.

  7. Targeted disruption in mice of a neural stem cell-maintaining, KRAB-Zn finger-encoding gene that has rapidly evolved in the human lineage.

    Directory of Open Access Journals (Sweden)

    Huan-Chieh Chien

    Full Text Available Understanding the genetic basis of the physical and behavioral traits that separate humans from other primates is a challenging but intriguing topic. The adaptive functions of the expansion and/or reduction in human brain size have long been explored. From a brain transcriptome project we have identified a KRAB-Zn finger protein-encoding gene (M003-A06 that has rapidly evolved since the human-chimpanzee separation. Quantitative RT-PCR analysis of different human tissues indicates that M003-A06 expression is enriched in the human fetal brain in addition to the fetal heart. Furthermore, analysis with use of immunofluorescence staining, neurosphere culturing and Western blotting indicates that the mouse ortholog of M003-A06, Zfp568, is expressed mainly in the embryonic stem (ES cells and fetal as well as adult neural stem cells (NSCs. Conditional gene knockout experiments in mice demonstrates that Zfp568 is both an NSC maintaining- and a brain size-regulating gene. Significantly, molecular genetic analyses show that human M003-A06 consists of 2 equilibrated allelic types, H and C, one of which (H is human-specific. Combined contemporary genotyping and database mining have revealed interesting genetic associations between the different genotypes of M003-A06 and the human head sizes. We propose that M003-A06 is likely one of the genes contributing to the uniqueness of the human brain in comparison to other higher primates.

  8. Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory

    DEFF Research Database (Denmark)

    Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra

    2017-01-01

    it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...

  9. Wide area network monitoring system for HEP experiments at Fermilab

    International Nuclear Information System (INIS)

    Grigoriev, Maxim; Fermilab; Cottrell, Les; Logg, Connie; SLAC

    2004-01-01

    Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system

  10. Wide Area Network Monitoring System for HEP Experiments at Fermilab

    International Nuclear Information System (INIS)

    Grigoriev, M.

    2004-01-01

    Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system

  11. Wide Area Network Monitoring System for HEP Experiments at Fermilab

    Energy Technology Data Exchange (ETDEWEB)

    Grigoriev, M.

    2004-11-23

    Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system.

  12. Production, Innovation and Service Networks

    DEFF Research Database (Denmark)

    Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Johansen, John

    2012-01-01

    Production, innovation and service networks of companies all over the world become increasingly decentralised, specialised and interdependent. These three characteristics combined inevitably lead to the formation of complex configurations of resources, crossing both national and organisational...... borders. The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gaps between these networks mean that coordinating them and managing their interfaces in a global operations context...... are becoming strategically important. The purpose of this paper is to address this issue and to develop a number of propositions about the development and organisation of these networks. The paper highlights the critical importance of engineering operations in this process. The propositions are developed...

  13. Production, Innovation and Service Networks

    DEFF Research Database (Denmark)

    Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Johansen, John

    2011-01-01

    is becoming strategically important. The purpose of this paper is to address this issue and to develop a number of propositions about how companies can organize these networks and coordinate between them effectively. The propositions are developed by employing the design science approach based on a literature......Production, innovation and service networks of companies all over the world become increasingly decentralized, specialized and interdependent. The three characteristics combined inevitably lead to the formation of complex configurations of assets and capabilities crossing both national...... and organisational borders. The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gap between these networks means that coordinating them and managing their interfaces in global operations context...

  14. A Squeezed Artificial Neural Network for the Symbolic Network Reliability Functions of Binary-State Networks.

    Science.gov (United States)

    Yeh, Wei-Chang

    Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.

  15. Primary progressive aphasia and the evolving neurology of the language network.

    Science.gov (United States)

    Mesulam, M-Marsel; Rogalski, Emily J; Wieneke, Christina; Hurley, Robert S; Geula, Changiz; Bigio, Eileen H; Thompson, Cynthia K; Weintraub, Sandra

    2014-10-01

    Primary progressive aphasia (PPA) is caused by selective neurodegeneration of the language-dominant cerebral hemisphere; a language deficit initially arises as the only consequential impairment and remains predominant throughout most of the course of the disease. Agrammatic, logopenic and semantic subtypes, each reflecting a characteristic pattern of language impairment and corresponding anatomical distribution of cortical atrophy, represent the most frequent presentations of PPA. Such associations between clinical features and the sites of atrophy have provided new insights into the neurology of fluency, grammar, word retrieval, and word comprehension, and have necessitated modification of concepts related to the functions of the anterior temporal lobe and Wernicke's area. The underlying neuropathology of PPA is, most commonly, frontotemporal lobar degeneration in the agrammatic and semantic forms, and Alzheimer disease (AD) pathology in the logopenic form; the AD pathology often displays atypical and asymmetrical anatomical features consistent with the aphasic phenotype. The PPA syndrome reflects complex interactions between disease-specific neuropathological features and patient-specific vulnerability. A better understanding of these interactions might help us to elucidate the biology of the language network and the principles of selective vulnerability in neurodegenerative diseases. We review these aspects of PPA, focusing on advances in our understanding of the clinical features and neuropathology of PPA and what they have taught us about the neural substrates of the language network.

  16. Completing sparse and disconnected protein-protein network by deep learning.

    Science.gov (United States)

    Huang, Lei; Liao, Li; Wu, Cathy H

    2018-03-22

    Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network

  17. A brief review of advances in complex networks of nuclear science and technology field

    International Nuclear Information System (INIS)

    Fang Jinqing

    2010-01-01

    A brief review of advances in complex networks of nuclear science and technology field at home and is given and summarized. These complex networks include: nuclear energy weapon network, network centric warfare, beam transport networks, continuum percolation evolving network associated with nuclear reactions, global nuclear power station network, (nuclear) chemistry reaction networks, radiological monitoring and anti-nuclear terror networks, and so on. Some challenge issues and development prospects of network science are pointed out finally. (authors)

  18. Evolving Technologies: A View to Tomorrow

    Science.gov (United States)

    Tamarkin, Molly; Rodrigo, Shelley

    2011-01-01

    Technology leaders must participate in strategy creation as well as operational delivery within higher education institutions. The future of higher education--the view to tomorrow--is irrevocably integrated and intertwined with evolving technologies. This article focuses on two specific evolving technologies: (1) alternative IT sourcing; and (2)…

  19. Mobile location services over the next generation IP core network

    DEFF Research Database (Denmark)

    Thongthammachart, Saowanee; Olesen, Henning

    2003-01-01

    network is changing from circuit-switched to packet-switched technology and evolving to an IP core network based on IPv6. The IP core network will allow all IP devices to be connected seamlessly. Due to the movement detection mechanism of Mobile IPv6, mobile terminals will periodically update....... The concept of mobile location services over the next generation IP networks is described. We also discuss the effectiveness of the short-range wireless network regarding a mobile user's position inside buildings and hotspot areas....

  20. Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance

    NARCIS (Netherlands)

    Moreno-Gamez, Stefany; Hill, Alison L.; Rosenbloom, Daniel I. S.; Petrov, Dmitri A.; Nowak, Martin A.; Pennings, Pleuni S.

    2015-01-01

    Infections with rapidly evolving pathogens are often treated using combinations of drugs with different mechanisms of action. One of the major goal of combination therapy is to reduce the risk of drug resistance emerging during a patient's treatment. Although this strategy generally has significant

  1. MIMO Communication for Cellular Networks

    CERN Document Server

    Huang, Howard; Venkatesan, Sivarama

    2012-01-01

    As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

  2. Duplicate Abalone Egg Coat Proteins Bind Sperm Lysin Similarly, but Evolve Oppositely, Consistent with Molecular Mimicry at Fertilization

    Science.gov (United States)

    Aagaard, Jan E.; Springer, Stevan A.; Soelberg, Scott D.; Swanson, Willie J.

    2013-01-01

    Sperm and egg proteins constitute a remarkable paradigm in evolutionary biology: despite their fundamental role in mediating fertilization (suggesting stasis), some of these molecules are among the most rapidly evolving ones known, and their divergence can lead to reproductive isolation. Because of strong selection to maintain function among interbreeding individuals, interacting fertilization proteins should also exhibit a strong signal of correlated divergence among closely related species. We use evidence of such molecular co-evolution to target biochemical studies of fertilization in North Pacific abalone (Haliotis spp.), a model system of reproductive protein evolution. We test the evolutionary rates (d N/d S) of abalone sperm lysin and two duplicated egg coat proteins (VERL and VEZP14), and find a signal of co-evolution specific to ZP-N, a putative sperm binding motif previously identified by homology modeling. Positively selected residues in VERL and VEZP14 occur on the same face of the structural model, suggesting a common mode of interaction with sperm lysin. We test this computational prediction biochemically, confirming that the ZP-N motif is sufficient to bind lysin and that the affinities of VERL and VEZP14 are comparable. However, we also find that on phylogenetic lineages where lysin and VERL evolve rapidly, VEZP14 evolves slowly, and vice versa. We describe a model of sexual conflict that can recreate this pattern of anti-correlated evolution by assuming that VEZP14 acts as a VERL mimic, reducing the intensity of sexual conflict and slowing the co-evolution of lysin and VERL. PMID:23408913

  3. Duplicate abalone egg coat proteins bind sperm lysin similarly, but evolve oppositely, consistent with molecular mimicry at fertilization.

    Directory of Open Access Journals (Sweden)

    Jan E Aagaard

    Full Text Available Sperm and egg proteins constitute a remarkable paradigm in evolutionary biology: despite their fundamental role in mediating fertilization (suggesting stasis, some of these molecules are among the most rapidly evolving ones known, and their divergence can lead to reproductive isolation. Because of strong selection to maintain function among interbreeding individuals, interacting fertilization proteins should also exhibit a strong signal of correlated divergence among closely related species. We use evidence of such molecular co-evolution to target biochemical studies of fertilization in North Pacific abalone (Haliotis spp., a model system of reproductive protein evolution. We test the evolutionary rates (d(N/d(S of abalone sperm lysin and two duplicated egg coat proteins (VERL and VEZP14, and find a signal of co-evolution specific to ZP-N, a putative sperm binding motif previously identified by homology modeling. Positively selected residues in VERL and VEZP14 occur on the same face of the structural model, suggesting a common mode of interaction with sperm lysin. We test this computational prediction biochemically, confirming that the ZP-N motif is sufficient to bind lysin and that the affinities of VERL and VEZP14 are comparable. However, we also find that on phylogenetic lineages where lysin and VERL evolve rapidly, VEZP14 evolves slowly, and vice versa. We describe a model of sexual conflict that can recreate this pattern of anti-correlated evolution by assuming that VEZP14 acts as a VERL mimic, reducing the intensity of sexual conflict and slowing the co-evolution of lysin and VERL.

  4. Rapid Alterations in Perirenal Adipose Tissue Transcriptomic Networks with Cessation of Voluntary Running.

    Directory of Open Access Journals (Sweden)

    Gregory N Ruegsegger

    Full Text Available In maturing rats, the growth of abdominal fat is attenuated by voluntary wheel running. After the cessation of running by wheel locking, a rapid increase in adipose tissue growth to a size that is similar to rats that have never run (i.e. catch-up growth has been previously reported by our lab. In contrast, diet-induced increases in adiposity have a slower onset with relatively delayed transcriptomic responses. The purpose of the present study was to identify molecular pathways associated with the rapid increase in adipose tissue after ending 6 wks of voluntary running at the time of puberty. Age-matched, male Wistar rats were given access to running wheels from 4 to 10 weeks of age. From the 10th to 11th week of age, one group of rats had continued wheel access, while the other group had one week of wheel locking. Perirenal adipose tissue was extracted, RNA sequencing was performed, and bioinformatics analyses were executed using Ingenuity Pathway Analysis (IPA. IPA was chosen to assist in the understanding of complex 'omics data by integrating data into networks and pathways. Wheel locked rats gained significantly more fat mass and significantly increased body fat percentage between weeks 10-11 despite having decreased food intake, as compared to rats with continued wheel access. IPA identified 646 known transcripts differentially expressed (p < 0.05 between continued wheel access and wheel locking. In wheel locked rats, IPA revealed enrichment of transcripts for the following functions: extracellular matrix, macrophage infiltration, immunity, and pro-inflammatory. These findings suggest that increases in visceral adipose tissue that accompanies the cessation of pubertal physical activity are associated with the alteration of multiple pathways, some of which may potentiate the development of pubertal obesity and obesity-associated systemic low-grade inflammation that occurs later in life.

  5. Structure and growth of weighted networks

    Energy Technology Data Exchange (ETDEWEB)

    Riccaboni, Massimo [Department of Computer and Management Sciences, University of Trento, Trento (Italy); Schiavo, Stefano [Department of Economics, University of Trento, Trento (Italy)], E-mail: massimo.riccaboni@unitn.it, E-mail: stefano.schiavo@unitn.it

    2010-02-15

    We develop a simple theoretical framework for the evolution of weighted networks that is consistent with a number of stylized features of real-world data. In our framework, the Barabasi-Albert model of network evolution is extended by assuming that link weights evolve according to a geometric Brownian motion. Our model is verified by means of simulations and real-world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationship of the growth of link weights, the relationship between the degree and strength of nodes, and the scale-free structure of the network.

  6. Security management of next generation telecommunications networks and services

    CERN Document Server

    Jacobs, Stuart

    2014-01-01

    This book will cover network management security issues and currently available security mechanisms by discussing how network architectures have evolved into the contemporary NGNs which support converged services (voice, video, TV, interactive information exchange, and classic data communications). It will also analyze existing security standards and their applicability to securing network management. This book will review 21st century security concepts of authentication, authorization, confidentiality, integrity, nonrepudiation, vulnerabilities, threats, risks, and effective approaches to enc

  7. The Age of Enlightenment: Evolving Opportunities in Brain Research Through Optical Manipulation of Neuronal Activity

    OpenAIRE

    Jerome, Jason; Heck, Detlef H.

    2011-01-01

    Optical manipulation of neuronal activity has rapidly developed into the most powerful and widely used approach to study mechanisms related to neuronal connectivity over a range of scales. Since the early use of single site uncaging to map network connectivity, rapid technological development of light modulation techniques has added important new options, such as fast scanning photostimulation, massively parallel control of light stimuli, holographic uncaging, and two-photon stimulation techn...

  8. Rapid countermeasure discovery against Francisella tularensis based on a metabolic network reconstruction.

    Directory of Open Access Journals (Sweden)

    Sidhartha Chaudhury

    Full Text Available In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of

  9. Network planning study of the metro-optical-network-oriented 3G application

    Science.gov (United States)

    Gong, Qian; Xu, Rong; Lin, Jin Tong

    2005-02-01

    To compare with the 2G mobile communication, 3G technologies can supply the perfect service scope and performance. 3G is the trend of the mobile communication. So now to build the transmission network, it is needed to consider how the transmission network to support the 3G applications. For the 3G network architecture, it include the 2 part: Utran access network and core network. So the metro optical network should consider how to build the network to adapt the 3G applications. Include the metro core and access layer. In the metro core, we should consider the network should evolved towards the Mesh architecture with ASON function to realize the fast protection and restoration, quick end-to-end service provision, and high capacity cross-connect matrix etc. In the access layer, the network should have the ability to access the 3G services such as ATM interface with IMA function. In addition, the traffic grooming should be provided to improve the bandwidth utility. In this paper, first we present the MCC network situation, the network planning model will be introduced. Then we present the topology architecture, node capacity and traffic forecast. At last, based on our analysis, we will give a total solution to MCC to build their metro optical network toward to the mesh network with the consideration of 3G services.

  10. Coevolution within a transcriptional network by compensatory trans and cis mutations

    KAUST Repository

    Kuo, D.

    2010-10-26

    Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of “coevolution” between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.

  11. Spacetimes containing slowly evolving horizons

    International Nuclear Information System (INIS)

    Kavanagh, William; Booth, Ivan

    2006-01-01

    Slowly evolving horizons are trapping horizons that are ''almost'' isolated horizons. This paper reviews their definition and discusses several spacetimes containing such structures. These include certain Vaidya and Tolman-Bondi solutions as well as (perturbatively) tidally distorted black holes. Taking into account the mass scales and orders of magnitude that arise in these calculations, we conjecture that slowly evolving horizons are the norm rather than the exception in astrophysical processes that involve stellar-scale black holes

  12. Optical processing for future computer networks

    Science.gov (United States)

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

    1986-01-01

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

  13. Order Patterns Networks (orpan – a method toestimate time-evolving functional connectivity frommultivariate time series

    Directory of Open Access Journals (Sweden)

    Stefan eSchinkel

    2012-11-01

    Full Text Available Complex networks provide an excellent framework for studying the functionof the human brain activity. Yet estimating functional networks from mea-sured signals is not trivial, especially if the data is non-stationary and noisyas it is often the case with physiological recordings. In this article we proposea method that uses the local rank structure of the data to define functionallinks in terms of identical rank structures. The method yields temporal se-quences of networks which permits to trace the evolution of the functionalconnectivity during the time course of the observation. We demonstrate thepotentials of this approach with model data as well as with experimentaldata from an electrophysiological study on language processing.

  14. Dynamics of Large Systems of Nonlinearly Evolving Units

    Science.gov (United States)

    Lu, Zhixin

    The dynamics of large systems of many nonlinearly evolving units is a general research area that has great importance for many areas in science and technology, including biology, computation by artificial neural networks, statistical mechanics, flocking in animal groups, the dynamics of coupled neurons in the brain, and many others. While universal principles and techniques are largely lacking in this broad area of research, there is still one particular phenomenon that seems to be broadly applicable. In particular, this is the idea of emergence, by which is meant macroscopic behaviors that "emerge" from a large system of many "smaller or simpler entities such that...large entities" [i.e., macroscopic behaviors] arise which "exhibit properties the smaller/simpler entities do not exhibit." In this thesis we investigate mechanisms and manifestations of emergence in four dynamical systems consisting many nonlinearly evolving units. These four systems are as follows. (a) We first study the motion of a large ensemble of many noninteracting particles in a slowly changing Hamiltonian system that undergoes a separatrix crossing. In such systems, we find that separatrix-crossing induces a counterintuitive effect. Specifically, numerical simulation of two sets of densely sprinkled initial conditions on two energy curves appears to suggest that the two energy curves, one originally enclosing the other, seemingly interchange their positions. This, however, is topologically forbidden. We resolve this paradox by introducing a numerical simulation method we call "robust" and study its consequences. (b) We next study the collective dynamics of oscillatory pacemaker neurons in Suprachiasmatic Nucleus (SCN), which, through synchrony, govern the circadian rhythm of mammals. We start from a high-dimensional description of the many coupled oscillatory neuronal units within the SCN. This description is based on a forced Kuramoto model. We then reduce the system dimensionality by using

  15. Jamming in complex networks with degree correlation

    International Nuclear Information System (INIS)

    Pastore y Piontti, Ana L.; Braunstein, Lidia A.; Macri, Pablo A.

    2010-01-01

    We study the effects of the degree-degree correlations on the pressure congestion J when we apply a dynamical process on scale free complex networks using the gradient network approach. We find that the pressure congestion for disassortative (assortative) networks is lower (bigger) than the one for uncorrelated networks which allow us to affirm that disassortative networks enhance transport through them. This result agree with the fact that many real world transportation networks naturally evolve to this kind of correlation. We explain our results showing that for the disassortative case the clusters in the gradient network turn out to be as much elongated as possible, reducing the pressure congestion J and observing the opposite behavior for the assortative case. Finally we apply our model to real world networks, and the results agree with our theoretical model.

  16. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  17. Modeling evolution of crosstalk in noisy signal transduction networks

    Science.gov (United States)

    Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-02-01

    Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

  18. The United Kingdom's radiotherapy dosimetry audit network

    International Nuclear Information System (INIS)

    Thwaites, D.I.; Allahverdi, M.; Powley, S.K.; Nisbet, A.

    2003-01-01

    The first comprehensive national dosimetry intercomparison in the United Kingdom involving all UK radiotherapy centres was carried out in the late 1980s. Out of this a regular radiotherapy dosimetry audit network evolved in the early 1990s. The network is co-ordinated by the Institute of Physics and Engineering in Medicine and comprises eight co-operative regional groups. Audits are based on site visits using ionization chambers and epoxy resin water substitute phantoms. The basic audit methodology and phantom design follows that of the original national intercomparison exercise. However, most of the groups have evolved more complex methods, to extend the audit scope to include other parameters, other parts of the radiotherapy process and other treatment modalities. A number of the groups have developed phantoms to simulate various clinical treatment situations, enabling the sharing of phantoms and expertise between groups, but retaining a common base. Besides megavoltage external beam photon dosimetry, a number of the groups have also included the audit of kilovoltage X ray beams, electron beams and brachytherapy dosimetry. The National Physical Laboratory is involved in the network and carries out basic beam calibration audits to link the groups. The network is described and the methods and results are illustrated using the Scottish+ group as an example. (author)

  19. The Evolving Science of Patient and Family Engagement: An Interview With Dr Karen Drenkard.

    Science.gov (United States)

    Reid-Ponte, Patricia

    2018-02-01

    Patient- and family-centered care is a central tenet of nursing practice. This concept has evolved to include patient partnerships, patient engagement, and patient activation. This column differentiates these concepts and describes the core principles embedded in the overriding intention of ensuring that patients (and their families or significant others) are orchestrators of their health and their care plans. In this interview, Karen Drenkard, PhD, RN, FAAN, NEA-BC, CNO, of the GetWellNetwork, discusses work by the O'Neil Center as a leader in this area.

  20. Approximating centrality in evolving graphs: toward sublinearity

    Science.gov (United States)

    Priest, Benjamin W.; Cybenko, George

    2017-05-01

    The identification of important nodes is a ubiquitous problem in the analysis of social networks. Centrality indices (such as degree centrality, closeness centrality, betweenness centrality, PageRank, and others) are used across many domains to accomplish this task. However, the computation of such indices is expensive on large graphs. Moreover, evolving graphs are becoming increasingly important in many applications. It is therefore desirable to develop on-line algorithms that can approximate centrality measures using memory sublinear in the size of the graph. We discuss the challenges facing the semi-streaming computation of many centrality indices. In particular, we apply recent advances in the streaming and sketching literature to provide a preliminary streaming approximation algorithm for degree centrality utilizing CountSketch and a multi-pass semi-streaming approximation algorithm for closeness centrality leveraging a spanner obtained through iteratively sketching the vertex-edge adjacency matrix. We also discuss possible ways forward for approximating betweenness centrality, as well as spectral measures of centrality. We provide a preliminary result using sketched low-rank approximations to approximate the output of the HITS algorithm.

  1. Structural and Infrastructural Underpinnings of International R&D Networks

    DEFF Research Database (Denmark)

    Niang, Mohamed; Sørensen, Brian Vejrum

    2009-01-01

    This paper explores the process of globally distributing R&D activities with an emphasis on the effects of network maturity. It discusses emerging configurations by asking how the structure and infrastructure of international R&D networks evolve along with the move from a strong R&D center...... to dispersed development. Drawing from case studies of two international R&D networks, it presents a capability maturity model and argues that understanding the interaction between new structures and infrastructures of the dispersed networks has become a key requirement for developing organizational...

  2. Towards integrated crisis support of regional emergency networks.

    Science.gov (United States)

    Caro, D H

    1999-01-01

    Emergency and crisis management pose multidimensional information systems challenges for communities across North America. In the quest to reduce mortality and morbidity risks and to increase the level of crisis preparedness, regional emergency management networks have evolved. Integrated Crisis Support Systems (ICSS) are enabling information technologies that assist emergency managers by enhancing the ability to strategically manage and control these regional emergency networks efficiently and effectively. This article underscores the ICCS development, control and leadership issues and their promising implications for regional emergency management networks.

  3. Service creation and deployment on an intelligent network

    OpenAIRE

    Collins, Michael

    1999-01-01

    Active competition in the telecommunications industry has caused a dramatic shift in focus for public network operators. Service designers need to be able to easily and rapidly create services according to the customer’s requirements. This is achievable by using Intelligent Networks (INs). Two primary goals of service development under the Intelligent Network paradigm are rapid service crcation using new software technologies and the minimisation of service development costs through switch ve...

  4. Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling

    DEFF Research Database (Denmark)

    Meng, Weizhi; Au, Man Ho

    2017-01-01

    Due to the popularity of mobile devices, medical smartphone networks (MSNs) have been evolved, which become an emerging network architecture in healthcare domain to improve the quality of service. There is no debate among security experts that the security of Internet-enabled medical devices...

  5. Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

    Science.gov (United States)

    Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

    2016-05-01

    Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 ;complex networks; articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

  6. Evolution of an artificial neural network based autonomous land vehicle controller.

    Science.gov (United States)

    Baluja, S

    1996-01-01

    This paper presents an evolutionary method for creating an artificial neural network based autonomous land vehicle controller. The evolved controllers perform better in unseen situations than those trained with an error backpropagation learning algorithm designed for this task. In this paper, an overview of the previous connectionist based approaches to this task is given, and the evolutionary algorithms used in this study are described in detail. Methods for reducing the high computational costs of training artificial neural networks with evolutionary algorithms are explored. Error metrics specific to the task of autonomous vehicle control are introduced; the evolutionary algorithms guided by these error metrics reveal improved performance over those guided by the standard sum-squared error metric. Finally, techniques for integrating evolutionary search and error backpropagation are presented. The evolved networks are designed to control Carnegie Mellon University's NAVLAB vehicles in road following tasks.

  7. Seismogeodesy for rapid earthquake and tsunami characterization

    Science.gov (United States)

    Bock, Y.

    2016-12-01

    Rapid estimation of earthquake magnitude and fault mechanism is critical for earthquake and tsunami warning systems. Traditionally, the monitoring of earthquakes and tsunamis has been based on seismic networks for estimating earthquake magnitude and slip, and tide gauges and deep-ocean buoys for direct measurement of tsunami waves. These methods are well developed for ocean basin-wide warnings but are not timely enough to protect vulnerable populations and infrastructure from the effects of local tsunamis, where waves may arrive within 15-30 minutes of earthquake onset time. Direct measurements of displacements by GPS networks at subduction zones allow for rapid magnitude and slip estimation in the near-source region, that are not affected by instrumental limitations and magnitude saturation experienced by local seismic networks. However, GPS displacements by themselves are too noisy for strict earthquake early warning (P-wave detection). Optimally combining high-rate GPS and seismic data (in particular, accelerometers that do not clip), referred to as seismogeodesy, provides a broadband instrument that does not clip in the near field, is impervious to magnitude saturation, and provides accurate real-time static and dynamic displacements and velocities in real time. Here we describe a NASA-funded effort to integrate GPS and seismogeodetic observations as part of NOAA's Tsunami Warning Centers in Alaska and Hawaii. It consists of a series of plug-in modules that allow for a hierarchy of rapid seismogeodetic products, including automatic P-wave picking, hypocenter estimation, S-wave prediction, magnitude scaling relationships based on P-wave amplitude (Pd) and peak ground displacement (PGD), finite-source CMT solutions and fault slip models as input for tsunami warnings and models. For the NOAA/NASA project, the modules are being integrated into an existing USGS Earthworm environment, currently limited to traditional seismic data. We are focused on a network of

  8. A rapid two step protocol of in vitro propagation of an important ...

    African Journals Online (AJOL)

    Attempts were made to evolve a rapid in vitro technology to conserve, as well as, mass propagate this valuable medicinal herb in very short duration. The combinations of ... MS media supplemented with BAP with IBA (4:0.5 and 5:0.5) resulted in shooting, as well as, rooting simultaneously. Micro propagated plantlets were ...

  9. Imaging complex nutrient dynamics in mycelial networks.

    Science.gov (United States)

    Fricker, M D; Lee, J A; Bebber, D P; Tlalka, M; Hynes, J; Darrah, P R; Watkinson, S C; Boddy, L

    2008-08-01

    Transport networks are vital components of multi-cellular organisms, distributing nutrients and removing waste products. Animal cardiovascular and respiratory systems, and plant vasculature, are branching trees whose architecture is thought to determine universal scaling laws in these organisms. In contrast, the transport systems of many multi-cellular fungi do not fit into this conceptual framework, as they have evolved to explore a patchy environment in search of new resources, rather than ramify through a three-dimensional organism. These fungi grow as a foraging mycelium, formed by the branching and fusion of threadlike hyphae, that gives rise to a complex network. To function efficiently, the mycelial network must both transport nutrients between spatially separated source and sink regions and also maintain its integrity in the face of continuous attack by mycophagous insects or random damage. Here we review the development of novel imaging approaches and software tools that we have used to characterise nutrient transport and network formation in foraging mycelia over a range of spatial scales. On a millimetre scale, we have used a combination of time-lapse confocal imaging and fluorescence recovery after photobleaching to quantify the rate of diffusive transport through the unique vacuole system in individual hyphae. These data then form the basis of a simulation model to predict the impact of such diffusion-based movement on a scale of several millimetres. On a centimetre scale, we have used novel photon-counting scintillation imaging techniques to visualize radiolabel movement in small microcosms. This approach has revealed novel N-transport phenomena, including rapid, preferential N-resource allocation to C-rich sinks, induction of simultaneous bi-directional transport, abrupt switching between different pre-existing transport routes, and a strong pulsatile component to transport in some species. Analysis of the pulsatile transport component using Fourier

  10. Network integration modelling of feeder and BRT(bus rapid transit) to reduce the usage of private vehicles in Palembang’s suburban area

    Science.gov (United States)

    Nur'afalia, D.; Afifa, F.; Rubianto, L.; Handayeni, K. D. M. E.

    2018-01-01

    The aim of this research is to determine the optimal feeder network route that integrates with BRT (Bus Rapid Transit). Palembang, a high growing population city with unresolved transportation demand sector. BRT as main public transportation could not fulfill people’s demand in transportation, especially in Alang-Alang Lebar sub-district. As an impact, the usage of private vehicles increases along the movement toward the city center. The concept of Network Integration that integrates feeder network with BRT is expected to be a solution to suppress the rate of private vehicles’ usage and to improve public transportation service, so that the use of BRT will be increased in the suburban area of Palembang. The method used to identifying the optimal route using Route Analysis method is route analysis using Tranetsim 0.4. The best route is obtained based on 156 movement samples. The result is 58,7% from 199 mobility’s potency of private vehicle usage’s can be reduced if there is a feeder network’s route in Alang-Alang Lebar’s sub-district. From the result, the existance of integration between feeder network and BRT is potential enough to reduce the usage of private vehicles and supports the sustainability of transportation mobility in Palembang City.

  11. INDIAN BUSINESSMEN IN FRANCE: AN INITIAL EXAMINATION OF THEIR ACTIVITIES IN A RAPIDLY-EVOLVING CONTEXT

    Directory of Open Access Journals (Sweden)

    Vasoodeven Vuddamalay

    2010-12-01

    Full Text Available The aim of this article is to understand the implications of the recent economic and political evolution of Indian immigration in Europe, and specifically in France, their businesses and entrepreneurial groups, as well as their links with the countries of origin/welcoming countries and their transnational networks, using an historical and geoanthropological approach. The analysis also covers the essential links that the transnational entrepreneurs establish between France/Europe and the rest of the world, particularly with the emerging cities of Asia, the Middle East and, possibly, certain parts of Africa, such as South Africa, the Mascarene Islands and East Africa. To that end, the author begins by contextualising Indian business projects in France, before going on to examine the current situation of ethnic shops, the transnational companies of traditional trading communities and, to some extent, their Institute of Information Technology networks. The author also carries out a study of the “Mittal Case” as a new paradigm of research within the changing world economy, as the traditional North-South separation is undermined and the complexities of fields in research on trading and business groups is renewed. Finally, the author situates these debates within the growing world knowledge of the communities of Indian immigrants in France and their small ethnic businessmen and traders.

  12. Surveillance Jumps on the Network

    Science.gov (United States)

    Raths, David

    2011-01-01

    Internet protocol (IP) network-based cameras and digital video management software are maturing, and many issues that have surrounded them, including bandwidth, data storage, ease of use, and integration are starting to become clearer as the technology continues to evolve. Prices are going down and the number of features is going up. Many school…

  13. Intoxigenic digital spaces? Youth, social networking sites and alcohol marketing.

    Science.gov (United States)

    Griffiths, Richard; Casswell, Sally

    2010-09-01

    To examine how young people in New Zealand engage with alcohol and reproduce alcohol marketing messages and alcohol-related branding in 'Bebo', a popular social networking site (SNS) on the Internet. Data are drawn from information posted on approximately 150 Bebo Web pages and analysed by way of textual analysis and cyberspace ethnography. Social networking sites, such as Bebo, provide young people with a digital space in which to share a range of alcohol marketing messages via peer-to-peer transmission. Bebo also enables youth to communicate to one another how they consume alcohol and their views of alcohol marketing messages. The information being shared by young people who use Bebo is openly provided in the form of personal information, forum comments, digital photographs and answering quizzes about their engagement with alcohol. Through this sharing of information in the digital Internet environment, young people are creating 'intoxigenic social identities' as well as 'intoxigenic digital spaces' that further contribute towards the normalisation of youth consumption of alcohol. A better understanding of how youth are using the Internet to share their experiences with alcohol and engagement with alcohol-related messages is crucial to public health research as alcohol marketing practices rapidly evolve.

  14. Network Layer Protocol Activation for Packet Data Access in UMTS WCDMA Laboratory Network

    OpenAIRE

    Lakkisto, Erkka

    2011-01-01

    The purpose of this Bachelor’s Thesis was to set up the UMTS WCDMA network in the laboratory environment of Helsinki Metropolia University of Applied Sciences and to study the network layer protocol activation for packet data access. The development of 3G technology has been very rapid and it can be considered as one of the main technologies in telecommunication. Implementing the laboratory network in Metropolia enables teaching and researching of the modern network technology. Labora...

  15. Molecular clock on a neutral network.

    Science.gov (United States)

    Raval, Alpan

    2007-09-28

    The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

  16. Temporal network epidemiology

    CERN Document Server

    Holme, Petter

    2017-01-01

    This book covers recent developments in epidemic process models and related data on temporally varying networks. It is widely recognized that contact networks are indispensable for describing, understanding, and intervening to stop the spread of infectious diseases in human and animal populations; “network epidemiology” is an umbrella term to describe this research field. More recently, contact networks have been recognized as being highly dynamic. This observation, also supported by an increasing amount of new data, has led to research on temporal networks, a rapidly growing area. Changes in network structure are often informed by epidemic (or other) dynamics, in which case they are referred to as adaptive networks. This volume gathers contributions by prominent authors working in temporal and adaptive network epidemiology, a field essential to understanding infectious diseases in real society.

  17. Assuring SS7 dependability: A robustness characterization of signaling network elements

    Science.gov (United States)

    Karmarkar, Vikram V.

    1994-04-01

    Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

  18. Hardware demonstration of high-speed networks for satellite applications.

    Energy Technology Data Exchange (ETDEWEB)

    Donaldson, Jonathon W.; Lee, David S.

    2008-09-01

    This report documents the implementation results of a hardware demonstration utilizing the Serial RapidIO{trademark} and SpaceWire protocols that was funded by Sandia National Laboratories (SNL's) Laboratory Directed Research and Development (LDRD) office. This demonstration was one of the activities in the Modeling and Design of High-Speed Networks for Satellite Applications LDRD. This effort has demonstrated the transport of application layer packets across both RapidIO and SpaceWire networks to a common downlink destination using small topologies comprised of commercial-off-the-shelf and custom devices. The RapidFET and NEX-SRIO debug and verification tools were instrumental in the successful implementation of the RapidIO hardware demonstration. The SpaceWire hardware demonstration successfully demonstrated the transfer and routing of application data packets between multiple nodes and also was able reprogram remote nodes using configuration bitfiles transmitted over the network, a key feature proposed in node-based architectures (NBAs). Although a much larger network (at least 18 to 27 nodes) would be required to fully verify the design for use in a real-world application, this demonstration has shown that both RapidIO and SpaceWire are capable of routing application packets across a network to a common downlink node, illustrating their potential use in real-world NBAs.

  19. On the Benefits of Divergent Search for Evolved Representations

    DEFF Research Database (Denmark)

    Lehman, Joel; Risi, Sebastian; Stanley, Kenneth O

    2012-01-01

    Evolved representations in evolutionary computation are often fragile, which can impede representation-dependent mechanisms such as self-adaptation. In contrast, evolved representations in nature are robust, evolvable, and creatively exploit available representational features. This paper provide...

  20. Conflict and convention in dynamic networks.

    Science.gov (United States)

    Foley, Michael; Forber, Patrick; Smead, Rory; Riedl, Christoph

    2018-03-01

    An important way to resolve games of conflict (snowdrift, hawk-dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioural strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host-guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models. © 2017 The Author(s).

  1. ELeaRNT: Evolutionary Learning of Rich Neural Network Topologies

    National Research Council Canada - National Science Library

    Matteucci, Matteo

    2006-01-01

    In this paper we present ELeaRNT an evolutionary strategy which evolves rich neural network topologies in order to find an optimal domain specific non linear function approximator with a good generalization performance...

  2. Not only … but also: REM sleep creates and NREM Stage 2 instantiates landmark junctions in cortical memory networks.

    Science.gov (United States)

    Llewellyn, Sue; Hobson, J Allan

    2015-07-01

    This article argues both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep contribute to overnight episodic memory processes but their roles differ. Episodic memory may have evolved from memory for spatial navigation in animals and humans. Equally, mnemonic navigation in world and mental space may rely on fundamentally equivalent processes. Consequently, the basic spatial network characteristics of pathways which meet at omnidirectional nodes or junctions may be conserved in episodic brain networks. A pathway is formally identified with the unidirectional, sequential phases of an episodic memory. In contrast, the function of omnidirectional junctions is not well understood. In evolutionary terms, both animals and early humans undertook tours to a series of landmark junctions, to take advantage of resources (food, water and shelter), whilst trying to avoid predators. Such tours required memory for emotionally significant landmark resource-place-danger associations and the spatial relationships amongst these landmarks. In consequence, these tours may have driven the evolution of both spatial and episodic memory. The environment is dynamic. Resource-place associations are liable to shift and new resource-rich landmarks may be discovered, these changes may require re-wiring in neural networks. To realise these changes, REM may perform an associative, emotional encoding function between memory networks, engendering an omnidirectional landmark junction which is instantiated in the cortex during NREM Stage 2. In sum, REM may preplay associated elements of past episodes (rather than replay individual episodes), to engender an unconscious representation which can be used by the animal on approach to a landmark junction in wake. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. The Development of Network Relations of MNC Subsidiaries : How Internal MNC and External (Local) Relations Evolve

    NARCIS (Netherlands)

    Drogendijk, H.J.

    2005-01-01

    Managing relations is a complex task for internationalizing firms and their subsidiaries: MNC subsidiaries are not only part of the MNC network but they also develop relations with network actors in their local environment.This paper investigates conceptually how MNC subsidiaries established through

  4. Spatial price dynamics: From complex network perspective

    Science.gov (United States)

    Li, Y. L.; Bi, J. T.; Sun, H. J.

    2008-10-01

    The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.

  5. RAPID DETERMINATION OF FOCAL DEPTH USING A GLOBAL NETWORK OF SMALL-APERTURE SEISMIC ARRAYS

    Science.gov (United States)

    Seats, K.; Koper, K.; Benz, H.

    2009-12-01

    The National Earthquake Information Center (NEIC) of the United States Geological Survey (USGS) operates 24 hours a day, 365 days a year with the mission of locating and characterizing seismic events around the world. A key component of this task is quickly determining the focal depth of each seismic event, which has a first-order effect on estimates of ground shaking used in the impact assessment applications of emergency response activities. Current methods of depth estimation used at the NEIC include arrival time inversion both with and without depth phases, a Bayesian depth constraint based on historical seismicity (1973-present), and moment tensor inversion primarily using P- and S-wave waveforms. In this study, we explore the possibility of automated modeling of waveforms from vertical-component arrays of the International Monitoring System (IMS) to improve rapid depth estimation at NEIC. Because these arrays are small-aperture, they are effective at increasing signal to noise ratios for frequencies of 1 Hz and higher. Currently, NEIC receives continuous real-time data from 23 IMS arrays. Following work done by previous researchers, we developed a technique that acts as an array of arrays. For a given epicentral location we calculate fourth root beams for each IMS array in the distance range of 30 to 95 degrees at the expected slowness vector of the first arrival. Because the IMS arrays are small-aperture, these beams highlight energy that has slowness similar to the first arrival, such as depth phases. The beams are rectified by taking the envelope and then automatically aligned on the largest peak within 5 seconds of the expected arrival time. The station beams are then combined into network beams assuming a range of depths varying from 10 km to 700 km in increments of 1 km. The network beams are computed assuming both pP and sP propagation, and a measure of beam power is output as a function of depth for both propagation models, as well as their sum. We

  6. Modeling Temporal Evolution and Multiscale Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2013-01-01

    Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...

  7. Probabilistic Mobility Models for Mobile and Wireless Networks

    DEFF Research Database (Denmark)

    Song, Lei; Godskesen, Jens Christian

    2010-01-01

    In this paper we present a probabilistic broadcast calculus for mobile and wireless networks whose connections are unreliable. In our calculus broadcasted messages can be lost with a certain probability, and due to mobility the connection probabilities may change. If a network broadcasts a message...... from a location it will evolve to a network distribution depending on whether nodes at other locations receive the message or not. Mobility of locations is not arbitrary but guarded by a probabilistic mobility function (PMF) and we also define the notion of a weak bisimulation given a PMF...

  8. The rapid evolution of CT findings in pulmonary langerhans cell histiocytosis: a case report

    International Nuclear Information System (INIS)

    Kang, Tae Wook; Lee, Kyung Soo; Cho, Eun Yoon

    2007-01-01

    Imaging findings of pulmonary Langerhans cell histiocytosis (PLCH) demonstrate evolving changes over time, and the radiological transitions shown by imaging tools may allow a prediction of histopathological activity in PLCH. However, there are no reports describing how rapidly CT findings change with time. We describe a case of PLCH that showed a rapid evolutional change of the pulmonary lesions in a 48-year-old man, in which the nodular lesions showed cystic changes within two-month follow-up periods on chest CT scans

  9. The genotype-phenotype map of an evolving digital organism

    OpenAIRE

    Fortuna, Miguel A.; Zaman, Luis; Ofria, Charles; Wagner, Andreas

    2017-01-01

    To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms fr...

  10. EVOLVE

    CERN Document Server

    Deutz, André; Schütze, Oliver; Legrand, Pierrick; Tantar, Emilia; Tantar, Alexandru-Adrian

    2017-01-01

    This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.

  11. Knowledge-based network ties in early rapidly internationalising small firms

    DEFF Research Database (Denmark)

    Masango, Shingairai Grace; Marinova, Svetla Trifonova

    2014-01-01

    strong knowledge-based contacts. The ERISF acts as the source that provides the technical information and knowledge, which is then adopted by their network partners. This means that the ERISF’s product and technological capabilities drive the international knowledge creation process. The findings provide...... a holistic characterisation of the concept of knowledge in ERISF internationalisation. Within their interorganisational relationships, ERISFs are involved in knowledge creation, knowledge transfer and knowledge adoption activities. Network ties developed in existing knowledge pools are extended to new...

  12. Resistance and Security Index of Networks: Structural Information Perspective of Network Security.

    Science.gov (United States)

    Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

    2016-06-03

    Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

  13. Resistance and Security Index of Networks: Structural Information Perspective of Network Security

    Science.gov (United States)

    Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

    2016-01-01

    Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks. PMID:27255783

  14. Resistance and Security Index of Networks: Structural Information Perspective of Network Security

    Science.gov (United States)

    Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

    2016-06-01

    Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

  15. The complex network of the Brazilian Popular Music

    Science.gov (United States)

    de Lima e Silva, D.; Medeiros Soares, M.; Henriques, M. V. C.; Schivani Alves, M. T.; de Aguiar, S. G.; de Carvalho, T. P.; Corso, G.; Lucena, L. S.

    2004-02-01

    We study the Brazilian Popular Music in a network perspective. We call the Brazilian Popular Music Network, BPMN, the graph where the vertices are the song writers and the links are determined by the existence of at least a common singer. The linking degree distribution of such graph shows power law and exponential regions. The exponent of the power law is compatible with the values obtained by the evolving network algorithms seen in the literature. The average path length of the BPMN is similar to the correspondent random graph, its clustering coefficient, however, is significantly larger. These results indicate that the BPMN forms a small-world network.

  16. Effects of deception in social networks.

    Science.gov (United States)

    Iñiguez, Gerardo; Govezensky, Tzipe; Dunbar, Robin; Kaski, Kimmo; Barrio, Rafael A

    2014-09-07

    Honesty plays a crucial role in any situation where organisms exchange information or resources. Dishonesty can thus be expected to have damaging effects on social coherence if agents cannot trust the information or goods they receive. However, a distinction is often drawn between prosocial lies ('white' lies) and antisocial lying (i.e. deception for personal gain), with the former being considered much less destructive than the latter. We use an agent-based model to show that antisocial lying causes social networks to become increasingly fragmented. Antisocial dishonesty thus places strong constraints on the size and cohesion of social communities, providing a major hurdle that organisms have to overcome (e.g. by evolving counter-deception strategies) in order to evolve large, socially cohesive communities. In contrast, white lies can prove to be beneficial in smoothing the flow of interactions and facilitating a larger, more integrated network. Our results demonstrate that these group-level effects can arise as emergent properties of interactions at the dyadic level. The balance between prosocial and antisocial lies may set constraints on the structure of social networks, and hence the shape of society as a whole. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  17. Research on NGN network control technology

    Science.gov (United States)

    Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

    2004-04-01

    Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

  18. Systemic risk on different interbank network topologies

    Science.gov (United States)

    Lenzu, Simone; Tedeschi, Gabriele

    2012-09-01

    In this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity.

  19. Evolving controllers for a homogeneous system of physical robots: structured cooperation with minimal sensors.

    Science.gov (United States)

    Quinn, Matt; Smith, Lincoln; Mayley, Giles; Husbands, Phil

    2003-10-15

    We report on recent work in which we employed artificial evolution to design neural network controllers for small, homogeneous teams of mobile autonomous robots. The robots were evolved to perform a formation-movement task from random starting positions, equipped only with infrared sensors. The dual constraints of homogeneity and minimal sensors make this a non-trivial task. We describe the behaviour of a successful system in which robots adopt and maintain functionally distinct roles in order to achieve the task. We believe this to be the first example of the use of artificial evolution to design coordinated, cooperative behaviour for real robots.

  20. We really need to talk: adapting FDA processes to rapid change.

    Science.gov (United States)

    Lykken, Sara

    2013-01-01

    The rapidly evolving realm of modern commerce strains traditional regulatory paradigms. This paper traces the historical evolution of FDA crisis-response regulation and provides examples of ways in which the definitions and procedures resulting from that past continue to be challenged by new products as market entrants, some in good faith and others not, take actions that create disconnects between actual product and marketing controls and those that consumers might expect. The paper then explores some of the techniques used by other federal agencies that have faced similar challenges in environments characterized by rapid innovation, and draws from this analysis suggestions for improvement of the FDA's warning letter system.

  1. Nation-Wide Mobile Network Energy Evolution Analysis

    DEFF Research Database (Denmark)

    Perez, Eva; Frank, Philipp; Micallef, Gilbert

    2013-01-01

    Mobile network operators are facing a challenging dilemma. While on the one hand they are committed to reducing their carbon emissions, and energy consumption, they are also required to continuously upgrade existing networks, ensuring that the relentless growth in data traffic can still be suppor......Mobile network operators are facing a challenging dilemma. While on the one hand they are committed to reducing their carbon emissions, and energy consumption, they are also required to continuously upgrade existing networks, ensuring that the relentless growth in data traffic can still...... be supported. In most cases, these upgrades increase the energy consumption of the network even further. This paper presents a nation-wide case study, based on a commercial network of a leading European operator, intended to provide a clear understanding of how the energy consumption of mobile networks...... is expected to evolve from 2012 until 2020. The study also considers an efficient network capacity evolution path, including base station equipment improvement forecasts....

  2. Network simulations of optical illusions

    Science.gov (United States)

    Shinbrot, Troy; Lazo, Miguel Vivar; Siu, Theo

    We examine a dynamical network model of visual processing that reproduces several aspects of a well-known optical illusion, including subtle dependencies on curvature and scale. The model uses a genetic algorithm to construct the percept of an image, and we show that this percept evolves dynamically so as to produce the illusions reported. We find that the perceived illusions are hardwired into the model architecture and we propose that this approach may serve as an archetype to distinguish behaviors that are due to nature (i.e. a fixed network architecture) from those subject to nurture (that can be plastically altered through learning).

  3. Rapid learning in visual cortical networks.

    Science.gov (United States)

    Wang, Ye; Dragoi, Valentin

    2015-08-26

    Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

  4. All projects related to Canada | Page 18 | IDRC - International ...

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

    The presence of pollutants in Brazil's coastal ecosystems can affect food systems ... China's large population, fast-growing economy, rapidly evolving social networks, ... Thailand, Viet Nam, Central Asia, South Asia, Cambodia, China, Canada.

  5. Popularity versus similarity in growing networks

    Science.gov (United States)

    Krioukov, Dmitri; Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, Mariangeles; Boguna, Marian

    2012-02-01

    Preferential attachment is a powerful mechanism explaining the emergence of scaling in growing networks. If new connections are established preferentially to more popular nodes in a network, then the network is scale-free. Here we show that not only popularity but also similarity is a strong force shaping the network structure and dynamics. We develop a framework where new connections, instead of preferring popular nodes, optimize certain trade-offs between popularity and similarity. The framework admits a geometric interpretation, in which preferential attachment emerges from local optimization processes. As opposed to preferential attachment, the optimization framework accurately describes large-scale evolution of technological (Internet), social (web of trust), and biological (E.coli metabolic) networks, predicting the probability of new links in them with a remarkable precision. The developed framework can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.

  6. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  7. Network evolution by nonlinear preferential rewiring of edges

    Science.gov (United States)

    Xu, Xin-Jian; Hu, Xiao-Ming; Zhang, Li-Jie

    2011-06-01

    The mathematical framework for small-world networks proposed in a seminal paper by Watts and Strogatz sparked a widespread interest in modeling complex networks in the past decade. However, most of research contributing to static models is in contrast to real-world dynamic networks, such as social and biological networks, which are characterized by rearrangements of connections among agents. In this paper, we study dynamic networks evolved by nonlinear preferential rewiring of edges. The total numbers of vertices and edges of the network are conserved, but edges are continuously rewired according to the nonlinear preference. Assuming power-law kernels with exponents α and β, the network structures in stationary states display a distinct behavior, depending only on β. For β>1, the network is highly heterogeneous with the emergence of starlike structures. For β<1, the network is widely homogeneous with a typical connectivity. At β=1, the network is scale free with an exponential cutoff.

  8. Genonets server-a web server for the construction, analysis and visualization of genotype networks.

    Science.gov (United States)

    Khalid, Fahad; Aguilar-Rodríguez, José; Wagner, Andreas; Payne, Joshua L

    2016-07-08

    A genotype network is a graph in which vertices represent genotypes that have the same phenotype. Edges connect vertices if their corresponding genotypes differ in a single small mutation. Genotype networks are used to study the organization of genotype spaces. They have shed light on the relationship between robustness and evolvability in biological systems as different as RNA macromolecules and transcriptional regulatory circuits. Despite the importance of genotype networks, no tool exists for their automatic construction, analysis and visualization. Here we fill this gap by presenting the Genonets Server, a tool that provides the following features: (i) the construction of genotype networks for categorical and univariate phenotypes from DNA, RNA, amino acid or binary sequences; (ii) analyses of genotype network topology and how it relates to robustness and evolvability, as well as analyses of genotype network topography and how it relates to the navigability of a genotype network via mutation and natural selection; (iii) multiple interactive visualizations that facilitate exploratory research and education. The Genonets Server is freely available at http://ieu-genonets.uzh.ch. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Maintaining evolvability.

    Science.gov (United States)

    Crow, James F

    2008-12-01

    Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy

  10. Genetic adaptation of the antibacterial human innate immunity network.

    Science.gov (United States)

    Casals, Ferran; Sikora, Martin; Laayouni, Hafid; Montanucci, Ludovica; Muntasell, Aura; Lazarus, Ross; Calafell, Francesc; Awadalla, Philip; Netea, Mihai G; Bertranpetit, Jaume

    2011-07-11

    Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

  11. Effective but costly, evolved mechanisms of defense against a virulent opportunistic pathogen in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Yixin H Ye

    2009-04-01

    Full Text Available Drosophila harbor substantial genetic variation for antibacterial defense, and investment in immunity is thought to involve a costly trade-off with life history traits, including development, life span, and reproduction. To understand the way in which insects invest in fighting bacterial infection, we selected for survival following systemic infection with the opportunistic pathogen Pseudomonas aeruginosa in wild-caught Drosophila melanogaster over 10 generations. We then examined genome-wide changes in expression in the selected flies relative to unselected controls, both of which had been infected with the pathogen. This powerful combination of techniques allowed us to specifically identify the genetic basis of the evolved immune response. In response to selection, population-level survivorship to infection increased from 15% to 70%. The evolved capacity for defense was costly, however, as evidenced by reduced longevity and larval viability and a rapid loss of the trait once selection pressure was removed. Counter to expectation, we observed more rapid developmental rates in the selected flies. Selection-associated changes in expression of genes with dual involvement in developmental and immune pathways suggest pleiotropy as a possible mechanism for the positive correlation. We also found that both the Toll and the Imd pathways work synergistically to limit infectivity and that cellular immunity plays a more critical role in overcoming P. aeruginosa infection than previously reported. This work reveals novel pathways by which Drosophila can survive infection with a virulent pathogen that may be rare in wild populations, however, due to their cost.

  12. Evolvability as a Quality Attribute of Software Architectures

    NARCIS (Netherlands)

    Ciraci, S.; van den Broek, P.M.; Duchien, Laurence; D'Hondt, Maja; Mens, Tom

    We review the definition of evolvability as it appears on the literature. In particular, the concept of software evolvability is compared with other system quality attributes, such as adaptability, maintainability and modifiability.

  13. JINR rapid communications

    International Nuclear Information System (INIS)

    1996-01-01

    The present collection of rapid communications from JINR, Dubna, contains five separate reports on analytic QCD running coupling with finite IR behaviour and universal α bar s (0) value, quark condensate in the interacting pion- nucleon medium at finite temperature and baryon number density, γ-π 0 discrimination with a shower maximum detector using neural networks for the solenoidal tracker at RHIC, off-specular neutron reflection from magnetic media with nondiagonal reflectivity matrices and molecular cytogenetics of radiation-induced gene mutations in Drosophila melanogaster. 21 fig., 1 tab

  14. Physical Configuration of the Next Generation Home Network

    Science.gov (United States)

    Terada, Shohei; Kakishima, Yu; Hanawa, Dai; Oguchi, Kimio

    The number of broadband users is rapidly increasing worldwide. Japan already has over 10 million FTTH users. Another trend is the rapid digitalization of home electrical equipment e. g. digital cameras and hard disc recorders. These trends will encourage the emergence of the next generation home network. In this paper, we introduce the next generation home network image and describe the five domains into which home devices can be classified. We then clarify the optimum medium with which to configure the network given the requirements imposed by the home environment. Wiring cable lengths for three network topologies are calculated. The results gained from the next generation home network implemented on the first phase testbed are shown. Finally, our conclusions are given.

  15. The age of enlightenment: evolving opportunities in brain research through optical manipulation of neuronal activity

    Directory of Open Access Journals (Sweden)

    Jason eJerome

    2011-12-01

    Full Text Available Optical manipulation of neuronal activity has rapidly developed into the most powerful and widely used approach to study mechanisms related to neuronal connectivity over a range of scales. Since the early use of single site uncaging to map network connectivity, rapid technological development of light modulation techniques has added important new options, such as fast scanning photostimulation, massively parallel control of light stimuli, holographic uncaging and 2-photon stimulation techniques. Exciting new developments in optogenetics complement neurotransmitter uncaging techniques by providing cell-type specificity and in vivo usability, providing optical access to the neural substrates of behavior. Here we review the rapid evolution of methods for the optical manipulation of neuronal activity, emphasizing crucial recent developments.

  16. The age of enlightenment: evolving opportunities in brain research through optical manipulation of neuronal activity.

    Science.gov (United States)

    Jerome, Jason; Heck, Detlef H

    2011-01-01

    Optical manipulation of neuronal activity has rapidly developed into the most powerful and widely used approach to study mechanisms related to neuronal connectivity over a range of scales. Since the early use of single site uncaging to map network connectivity, rapid technological development of light modulation techniques has added important new options, such as fast scanning photostimulation, massively parallel control of light stimuli, holographic uncaging, and two-photon stimulation techniques. Exciting new developments in optogenetics complement neurotransmitter uncaging techniques by providing cell-type specificity and in vivo usability, providing optical access to the neural substrates of behavior. Here we review the rapid evolution of methods for the optical manipulation of neuronal activity, emphasizing crucial recent developments.

  17. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

    A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

  18. Evolution and Function of the Insulin and Insulin-like Signaling Network in Ectothermic Reptiles: Some Answers and More Questions.

    Science.gov (United States)

    Schwartz, Tonia S; Bronikowski, Anne M

    2016-08-01

    The insulin and insulin-like signaling (IIS) molecular network regulates cellular growth and division, and influences organismal metabolism, growth and development, reproduction, and lifespan. As a group, reptiles have incredible diversity in the complex life history traits that have been associated with the IIS network, yet the research on the IIS network in ectothermic reptiles is sparse. Here, we review the IIS network and synthesize what is known about the function and evolution of the IIS network in ectothermic reptiles. The primary hormones of this network-the insulin-like growth factors 1 and 2 (IGFs) likely function in reproduction in ectothermic reptiles, but the precise mechanisms are unclear, and likely range from influencing mating and ovulation to maternal investment in embryonic development. In general, plasma levels of IGF1 increase with food intake in ectothermic reptiles, but the magnitude of the response to food varies across species or populations and the ages of animals. Long-term temperature treatments as well as thermal stress can alter expression of genes within the IIS network. Although relatively little work has been done on IGF2 in ectothermic reptiles, IGF2 is consistently expressed at higher levels than IGF1 in juvenile ectothermic reptiles. Furthermore, in contrast to mammals that have genetic imprinting that silences the maternal IGF2 allele, in reptiles IGF2 is bi-allelically expressed (based on findings in chickens, a snake, and a lizard). Evolutionary analyses indicate some members of the IIS network are rapidly evolving across reptile species, including IGF1, insulin (INS), and their receptors. In particular, IGF1 displays extensive nucleotide variation across lizards and snakes, which suggests that its functional role may vary across this group. In addition, genetic variation across families and populations in the response of the IIS network to environmental conditions illustrates that components of this network may be evolving in

  19. Rapid evolution of coral proteins responsible for interaction with the environment.

    KAUST Repository

    Voolstra, Christian R.; Sunagawa, Shinichi; Matz, Mikhail V; Bayer, Till; Aranda, Manuel; Buschiazzo, Emmanuel; Desalvo, Michael K; Lindquist, Erika; Szmant, Alina M; Coffroth, Mary Alice; Medina, Mó nica

    2011-01-01

    Corals worldwide are in decline due to climate change effects (e.g., rising seawater temperatures), pollution, and exploitation. The ability of corals to cope with these stressors in the long run depends on the evolvability of the underlying genetic networks and proteins, which remain largely unknown. A genome-wide scan for positively selected genes between related coral species can help to narrow down the search space considerably.

  20. Rapid evolution of coral proteins responsible for interaction with the environment.

    KAUST Repository

    Voolstra, Christian R.

    2011-05-25

    Corals worldwide are in decline due to climate change effects (e.g., rising seawater temperatures), pollution, and exploitation. The ability of corals to cope with these stressors in the long run depends on the evolvability of the underlying genetic networks and proteins, which remain largely unknown. A genome-wide scan for positively selected genes between related coral species can help to narrow down the search space considerably.

  1. Enabling dynamic network analysis through visualization in TVNViewer

    Directory of Open Access Journals (Sweden)

    Curtis Ross E

    2012-08-01

    Full Text Available Abstract Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer, a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

  2. Enabling dynamic network analysis through visualization in TVNViewer

    Science.gov (United States)

    2012-01-01

    Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space. PMID:22897913

  3. MONOMIALS AND BASIN CYLINDERS FOR NETWORK DYNAMICS.

    Science.gov (United States)

    Austin, Daniel; Dinwoodie, Ian H

    We describe methods to identify cylinder sets inside a basin of attraction for Boolean dynamics of biological networks. Such sets are used for designing regulatory interventions that make the system evolve towards a chosen attractor, for example initiating apoptosis in a cancer cell. We describe two algebraic methods for identifying cylinders inside a basin of attraction, one based on the Groebner fan that finds monomials that define cylinders and the other on primary decomposition. Both methods are applied to current examples of gene networks.

  4. Asymmetric core collapse of rapidly rotating massive star

    Science.gov (United States)

    Gilkis, Avishai

    2018-02-01

    Non-axisymmetric features are found in the core collapse of a rapidly rotating massive star, which might have important implications for magnetic field amplification and production of a bipolar outflow that can explode the star, as well as for r-process nucleosynthesis and natal kicks. The collapse of an evolved rapidly rotating MZAMS = 54 M⊙ star is followed in three-dimensional hydrodynamic simulations using the FLASH code with neutrino leakage. A rotating proto-neutron star (PNS) forms with a non-zero linear velocity. This can contribute to the natal kick of the remnant compact object. The PNS is surrounded by a turbulent medium, where high shearing is likely to amplify magnetic fields, which in turn can drive a bipolar outflow. Neutron-rich material in the PNS vicinity might induce strong r-process nucleosynthesis. The rapidly rotating PNS possesses a rotational energy of E_rot ≳ 10^{52} erg. Magnetar formation proceeding in a similar fashion will be able to deposit a portion of this energy later on in the supernova ejecta through a spin-down mechanism. These processes can be important for rare supernovae generated by rapidly rotating progenitors, even though a complete explosion is not simulated in the present study.

  5. The Health and Occupation Research Network: An Evolving Surveillance System.

    Science.gov (United States)

    Carder, Melanie; Hussey, Louise; Money, Annemarie; Gittins, Matthew; McNamee, Roseanne; Stocks, Susan Jill; Sen, Dil; Agius, Raymond M

    2017-09-01

    Vital to the prevention of work-related ill-health (WRIH) is the availability of good quality data regarding WRIH burden and risks. Physician-based surveillance systems such as The Health and Occupation Research (THOR) network in the UK are often established in response to limitations of statutory, compensation-based systems for addressing certain epidemiological aspects of disease surveillance. However, to fulfil their purpose, THOR and others need to have methodologic rigor in capturing and ascertaining cases. This article describes how data collected by THOR and analogous systems can inform WRIH incidence, trends, and other determinants. An overview of the different strands of THOR research is provided, including methodologic advancements facilitated by increased data quantity/quality over time and the value of the research outputs for informing Government and other policy makers. In doing so, the utility of data collected by systems such as THOR to address a wide range of research questions, both in relation to WRIH and to wider issues of public and social health, is demonstrated.

  6. The Health and Occupation Research Network: An Evolving Surveillance System

    Directory of Open Access Journals (Sweden)

    Melanie Carder

    2017-09-01

    Full Text Available Vital to the prevention of work-related ill-health (WRIH is the availability of good quality data regarding WRIH burden and risks. Physician-based surveillance systems such as The Health and Occupation Research (THOR network in the UK are often established in response to limitations of statutory, compensation-based systems for addressing certain epidemiological aspects of disease surveillance. However, to fulfil their purpose, THOR and others need to have methodologic rigor in capturing and ascertaining cases. This article describes how data collected by THOR and analogous systems can inform WRIH incidence, trends, and other determinants. An overview of the different strands of THOR research is provided, including methodologic advancements facilitated by increased data quantity/quality over time and the value of the research outputs for informing Government and other policy makers. In doing so, the utility of data collected by systems such as THOR to address a wide range of research questions, both in relation to WRIH and to wider issues of public and social health, is demonstrated.

  7. A critical analysis of methods for rapid and nondestructive determination of wood density in standing trees

    Science.gov (United States)

    Shan Gao; Xiping Wang; Michael C. Wiemann; Brian K. Brashaw; Robert J. Ross; Lihai Wang

    2017-01-01

    Key message Field methods for rapid determination of wood density in trees have evolved from increment borer, torsiometer, Pilodyn, and nail withdrawal into sophisticated electronic tools of resistance drilling measurement. A partial resistance drilling approach coupled with knowledge of internal tree density distribution may...

  8. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  9. Rapid consolidation of new knowledge in adulthood via fast mapping.

    Science.gov (United States)

    Coutanche, Marc N; Thompson-Schill, Sharon L

    2015-09-01

    Rapid word learning, where words are 'fast mapped' onto new concepts, may help build vocabulary during childhood. Recent evidence has suggested that fast mapping might help to rapidly integrate information into memory networks of the adult neocortex. The neural basis for this learning by fast mapping determines key properties of the learned information. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Network-assisted crop systems genetics: network inference and integrative analysis.

    Science.gov (United States)

    Lee, Tak; Kim, Hyojin; Lee, Insuk

    2015-04-01

    Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. How does language change as a lexical network? An investigation based on written Chinese word co-occurrence networks

    Science.gov (United States)

    Chen, Heng; Chen, Xinying

    2018-01-01

    Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system. PMID:29489837

  12. Quantifying the Structure of Free Association Networks across the Life Span

    Science.gov (United States)

    Dubossarsky, Haim; De Deyne, Simon; Hills, Thomas T.

    2017-01-01

    We investigate how the mental lexicon changes over the life span using free association data from over 8,000 individuals, ranging from 10 to 84 years of age, with more than 400 cue words per age group. Using network analysis, with words as nodes and edges defined by the strength of shared associations, we find that associative networks evolve in a…

  13. Mentoring: An Evolving Relationship.

    Science.gov (United States)

    Block, Michelle; Florczak, Kristine L

    2017-04-01

    The column concerns itself with mentoring as an evolving relationship between mentor and mentee. The collegiate mentoring model, the transformational transcendence model, and the humanbecoming mentoring model are considered in light of a dialogue with mentors at a Midwest university and conclusions are drawn.

  14. Review of network research in scientific journal ‘Entrepreneurship Theory and Practice’

    OpenAIRE

    Agnieszka Brzozowska; Michał Zdziarski

    2016-01-01

    This article aims at presenting a systematic review of publications that verified the network theory and the theory of networks empirically, published in the entrepreneurship journal with the highest Impact Factor: “Entrepreneurship Theory and Practice”. We present how publication frequency evolved over time, and classify papers into major streams of entrepreneurship research. Our findings suggest the theory of networks is an under-researched area promising for further advancing the theory of...

  15. Integration and segregation of large-scale brain networks during short-term task automatization.

    Science.gov (United States)

    Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

    2016-11-03

    The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

  16. Co-evolving prisoner's dilemma: Performance indicators and analytic approaches

    Science.gov (United States)

    Zhang, W.; Choi, C. W.; Li, Y. S.; Xu, C.; Hui, P. M.

    2017-02-01

    Understanding the intrinsic relation between the dynamical processes in a co-evolving network and the necessary ingredients in formulating a reliable theory is an important question and a challenging task. Using two slightly different definitions of performance indicator in the context of a co-evolving prisoner's dilemma game, it is shown that very different cooperative levels result and theories of different complexity are required to understand the key features. When the payoff per opponent is used as the indicator (Case A), non-cooperative strategy has an edge and dominates in a large part of the parameter space formed by the cutting-and-rewiring probability and the strategy imitation probability. When the payoff from all opponents is used (Case B), cooperative strategy has an edge and dominates the parameter space. Two distinct phases, one homogeneous and dynamical and another inhomogeneous and static, emerge and the phase boundary in the parameter space is studied in detail. A simple theory assuming an average competing environment for cooperative agents and another for non-cooperative agents is shown to perform well in Case A. The same theory, however, fails badly for Case B. It is necessary to include more spatial correlation into a theory for Case B. We show that the local configuration approximation, which takes into account of the different competing environments for agents with different strategies and degrees, is needed to give reliable results for Case B. The results illustrate that formulating a proper theory requires both a conceptual understanding of the effects of the adaptive processes in the problem and a delicate balance between simplicity and accuracy.

  17. Evolving effective incremental SAT solvers with GP

    OpenAIRE

    Bader, Mohamed; Poli, R.

    2008-01-01

    Hyper-Heuristics could simply be defined as heuristics to choose other heuristics, and it is a way of combining existing heuristics to generate new ones. In a Hyper-Heuristic framework, the framework is used for evolving effective incremental (Inc*) solvers for SAT. We test the evolved heuristics (IncHH) against other known local search heuristics on a variety of benchmark SAT problems.

  18. Modelling the impact of social network on energy savings

    International Nuclear Information System (INIS)

    Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.

    2016-01-01

    Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout

  19. Dynamic optical resource allocation for mobile core networks with software defined elastic optical networking.

    Science.gov (United States)

    Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo

    2016-07-25

    Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.

  20. Co-regulation of a large and rapidly evolving repertoire of odorant receptor genes

    Directory of Open Access Journals (Sweden)

    Lane Robert P

    2007-09-01

    Full Text Available Abstract The olfactory system meets niche- and species-specific demands by an accelerated evolution of its odorant receptor repertoires. In this review, we describe evolutionary processes that have shaped olfactory and vomeronasal receptor gene families in vertebrate genomes. We emphasize three important periods in the evolution of the olfactory system evident by comparative genomics: the adaptation to land in amphibian ancestors, the decline of olfaction in primates, and the delineation of putative pheromone receptors concurrent with rodent speciation. The rapid evolution of odorant receptor genes, the sheer size of the repertoire, as well as their wide distribution in the genome, presents a developmental challenge: how are these ever-changing odorant receptor repertoires coordinated within the olfactory system? A central organizing principle in olfaction is the specialization of sensory neurons resulting from each sensory neuron expressing only ~one odorant receptor allele. In this review, we also discuss this mutually exclusive expression of odorant receptor genes. We have considered several models to account for co-regulation of odorant receptor repertoires, as well as discussed a new hypothesis that invokes important epigenetic properties of the system.

  1. Evaluating the electricity intensity of evolving water supply mixes: the case of California’s water network

    Science.gov (United States)

    Stokes-Draut, Jennifer; Taptich, Michael; Kavvada, Olga; Horvath, Arpad

    2017-11-01

    Climate change is making water supply less predictable, even unreliable, in parts of the world. Urban water providers, especially in already arid areas, will need to diversify their water resources by switching to alternative sources and negotiating trading agreements to create more resilient and interdependent networks. The increasing complexity of these networks will likely require more operational electricity. The ability to document, visualize, and analyze water-energy relationships will be critical to future water planning, especially as data needed to conduct the analyses become increasingly available. We have developed a network model and decision-support tool, WESTNet, to perform these tasks. Herein, WESTNet was used to analyze a model of California’s 2010 urban water network as well as the projected system for 2020 and 2030. Results for California’s ten hydrologic regions show that the average number of water sources per utility and total electricity consumption for supplying water will increase in spite of decreasing per-capita water consumption. Electricity intensity (kWh m-3) will increase in arid regions of the state due to shifts to alternative water sources such as indirect potable water reuse, desalination, and water transfers. In wetter, typically less populated, regions, reduced water demand for electricity-intensive supplies will decrease the electricity intensity of the water supply mix, though total electricity consumption will increase due to urban population growth. The results of this study provide a baseline for comparing current and potential innovations to California’s water system. The WESTNet tool can be applied to diverse water systems in any geographic region at a variety of scales to evaluate an array of network-dependent water-energy parameters.

  2. Growing networks with mixed attachment mechanisms

    International Nuclear Information System (INIS)

    Shao Zhigang; Zou Xianwu; Tan Zhijie; Jin Zhunzhi

    2006-01-01

    Networks grow and evolve when new nodes and links are added in. There are two methods to add the links: uniform attachment and preferential attachment. We take account of the addition of links with mixed attachment between uniform attachment and preferential attachment in proportion. By using numerical simulations and analysis based on a continuum theory, we obtain that the degree distribution P(k) has an extended power-law form P(k) ∼ (k + k 0 ) -γ . When the number of edges k of a node is much larger than a certain value k 0 , the degree distribution reduces to the power-law form P(k) ∼ k -γ ; and when k is much smaller than k 0 , the degree distribution degenerates into the exponential form P(k)∼exp(-yk/k 0 ). It has been found that degree distribution possesses this extended power-law form for many real networks, such as the movie actor network, the citation network of scientific papers and diverse protein interaction networks

  3. Gigabit network technology. Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    Davenport, C.M.C. [ed.

    1996-10-01

    Current digital networks are evolving toward distributed multimedia with a wide variety of applications with individual data rates ranging from kb/sec to tens and hundreds of Mb/sec. Link speed requirements are pushing into the Gb/sec range and beyond the envelop of electronic networking capabilities. There is a vast amount of untapped bandwidth available in the low-attenuation communication bands of an optical fiber. The capacity in one fiber thread is enough to carry more than two thousand times as much information as all the current radio and microwave frequencies. And while fiber optics has replaced copper wire as the transmission medium of choice, the communication capacity of conventional fiber optic networks is ultimately limited by electronic processing speeds.

  4. Self-Awareness in Computer Networks

    Directory of Open Access Journals (Sweden)

    Ariane Keller

    2014-01-01

    Full Text Available The Internet architecture works well for a wide variety of communication scenarios. However, its flexibility is limited because it was initially designed to provide communication links between a few static nodes in a homogeneous network and did not attempt to solve the challenges of today’s dynamic network environments. Although the Internet has evolved to a global system of interconnected computer networks, which links together billions of heterogeneous compute nodes, its static architecture remained more or less the same. Nowadays the diversity in networked devices, communication requirements, and network conditions vary heavily, which makes it difficult for a static set of protocols to provide the required functionality. Therefore, we propose a self-aware network architecture in which protocol stacks can be built dynamically. Those protocol stacks can be optimized continuously during communication according to the current requirements. For this network architecture we propose an FPGA-based execution environment called EmbedNet that allows for a dynamic mapping of network protocols to either hardware or software. We show that our architecture can reduce the communication overhead significantly by adapting the protocol stack and that the dynamic hardware/software mapping of protocols considerably reduces the CPU load introduced by packet processing.

  5. Evolution under changing climates: climatic niche stasis despite rapid evolution in a non-native plant.

    Science.gov (United States)

    Alexander, Jake M

    2013-09-22

    A topic of great current interest is the capacity of populations to adapt genetically to rapidly changing climates, for example by evolving the timing of life-history events, but this is challenging to address experimentally. I use a plant invasion as a model system to tackle this question by combining molecular markers, a common garden experiment and climatic niche modelling. This approach reveals that non-native Lactuca serriola originates primarily from Europe, a climatic subset of its native range, with low rates of admixture from Asia. It has rapidly refilled its climatic niche in the new range, associated with the evolution of flowering phenology to produce clines along climate gradients that mirror those across the native range. Consequently, some non-native plants have evolved development times and grow under climates more extreme than those found in Europe, but not among populations from the native range as a whole. This suggests that many plant populations can adapt rapidly to changed climatic conditions that are already within the climatic niche space occupied by the species elsewhere in its range, but that evolution to conditions outside of this range is more difficult. These findings can also help to explain the prevalence of niche conservatism among non-native species.

  6. Evolving earth-based and in-situ satellite network architectures for Mars communications and navigation support

    Science.gov (United States)

    Hastrup, Rolf; Weinberg, Aaron; McOmber, Robert

    1991-09-01

    Results of on-going studies to develop navigation/telecommunications network concepts to support future robotic and human missions to Mars are presented. The performance and connectivity improvements provided by the relay network will permit use of simpler, lower performance, and less costly telecom subsystems for the in-situ mission exploration elements. Orbiting relay satellites can serve as effective navigation aids by supporting earth-based tracking as well as providing Mars-centered radiometric data for mission elements approaching, in orbit, or on the surface of Mars. The relay satellite orbits may be selected to optimize navigation aid support and communication coverage for specific mission sets.

  7. Opinion formation and distribution in a bounded-confidence model on various networks

    Science.gov (United States)

    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.

  8. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  9. Evolving Intelligent Systems Methodology and Applications

    CERN Document Server

    Angelov, Plamen; Kasabov, Nik

    2010-01-01

    From theory to techniques, the first all-in-one resource for EIS. There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on th

  10. Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

    Directory of Open Access Journals (Sweden)

    Danielle S Bassett

    2010-04-01

    Full Text Available Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.

  11. Global Operations Networks in Motion

    DEFF Research Database (Denmark)

    Slepniov, Dmitrij; Jørgensen, Claus; Wæhrens, Brian Vejrum

    2009-01-01

    This paper addresses the phenomenon of global operations networks and how they change over time. The paper is based on the cases of three Danish companies and their global operations networks. It finds a number of common patterns highlighting some organisational effects and managerial challenges...... the companies face regarding rapid changes in their networks configurations and capabilities. The paper details the variables determining these changes and suggests how the on-going interplay between the focal organisation, its network partners, and their various contextual conditions can be approached....

  12. Fluid limits for bandwidth-sharing networks with rate constraints

    NARCIS (Netherlands)

    M. Frolkova (Masha); J. Reed (Josh); A.P. Zwart (Bert)

    2013-01-01

    htmlabstractBandwidth-sharing networks as introduced by Massouli\\'e~\\& Roberts (1998) model the dynamic interaction among an evolving population of elastic flows competing for several links. With policies based on optimization procedures, such models are of interest both from a~Queueing Theory and

  13. Network-induced oscillatory behavior in material flow networks and irregular business cycles

    Science.gov (United States)

    Helbing, Dirk; Lämmer, Stefen; Witt, Ulrich; Brenner, Thomas

    2004-11-01

    Network theory is rapidly changing our understanding of complex systems, but the relevance of topological features for the dynamic behavior of metabolic networks, food webs, production systems, information networks, or cascade failures of power grids remains to be explored. Based on a simple model of supply networks, we offer an interpretation of instabilities and oscillations observed in biological, ecological, economic, and engineering systems. We find that most supply networks display damped oscillations, even when their units—and linear chains of these units—behave in a nonoscillatory way. Moreover, networks of damped oscillators tend to produce growing oscillations. This surprising behavior offers, for example, a different interpretation of business cycles and of oscillating or pulsating processes. The network structure of material flows itself turns out to be a source of instability, and cyclical variations are an inherent feature of decentralized adjustments.

  14. Methods Evolved by Observation

    Science.gov (United States)

    Montessori, Maria

    2016-01-01

    Montessori's idea of the child's nature and the teacher's perceptiveness begins with amazing simplicity, and when she speaks of "methods evolved," she is unveiling a methodological system for observation. She begins with the early childhood explosion into writing, which is a familiar child phenomenon that Montessori has written about…

  15. Deterministic bound for avionics switched networks according to networking features using network calculus

    Directory of Open Access Journals (Sweden)

    Feng HE

    2017-12-01

    Full Text Available The state of the art avionics system adopts switched networks for airborne communications. A major concern in the design of the networks is the end-to-end guarantee ability. Analytic methods have been developed to compute the worst-case delays according to the detailed configurations of flows and networks within avionics context, such as network calculus and trajectory approach. It still lacks a relevant method to make a rapid performance estimation according to some typically switched networking features, such as networking scale, bandwidth utilization and average flow rate. The goal of this paper is to establish a deterministic upper bound analysis method by using these networking features instead of the complete network configurations. Two deterministic upper bounds are proposed from network calculus perspective: one is for a basic estimation, and another just shows the benefits from grouping strategy. Besides, a mathematic expression for grouping ability is established based on the concept of network connecting degree, which illustrates the possibly minimal grouping benefit. For a fully connected network with 4 switches and 12 end systems, the grouping ability coming from grouping strategy is 15–20%, which just coincides with the statistical data (18–22% from the actual grouping advantage. Compared with the complete network calculus analysis method for individual flows, the effectiveness of the two deterministic upper bounds is no less than 38% even with remarkably varied packet lengths. Finally, the paper illustrates the design process for an industrial Avionics Full DupleX switched Ethernet (AFDX networking case according to the two deterministic upper bounds and shows that a better control for network connecting, when designing a switched network, can improve the worst-case delays dramatically. Keywords: Deterministic bound, Grouping ability, Network calculus, Networking features, Switched networks

  16. Molecular evolution in court: analysis of a large hepatitis C virus outbreak from an evolving source.

    Science.gov (United States)

    González-Candelas, Fernando; Bracho, María Alma; Wróbel, Borys; Moya, Andrés

    2013-07-19

    Molecular phylogenetic analyses are used increasingly in the epidemiological investigation of outbreaks and transmission cases involving rapidly evolving RNA viruses. Here, we present the results of such an analysis that contributed to the conviction of an anesthetist as being responsible for the infection of 275 of his patients with hepatitis C virus. We obtained sequences of the NS5B and E1-E2 regions in the viral genome for 322 patients suspected to have been infected by the doctor, and for 44 local, unrelated controls. The analysis of 4,184 cloned sequences of the E1-E2 region allowed us to exclude 47 patients from the outbreak. A subset of patients had known dates of infection. We used these data to calibrate a relaxed molecular clock and to determine a rough estimate of the time of infection for each patient. A similar analysis led to an estimate for the time of infection of the source. The date turned out to be 10 years before the detection of the outbreak. The number of patients infected was small at first, but it increased substantially in the months before the detection of the outbreak. We have developed a procedure to integrate molecular phylogenetic reconstructions of rapidly evolving viral populations into a forensic setting adequate for molecular epidemiological analysis of outbreaks and transmission events. We applied this procedure to a large outbreak of hepatitis C virus caused by a single source and the results obtained played a key role in the trial that led to the conviction of the suspected source.

  17. High-Performance Networking

    CERN Multimedia

    CERN. Geneva

    2003-01-01

    The series will start with an historical introduction about what people saw as high performance message communication in their time and how that developed to the now to day known "standard computer network communication". It will be followed by a far more technical part that uses the High Performance Computer Network standards of the 90's, with 1 Gbit/sec systems as introduction for an in depth explanation of the three new 10 Gbit/s network and interconnect technology standards that exist already or emerge. If necessary for a good understanding some sidesteps will be included to explain important protocols as well as some necessary details of concerned Wide Area Network (WAN) standards details including some basics of wavelength multiplexing (DWDM). Some remarks will be made concerning the rapid expanding applications of networked storage.

  18. Software Defined Networking for Next Generation Converged Metro-Access Networks

    Science.gov (United States)

    Ruffini, M.; Slyne, F.; Bluemm, C.; Kitsuwan, N.; McGettrick, S.

    2015-12-01

    While the concept of Software Defined Networking (SDN) has seen a rapid deployment within the data center community, its adoption in telecommunications network has progressed slowly, although the concept has been swiftly adopted by all major telecoms vendors. This paper presents a control plane architecture for SDN-driven converged metro-access networks, developed through the DISCUS European FP7 project. The SDN-based controller architecture was developed in a testbed implementation targeting two main scenarios: fast feeder fiber protection over dual-homed Passive Optical Networks (PONs) and dynamic service provisioning over a multi-wavelength PON. Implementation details and results of the experiment carried out over the second scenario are reported in the paper, showing the potential of SDN in providing assured on-demand services to end-users.

  19. A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets

    Science.gov (United States)

    Chen, Jianrui; Wang, Hua; Wang, Lina; Liu, Weiwei

    2016-04-01

    Community detection in social networks has been intensively studied in recent years. In this paper, a novel similarity measurement is defined according to social balance theory for signed networks. Inter-community positive links are found and deleted due to their low similarity. The positive neighbor sets are reconstructed by this method. Then, differential equations are proposed to imitate the constantly changing states of nodes. Each node will update its state based on the difference between its state and average state of its positive neighbors. Nodes in the same community will evolve together with time and nodes in the different communities will evolve far away. Communities are detected ultimately when states of nodes are stable. Experiments on real world and synthetic networks are implemented to verify detection performance. The thorough comparisons demonstrate the presented method is more efficient than two acknowledged better algorithms.

  20. Orbital Decay in Binaries with Evolved Stars

    Science.gov (United States)

    Sun, Meng; Arras, Phil; Weinberg, Nevin N.; Troup, Nicholas; Majewski, Steven R.

    2018-01-01

    Two mechanisms are often invoked to explain tidal friction in binary systems. The ``dynamical tide” is the resonant excitation of internal gravity waves by the tide, and their subsequent damping by nonlinear fluid processes or thermal diffusion. The ``equilibrium tide” refers to non-resonant excitation of fluid motion in the star’s convection zone, with damping by interaction with the turbulent eddies. There have been numerous studies of these processes in main sequence stars, but less so on the subgiant and red giant branches. Motivated by the newly discovered close binary systems in the Apache Point Observatory Galactic Evolution Experiment (APOGEE-1), we have performed calculations of both the dynamical and equilibrium tide processes for stars over a range of mass as the star’s cease core hydrogen burning and evolve to shell burning. Even for stars which had a radiative core on the main sequence, the dynamical tide may have very large amplitude in the newly radiative core in post-main sequence, giving rise to wave breaking. The resulting large dynamical tide dissipation rate is compared to the equilibrium tide, and the range of secondary masses and orbital periods over which rapid orbital decay may occur will be discussed, as well as applications to close APOGEE binaries.