WorldWideScience

Sample records for underlying network organization

  1. Network planning under uncertainties

    Science.gov (United States)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a

  2. Organization Virtual or Networked?

    Directory of Open Access Journals (Sweden)

    Rūta Tamošiūnaitė

    2013-08-01

    Full Text Available Purpose—to present distinction between “virtual organization” and “networked organization”; giving their definitions.Design/methodology/approach—review of previous researches, systemic analyses of their findings and synthesis of distinctive characteristics of ”virtual organization” and “networked organization.”Findings—the main result of the research is key diverse features separating ”virtual organization” and ”networked organization.” Definitions of “virtual organization” and “networked organization” are presented.Originality/Value—distinction between “virtual organization” and “networked organization” creates possibilities to use all advantages of those types of organizations and gives foundation for deeper researches in this field.Research type: general review.

  3. Exploring network organization in practice

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    that there are different logical considerations when designing a network organization to facilitate innovation. I identify three types of network organizations: market-led, directed and culture-led network organizations. Different types of network organizations show that organizations are dual and even ternary systems...

  4. Evolution of metabolic network organization

    Directory of Open Access Journals (Sweden)

    Bonchev Danail

    2010-05-01

    Full Text Available Abstract Background Comparison of metabolic networks across species is a key to understanding how evolutionary pressures shape these networks. By selecting taxa representative of different lineages or lifestyles and using a comprehensive set of descriptors of the structure and complexity of their metabolic networks, one can highlight both qualitative and quantitative differences in the metabolic organization of species subject to distinct evolutionary paths or environmental constraints. Results We used a novel representation of metabolic networks, termed network of interacting pathways or NIP, to focus on the modular, high-level organization of the metabolic capabilities of the cell. Using machine learning techniques we identified the most relevant aspects of cellular organization that change under evolutionary pressures. We considered the transitions from prokarya to eukarya (with a focus on the transitions among the archaea, bacteria and eukarya, from unicellular to multicellular eukarya, from free living to host-associated bacteria, from anaerobic to aerobic, as well as the acquisition of cell motility or growth in an environment of various levels of salinity or temperature. Intuitively, we expect organisms with more complex lifestyles to have more complex and robust metabolic networks. Here we demonstrate for the first time that such organisms are not only characterized by larger, denser networks of metabolic pathways but also have more efficiently organized cross communications, as revealed by subtle changes in network topology. These changes are unevenly distributed among metabolic pathways, with specific categories of pathways being promoted to more central locations as an answer to environmental constraints. Conclusions Combining methods from graph theory and machine learning, we have shown here that evolutionary pressures not only affects gene and protein sequences, but also specific details of the complex wiring of functional modules

  5. Self-organizing networks

    DEFF Research Database (Denmark)

    Marchetti, Nicola; Prasad, Neeli R.; Johansson, Johan

    2010-01-01

    In this paper, a general overview of Self-Organizing Networks (SON), and the rationale and state-of-the-art of wireless SON are first presented. The technical and business requirements are then briefly treated, and the research challenges within the field of SON are highlighted. Thereafter...

  6. Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme.

    Science.gov (United States)

    Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

    2015-01-01

    -associated cell network takes 54.5 years from a normal state to stage I cancer, 1.5 years from stage I to stage II cancer, and 2.5 years from stage II to stage III cancer, with a reasonable match for the statistical result of the average age of lung cancer. These results suggest that a robust negative feedback scheme, based on a stochastic evolutionary game strategy, plays a critical role in an evolutionary biological network of carcinogenesis under a natural selection scheme.

  7. Population dynamics, information transfer, and spatial organization in a chemical reaction network under spatial confinement and crowding conditions.

    Science.gov (United States)

    Bellesia, Giovanni; Bales, Benjamin B

    2016-10-01

    We investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been "extended" and considered as a prototype reaction-diffusion system. Our results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatial stochastic simulation methods for the study of biochemical networks in vivo where the "well-mixed" approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.

  8. Revisiting Network Organization in Practice

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    of the organizational designs, which we refer to duality of organization. In terms of duality of organization, there are three emerging patterns of duality, i.e. market-led, value-led and directed network organization. More important, we find that an organization is not only dual but also ternary since...

  9. Network Physiology: How Organ Systems Dynamically Interact.

    Science.gov (United States)

    Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  10. Organic-Inorganic hybrid networks

    Czech Academy of Sciences Publication Activity Database

    Matějka, Libor; Dukh, O.

    2001-01-01

    Roč. 171, - (2001), s. 181-188 ISSN 1022-1360. [Polymer Networks Group Meeting: Polymer Networks - Formation-Structure-Properties /15./. Rzeszów, 17.07.2000-21.07.2000] R&D Projects: GA ČR GA203/98/0884; GA AV ČR IAA4050008; GA AV ČR KSK2050602 Institutional research plan: CEZ:AV0Z4050913 Keywords : organic-inorganic networks * nanosized silica * mammalian cells Subject RIV: CD - Macromolecular Chemistry Impact factor: 0.634, year: 2001

  11. Organ trade using social networks.

    Science.gov (United States)

    Alrogy, Waleed; Jawdat, Dunia; Alsemari, Muhannad; Alharbi, Abdulrahman; Alasaad, Abdullah; Hajeer, Ali H

    2016-01-01

    Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30%) from donors or sellers, and 392 (70%) from recipients or buyers. On Twitter, we found 472 (85%) adverts, on Google answers 61 (11%), and on Facebook 24 (4%). Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  12. Organ trade using social networks

    Directory of Open Access Journals (Sweden)

    Waleed Alrogy

    2016-01-01

    Full Text Available Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30% from donors or sellers, and 392 (70% from recipients or buyers. On Twitter, we found 472 (85% adverts, on Google answers 61 (11%, and on Facebook 24 (4%. Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  13. Specifying Orchestrating Capability in Network Organization and Interfirm Innovation Networks

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    implements its blue ocean strategy through purposively build multi-level networks, i.e. an intra network organization and interfirm innovation networks. In order to get more innovation output from external and internal networks, orchestration capability is needed and should be applied both externally...

  14. Social network analysis of sustainable transportation organizations.

    Science.gov (United States)

    2012-07-15

    Studying how organizations communicate with each other can provide important insights into the influence, and policy success of different types of organizations. This study examines the communication networks of 121 organizations promoting sustainabl...

  15. Modular networks with hierarchical organization: The dynamical ...

    Indian Academy of Sciences (India)

    constraint optimization as shown by us previously. Keywords. Modular network; hierarchical organization; stability; robustness. PACS Nos 89.75.Hc; 05.45.-a; 89.75.Fb. 1. Introduction. Structural patterns in complex networks occurring in biological, ...

  16. Irreversible Conversion of a Water-Ethanol Solution into an Organized Two-Dimensional Network of Alternating Supramolecular Units in a Hydrophobic Zeolite under Pressure.

    Science.gov (United States)

    Arletti, Rossella; Fois, Ettore; Gigli, Lara; Vezzalini, Giovanna; Quartieri, Simona; Tabacchi, Gloria

    2017-02-13

    Turning disorder into organization is a key issue in science. By making use of X-ray powder diffraction and modeling studies, we show herein that high pressures in combination with the shape and space constraints of the hydrophobic all-silica zeolite ferrierite separate an ethanol-water liquid mixture into ethanol dimer wires and water tetramer squares. The confined supramolecular blocks alternate in a binary two-dimensional (2D) architecture that remains stable upon complete pressure release. These results support the combined use of high pressures and porous networks as a viable strategy for driving the organization of molecules or nano-objects towards complex, pre-defined patterns relevant for the realization of novel functional nanocomposites. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...

  18. Bridging Boundaries in Networked Military Organizations

    NARCIS (Netherlands)

    Kleij, R. van der; Broek, J. van den; Cornelissen, M.; Essens, P.J.D.M.

    2010-01-01

    One of the challenges facing networked military organizations is to coordinate and integrate activities of organization components. Several studies have demonstrated the importance of boundary spanning as integrative mechanism, and, more specifically, individual communication holes within

  19. Modular networks with hierarchical organization

    Indian Academy of Sciences (India)

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary ...

  20. Self-organized critical neural networks

    International Nuclear Information System (INIS)

    Bornholdt, Stefan; Roehl, Torsten

    2003-01-01

    A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

  1. Major component analysis of dynamic networks of physiologic organ interactions

    International Nuclear Information System (INIS)

    Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P

    2015-01-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)

  2. Major component analysis of dynamic networks of physiologic organ interactions

    Science.gov (United States)

    Liu, Kang K. L.; Bartsch, Ronny P.; Ma, Qianli D. Y.; Ivanov, Plamen Ch

    2015-09-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.

  3. Informal Networks in Organizations - A Literature Review

    DEFF Research Database (Denmark)

    Waldstrøm, Christian

    2001-01-01

    and assess the existing contributions to the understanding of these informal networks in organizations. The first part of the paper presents the key terms and concepts needed to understand social networks both in general and within the framework of formal organizations in particular. In the second part......In the increasingly complex and dynamic theories of modern organizations, there is a substantial lack of knowledge about the way things actually get done, and how individuals interact socially within the organizations to facilitate this. The primary goal of this paper is to identify, analyse......, the main characteristics of the informal networks are highlighted along with an analysis of the implications for managers and for the formal organization as a whole. Finally, some propositions about the importance of the informal networks are listed, as they form the basis for the indications of the future...

  4. Organization of growing random networks

    Energy Technology Data Exchange (ETDEWEB)

    Krapivsky, P. L.; Redner, S.

    2001-06-01

    The organizational development of growing random networks is investigated. These growing networks are built by adding nodes successively, and linking each to an earlier node of degree k with an attachment probability A{sub k}. When A{sub k} grows more slowly than linearly with k, the number of nodes with k links, N{sub k}(t), decays faster than a power law in k, while for A{sub k} growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A{sub k} is asymptotically linear, N{sub k}(t){similar_to}tk{sup {minus}{nu}}, with {nu} dependent on details of the attachment probability, but in the range 2{lt}{nu}{lt}{infinity}. The combined age and degree distribution of nodes shows that old nodes typically have a large degree. There is also a significant correlation in the degrees of neighboring nodes, so that nodes of similar degree are more likely to be connected. The size distributions of the in and out components of the network with respect to a given node{emdash}namely, its {open_quotes}descendants{close_quotes} and {open_quotes}ancestors{close_quotes}{emdash}are also determined. The in component exhibits a robust s{sup {minus}2} power-law tail, where s is the component size. The out component has a typical size of order lnt, and it provides basic insights into the genealogy of the network.

  5. 42 CFR 405.2112 - ESRD network organizations.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false ESRD network organizations. 405.2112 Section 405... End-Stage Renal Disease (ESRD) Services § 405.2112 ESRD network organizations. CMS will designate an administrative governing body (network organization) for each network. The functions of a network organization...

  6. Trade networks evolution under the conditions of stock market globalization

    Directory of Open Access Journals (Sweden)

    Kopylova Olga Volodymyrivna

    2016-12-01

    Full Text Available The modern perception of the stock market in terms of information technologies rapid development and under the institutionalists influence has been significantly modified and becomes multifaceted. It was detected that the main function of the market is activated, information asymmetry is minimized and more advanced financial architecture space is formed through trade networks. Formation of the modern trade networks has started on the basis of the old infrastructure, that had the highest tendency to self-organization and adaptation. The proposed architecture of trade networks of the stock market has a very clear vector of subordination – from top to bottom and has a number of positive points.

  7. Organization and scaling in water supply networks

    Science.gov (United States)

    Cheng, Likwan; Karney, Bryan W.

    2017-12-01

    Public water supply is one of the society's most vital resources and most costly infrastructures. Traditional concepts of these networks capture their engineering identity as isolated, deterministic hydraulic units, but overlook their physics identity as related entities in a probabilistic, geographic ensemble, characterized by size organization and property scaling. Although discoveries of allometric scaling in natural supply networks (organisms and rivers) raised the prospect for similar findings in anthropogenic supplies, so far such a finding has not been reported in public water or related civic resource supplies. Examining an empirical ensemble of large number and wide size range, we show that water supply networks possess self-organized size abundance and theory-explained allometric scaling in spatial, infrastructural, and resource- and emission-flow properties. These discoveries establish scaling physics for water supply networks and may lead to novel applications in resource- and jurisdiction-scale water governance.

  8. 42 CFR 121.13 - Definition of Human Organ Under section 301 of the National Organ Transplant Act, as amended.

    Science.gov (United States)

    2010-10-01

    ... National Organ Transplant Act, as amended. 121.13 Section 121.13 Public Health PUBLIC HEALTH SERVICE... NETWORK § 121.13 Definition of Human Organ Under section 301 of the National Organ Transplant Act, as amended. “Human organ,” as covered by section 301 of the National Organ Transplant Act, as amended, means...

  9. Flows in networks under fuzzy conditions

    CERN Document Server

    Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich

    2017-01-01

    This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...

  10. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

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

  11. Complex networks under dynamic repair model

    Science.gov (United States)

    Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

    2018-01-01

    Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

  12. Strategies for optical transport network recovery under epidemic network failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova; Kosteas, Vasileios

    2015-01-01

    are evaluated under multiple correlated large-scale failures. We employ the Susceptible–Infected– Disabled epidemic failure spreading model and look into possible trade-offs between resiliency and resource effi- ciency. Via extensive simulations, we show that source rerouting outperforms on-site rerouting......The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust......, and that there exist a clear trade-off between policy performance and network resource consumption, which must be addressed by network operators for improved robustness of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections...

  13. Robustness of Dengue Complex Network under Targeted versus Random Attack

    Directory of Open Access Journals (Sweden)

    Hafiz Abid Mahmood Malik

    2017-01-01

    Full Text Available Dengue virus infection is one of those epidemic diseases that require much consideration in order to save the humankind from its unsafe impacts. According to the World Health Organization (WHO, 3.6 billion individuals are at risk because of the dengue virus sickness. Researchers are striving to comprehend the dengue threat. This study is a little commitment to those endeavors. To observe the robustness of the dengue network, we uprooted the links between nodes randomly and targeted by utilizing different centrality measures. The outcomes demonstrated that 5% targeted attack is equivalent to the result of 65% random assault, which showed the topology of this complex network validated a scale-free network instead of random network. Four centrality measures (Degree, Closeness, Betweenness, and Eigenvector have been ascertained to look for focal hubs. It has been observed through the results in this study that robustness of a node and links depends on topology of the network. The dengue epidemic network presented robust behaviour under random attack, and this network turned out to be more vulnerable when the hubs of higher degree have higher probability to fail. Moreover, representation of this network has been projected, and hub removal impact has been shown on the real map of Gombak (Malaysia.

  14. Ecological Networks and Neighborhood Social Organization.

    Science.gov (United States)

    Browning, Christopher R; Calder, Catherine A; Soller, Brian; Jackson, Aubrey L; Dirlam, Jonathan

    2017-05-01

    Drawing on the social disorganization tradition and the social ecological perspective of Jane Jacobs, the authors hypothesize that neighborhoods composed of residents who intersect in space more frequently as a result of routine activities will exhibit higher levels of collective efficacy, intergenerational closure, and social network interaction and exchange. They develop this approach employing the concept of ecological networks-two-mode networks that indirectly link residents through spatial overlap in routine activities. Using data from the Los Angeles Family and Neighborhood Survey, they find evidence that econetwork extensity (the average proportion of households in the neighborhood to which a given household is tied through any location) and intensity (the degree to which household dyads are characterized by ties through multiple locations) are positively related to changes in social organization between 2000-2001 and 2006-2008. These findings demonstrate the relevance of econetwork characteristics-heretofore neglected in research on urban neighborhoods-for consequential dimensions of neighborhood social organization.

  15. Dynamical networks with topological self-organization

    Science.gov (United States)

    Zak, M.

    2001-01-01

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

  16. Growth, collapse, and self-organized criticality in complex networks

    Science.gov (United States)

    Wang, Yafeng; Fan, Huawei; Lin, Weijie; Lai, Ying-Cheng; Wang, Xingang

    2016-01-01

    Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well as sustainability science and engineering. We address the question of whether a complex network of nonlinear oscillators can maintain its synchronization stability as it expands. We find that a large scale avalanche over the entire network can be triggered in the sense that the individual nodal dynamics diverges from the synchronous state in a cascading manner within a relatively short time period. In particular, after an initial stage of linear growth, the network typically evolves into a critical state where the addition of a single new node can cause a group of nodes to lose synchronization, leading to synchronization collapse for the entire network. A statistical analysis reveals that the collapse size is approximately algebraically distributed, indicating the emergence of self-organized criticality. We demonstrate the generality of the phenomenon of synchronization collapse using a variety of complex network models, and uncover the underlying dynamical mechanism through an eigenvector analysis. PMID:27079515

  17. Nutritional status, brain network organization, and general intelligence.

    Science.gov (United States)

    Zamroziewicz, Marta K; Talukdar, M Tanveer; Zwilling, Chris E; Barbey, Aron K

    2017-11-01

    The high energy demands of the brain underscore the importance of nutrition in maintaining brain health and further indicate that aspects of nutrition may optimize brain health, in turn enhancing cognitive performance. General intelligence represents a critical cognitive ability that has been well characterized by cognitive neuroscientists and psychologists alike, but the extent to which a driver of brain health, namely nutritional status, impacts the neural mechanisms that underlie general intelligence is not understood. This study therefore examined the relationship between the intrinsic connectivity networks supporting general intelligence and nutritional status, focusing on nutrients known to impact the metabolic processes that drive brain function. We measured general intelligence, favorable connective architecture of seven intrinsic connectivity networks, and seventeen plasma phospholipid monounsaturated and saturated fatty acids in a sample of 99 healthy, older adults. A mediation analysis was implemented to investigate the relationship between empirically derived patterns of fatty acids, general intelligence, and underlying intrinsic connectivity networks. The mediation analysis revealed that small world propensity within one intrinsic connectivity network supporting general intelligence, the dorsal attention network, was promoted by a pattern of monounsaturated fatty acids. These results suggest that the efficiency of functional organization within a core network underlying general intelligence is influenced by nutritional status. This report provides a novel connection between nutritional status and functional network efficiency, and further supports the promise and utility of functional connectivity metrics in studying the impact of nutrition on cognitive and brain health. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. [Cystic fibrosis: centers and care networks organization].

    Science.gov (United States)

    Bellon, G

    2012-05-01

    More than 20 years after the gene discovery, without specific treatment, the observed improvement of the cystic fibrosis prognosis appears due to management's organization as well as early diagnosis (neonatal screening) or progress in symptomatic treatment. The CF Centers (CRCM) official recognition was a necessary step before generalization of routine neonatal screening (October, 2002). Actually French CF management relies on three levels of organization: CF centers, regional care networks and French CF Society, in close relationship with patients association (Vaincre la Mucoviscidose). Copyright © 2012 Elsevier Masson SAS. All rights reserved.

  19. EHV network operation, maintenance, organization and training

    Energy Technology Data Exchange (ETDEWEB)

    Gravier, J.P. [Electricite de France (EDF), 75 - Paris (France)

    1994-12-31

    The service interruptions of electricity have an ever increasing social and industrial impact, it is thus fundamental to operate the network to its best level of performances. To face these changing conditions, Electricite de France has consequently adapted its strategy to improve its organization for maintenance and operation, clarify the operation procedures and give further training to the staff. This work presents the above mentioned issues. (author) 2 figs.

  20. Supply chain network design under uncertainty

    DEFF Research Database (Denmark)

    Govindan, Kannan; Fattahi, Mohammad; Keyvanshokooh, Esmaeil

    2017-01-01

    Supply chain network design (SCND) is one of the most crucial planning problems in supply chain management (SCM). Nowadays, design decisions should be viable enough to function well under complex and uncertain business environments for many years or decades. Therefore, it is essential to make...... programming, risk-averse stochastic programming, robust optimization, and fuzzy mathematical programming are explored in terms of mathematical modeling and solution approaches. Finally, the drawbacks and missing aspects of the related literature are highlighted and a list of potential issues for future...

  1. Brain rhythms reveal a hierarchical network organization.

    Directory of Open Access Journals (Sweden)

    G Karl Steinke

    2011-10-01

    Full Text Available Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or "virtual brains", whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic, in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states

  2. Network Performance Improvement under Epidemic Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2013-01-01

    In this paper we investigate epidemic failure spreading in large- scale GMPLS-controlled transport networks. By evaluating the effect of the epidemic failure spreading on the network, we design several strategies for cost-effective network performance improvement via differentiated repair times....... First we identify the most vulnerable and the most strategic nodes in the network. Then, via extensive simulations we show that strategic placement of resources for improved failure recovery has better performance than randomly assigning lower repair times among the network nodes. Our OPNET simulation...... model can be used during the network planning process for facilitating cost- effective network survivability design....

  3. Network attributes underlying intellectual giftedness in the developing brain.

    Science.gov (United States)

    Ma, Jiyoung; Kang, Hee Jin; Kim, Jung Yoon; Jeong, Hyeonseok S; Im, Jooyeon Jamie; Namgung, Eun; Kim, Myeong Ju; Lee, Suji; Kim, Tammy D; Oh, Jin Kyoung; Chung, Yong-An; Lyoo, In Kyoon; Lim, Soo Mee; Yoon, Sujung

    2017-09-12

    Brain network is organized to maximize the efficiency of both segregated and integrated information processing that may be related to human intelligence. However, there have been surprisingly few studies that focus on the topological characteristics of brain network underlying extremely high intelligence that is intellectual giftedness, particularly in adolescents. Here, we examined the network topology in 25 adolescents with superior intelligence (SI-Adol), 25 adolescents with average intelligence (AI-Adol), and 27 young adults with AI (AI-Adult). We found that SI-Adol had network topological properties of high global efficiency as well as high clustering with a low wiring cost, relative to AI-Adol. However, contrary to the suggested role that brain hub regions play in general intelligence, the network efficiency of rich club connection matrix, which represents connections among brain hubs, was low in SI-Adol in comparison to AI-Adol. Rather, a higher level of local connection density was observed in SI-Adol than in AI-Adol. The highly intelligent brain may not follow this efficient yet somewhat stereotypical process of information integration entirely. Taken together, our results suggest that a highly intelligent brain may communicate more extensively, while being less dependent on rich club communications during adolescence.

  4. Scaling of differentiation in networks: nervous systems, organisms, ant colonies, ecosystems, businesses, universities, cities, electronic circuits, and Legos.

    Science.gov (United States)

    Changizi, M A; McDannald, M A; Widders, D

    2002-09-21

    Nodes in networks are often of different types, and in this sense networks are differentiated. Here we examine the relationship between network differentiation and network size in networks under economic or natural selective pressure, such as electronic circuits (networks of electronic components), Legos (networks of Lego pieces), businesses (networks of employees), universities (networks of faculty), organisms (networks of cells), ant colonies (networks of ants), and nervous systems (networks of neurons). For each of these we find that (i) differentiation increases with network size, and (ii) the relationship is consistent with a power law. These results are explained by a hypothesis that, because nodes are costly to build and maintain in such "selected networks", network size is optimized, and from this the power-law relationship may be derived. The scaling exponent depends on the particular kind of network, and is determined by the degree to which nodes are used in a combinatorial fashion to carry out network-level functions. We find that networks under natural selection (organisms, ant colonies, and nervous systems) have much higher combinatorial abilities than the networks for which human ingenuity is involved (electronic circuits, Legos, businesses, and universities). A distinct but related optimization hypothesis may be used to explain scaling of differentiation in competitive networks (networks where the nodes themselves, rather than the entire network, are under selective pressure) such as ecosystems (networks of organisms).

  5. Tau can switch microtubule network organizations: from random networks to dynamic and stable bundles.

    Science.gov (United States)

    Prezel, Elea; Elie, Auréliane; Delaroche, Julie; Stoppin-Mellet, Virginie; Bosc, Christophe; Serre, Laurence; Fourest-Lieuvin, Anne; Andrieux, Annie; Vantard, Marylin; Arnal, Isabelle

    2018-01-15

    In neurons, microtubule networks alternate between single filaments and bundled arrays under the influence of effectors controlling their dynamics and organization. Tau is a microtubule bundler that stabilizes microtubules by stimulating growth and inhibiting shrinkage. The mechanisms by which tau organizes microtubule networks remain poorly understood. Here, we studied the self-organization of microtubules growing in the presence of tau isoforms and mutants. The results show that tau's ability to induce stable microtubule bundles requires two hexapeptides located in its microtubule-binding domain and is modulated by its projection domain. Site-specific pseudophosphorylation of tau promotes distinct microtubule organizations: stable single microtubules, stable bundles, or dynamic bundles. Disease-related tau mutations increase the formation of highly dynamic bundles. Finally, cryo-electron microscopy experiments indicate that tau and its variants similarly change the microtubule lattice structure by increasing both the protofilament number and lattice defects. Overall, our results uncover novel phosphodependent mechanisms governing tau's ability to trigger microtubule organization and reveal that disease-related modifications of tau promote specific microtubule organizations that may have a deleterious impact during neurodegeneration. © 2018 Prezel, Elie, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. Identification of inter-organ vascular network: vessels bridging between organs.

    Science.gov (United States)

    Omae, Madoka; Takada, Norio; Yamamoto, Shohei; Nakajima, Hiroyuki; Sato, Thomas N

    2013-01-01

    Development and homeostasis of organs and whole body is critically dependent on the circulatory system. In particular, the circulatory system, the railways shuttling oxygen and nutrients among various organs, is indispensible for inter-organ humoral communication. Since the modern view of the anatomy and mechanics of the circulatory system was established in 17(th) century, it has been assumed that humoral factors are carried to and from organs via vascular branches of the central arteries and veins running along the body axis. Over the past few decades, major advances have been made in understanding molecular and cellular mechanisms underlying the vascularization of organs. However, very little is known about how each organ is linked by vasculature (i.e., inter-organ vascular networks). In fact, the exact anatomy of inter-organ vascular networks has remained obscure. Herein, we report the identification of four distinct vessels, V1(LP), V2(LP), V3(LP) and V4(LP), that bridge between two organs, liver and pancreas in developing zebrafish. We found that these inter-organ vessels can be classified into two types: direct and indirect types. The direct type vessels are those that bridge between two organs via single distinct vessel, to which V1(LP) and V2(LP) vessels belong. The indirect type bridges between two organs via separate branches that emanate from a stem vessel, and V3(LP) and V4(LP) vessels belong to this type. Our finding of V1(LP), V2(LP), V3(LP) and V4(LP) vessels provides the proof of the existence of inter-organ vascular networks. These and other yet-to-be-discovered inter-organ vascular networks may facilitate the direct exchange of humoral factors that are necessary for the coordinated growth, differentiation and homeostasis of the connected organs. It is also possible that the inter-organ vessels serve as tracks for their connected organs to follow during their growth to establish their relative positions and size differences.

  7. Identification of inter-organ vascular network: vessels bridging between organs.

    Directory of Open Access Journals (Sweden)

    Madoka Omae

    Full Text Available Development and homeostasis of organs and whole body is critically dependent on the circulatory system. In particular, the circulatory system, the railways shuttling oxygen and nutrients among various organs, is indispensible for inter-organ humoral communication. Since the modern view of the anatomy and mechanics of the circulatory system was established in 17(th century, it has been assumed that humoral factors are carried to and from organs via vascular branches of the central arteries and veins running along the body axis. Over the past few decades, major advances have been made in understanding molecular and cellular mechanisms underlying the vascularization of organs. However, very little is known about how each organ is linked by vasculature (i.e., inter-organ vascular networks. In fact, the exact anatomy of inter-organ vascular networks has remained obscure. Herein, we report the identification of four distinct vessels, V1(LP, V2(LP, V3(LP and V4(LP, that bridge between two organs, liver and pancreas in developing zebrafish. We found that these inter-organ vessels can be classified into two types: direct and indirect types. The direct type vessels are those that bridge between two organs via single distinct vessel, to which V1(LP and V2(LP vessels belong. The indirect type bridges between two organs via separate branches that emanate from a stem vessel, and V3(LP and V4(LP vessels belong to this type. Our finding of V1(LP, V2(LP, V3(LP and V4(LP vessels provides the proof of the existence of inter-organ vascular networks. These and other yet-to-be-discovered inter-organ vascular networks may facilitate the direct exchange of humoral factors that are necessary for the coordinated growth, differentiation and homeostasis of the connected organs. It is also possible that the inter-organ vessels serve as tracks for their connected organs to follow during their growth to establish their relative positions and size differences.

  8. Functional brain networks develop from a "local to distributed" organization.

    Directory of Open Access Journals (Sweden)

    Damien A Fair

    2009-05-01

    Full Text Available The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI, graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength between regions close in anatomical space and 'integration' (an increased correlation strength between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults

  9. Network Performance Improvement under Epidemic Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2013-01-01

    In this paper we investigate epidemic failure spreading in large- scale GMPLS-controlled transport networks. By evaluating the effect of the epidemic failure spreading on the network, we design several strategies for cost-effective network performance improvement via differentiated repair times....... First we identify the most vulnerable and the most strategic nodes in the network. Then, via extensive simulations we show that strategic placement of resources for improved failure recovery has better performance than randomly assigning lower repair times among the network nodes. Our OPNET simulation...

  10. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    But, the inner interaction is always overlooked. Afterwards, the coloured network model has been brought in this scope by Wu et al [8]. A brief introduction of coloured network is reviewed as fol- lows: In social networks, there are many relationships between individuals, e.g., between schoolmates, relatives and collaborators.

  11. The stochastic network dynamics underlying perceptual discrimination

    Directory of Open Access Journals (Sweden)

    Genis Prat-Ortega

    2015-04-01

    Full Text Available The brain is able to interpret streams of high-dimensional ambiguous information and yield coherent percepts. The mechanisms governing sensory integration have been extensively characterized using time-varying visual stimuli (Britten et al. 1996; Roitman and Shadlen 2002, but some of the basic principles regarding the network dynamics underlying this process remain largely unknown. We captured the basic features of a neural integrator using three canonical one-dimensional models: (1 the Drift Diffusion Model (DDM, (2 the Perfect Integrator (PI which is a particular case of the DDM where the bounds are set to infinity and (3 the double-well potential (DW which captures the dynamics of the attractor networks (Wang 2002; Roxin and Ledberg 2008. Although these models has been widely studied (Bogacz et al. 2006; Roxin and Ledberg 2008; Gold and Shadlen 2002, it has been difficult to experimentally discriminate among them because most of the observables measured are only quantitatively different among these models (e.g. psychometric curves. Here we aim to find experimentally measurable quantities that can yield qualitatively different behaviors depending on the nature of the underlying network dynamics. We examined the categorization dynamics of these models in response to fluctuating stimuli of different duration (T. On each time step, stimuli are drawn from a Gaussian distribution N(μ, σ and the two stimulus categories are defined by μ > 0 and μ < 0. Psychometric curves can therefore be obtained by quantifying the probability of the integrator to yield one category versus μ . We find however that varying σ can reveal more clearly the differences among the different integrators. In the small σ regime, both the DW and the DDM perform transient integration and exhibit a decaying stimulus reverse correlation kernel revealing a primacy effect (Nienborg and Cumming 2009; Wimmer et al. 2015 . In the large σ regime, the integration in the DDM

  12. Optimization of temporal networks under uncertainty

    CERN Document Server

    Wiesemann, Wolfram

    2012-01-01

    Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization probl

  13. Impact of network topology on self-organized criticality

    Science.gov (United States)

    Hoffmann, Heiko

    2018-02-01

    The general mechanisms behind self-organized criticality (SOC) are still unknown. Several microscopic and mean-field theory approaches have been suggested, but they do not explain the dependence of the exponents on the underlying network topology of the SOC system. Here, we first report the phenomena that in the Bak-Tang-Wiesenfeld (BTW) model, sites inside an avalanche area largely return to their original state after the passing of an avalanche, forming, effectively, critically arranged clusters of sites. Then, we hypothesize that SOC relies on the formation process of these clusters, and present a model of such formation. For low-dimensional networks, we show theoretically and in simulation that the exponent of the cluster-size distribution is proportional to the ratio of the fractal dimension of the cluster boundary and the dimensionality of the network. For the BTW model, in our simulations, the exponent of the avalanche-area distribution matched approximately our prediction based on this ratio for two-dimensional networks, but deviated for higher dimensions. We hypothesize a transition from cluster formation to the mean-field theory process with increasing dimensionality. This work sheds light onto the mechanisms behind SOC, particularly, the impact of the network topology.

  14. EXPLORING THE ROLE OF BUSINESS SOCIAL NETWORKING FOR ORGANIZATIONS

    Directory of Open Access Journals (Sweden)

    Damjana Jerman

    2015-01-01

    Full Text Available This article explores the relationship between communication, with the emphasis on public relations, and social network perspectives. What, then, does social networking for business mean in communication, particularly in public relations? This paper argues that business social networking play an important role in improving organizations communications. The goal of our paper is to identify the basic characteristics of social networks and its role for public relations for the effective implementation of social networking initiatives and tools in the workplace. Business social networking tools such as Facebook and LinkedIn are being used by organizations to reach the corporate objectives and to create a positive company image. Specific social networks, such the personalised networks of influence, are perceived to be one of the main strategic resources for organizations.

  15. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

  16. Stochastic Online Learning in Dynamic Networks under Unknown Models

    Science.gov (United States)

    2016-08-02

    Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for...12211 Research Triangle Park, NC 27709-2211 Online learning , multi-armed bandit, dynamic networks REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S... Online Learning in Dynamic Networks under Unknown Models Report Title This research aims to develop fundamental theories and practical algorithms for

  17. Dissolution of covalent adaptable network polymers in organic solvent

    Science.gov (United States)

    Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

    2017-12-01

    It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.

  18. Hierarchical spatial organization of geographical networks

    Energy Technology Data Exchange (ETDEWEB)

    Travencolo, Bruno A N; Costa, Luciano da F [Cybernetic Vision Research Group, GII-IFSC, Universidade de Sao Paulo, Caixa Postal 369, Sao Carlos, SP, 13560-970 (Brazil)], E-mail: luciano@if.sc.usp.br

    2008-06-06

    In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

  19. Core-periphery organization of complex networks

    OpenAIRE

    Holme, Petter

    2005-01-01

    Networks may, or may not, be wired to have a core that is both itself densely connected and central in terms of graph distance. In this study we propose a coefficient to measure if the network has such a clear-cut core-periphery dichotomy. We measure this coefficient for a number of real-world and model networks and find that different classes of networks have their characteristic values. For example do geographical networks have a strong core-periphery structure, while the core-periphery str...

  20. How networks reshape organizations--for results.

    Science.gov (United States)

    Charan, R

    1991-01-01

    Recently a new term-networks-has entered the vocabulary of corporate renewal. Yet there remains much confusion over just what networks are and how they operate. Ram Charan, a leading international consultant, has spent four years observing and participating in the creation of networks at ten companies in North America and Europe. These companies--which include Conrail, Dun & Bradstreet Europe, Du Pont, and Royal Bank of Canada-are clear about why they are creating networks, what networks are, and how they operate. A network is recognized group of managers (seldom more than 100, often fewer than 25) assembled by the CEO. Membership criteria are simple but subtle: What select group of managers, by virtue of its business skills, personal motivations and drive, and control of resources is uniquely positioned to shape and deliver on the strategy? Networks begin to matter when they change behavior-the frequency, intensity, and honesty of the dialogue among managers on priority tasks. The process of building a network starts at the top. Senior managers work as change agents to build a new "social architecture." Once the network is in place, they play three additional roles: 1. Define with clarity the business outputs they expect of the network and the time frame in which they expect it to deliver. 2. Guarantee the visibility and free flow of information to all members of the network who need it. 3. Develop new criteria for performance evaluation that emphasize horizontal collaboration and leadership.

  1. Core-periphery organization of complex networks.

    Science.gov (United States)

    Holme, Petter

    2005-10-01

    Networks may, or may not, be wired to have a core that is both itself densely connected and central in terms of graph distance. In this study we propose a coefficient to measure if the network has such a clear-cut core-periphery dichotomy. We measure this coefficient for a number of real-world and model networks and find that different classes of networks have their characteristic values. Among other things we conclude that geographically embedded transportation networks have a strong core-periphery structure. We proceed to study radial statistics of the core, i.e., properties of the neighborhoods of the core vertices for increasing n. We find that almost all networks have unexpectedly many edges within n neighborhoods at a certain distance from the core suggesting an effective radius for nontrivial network processes.

  2. Self-organizing networks for extracting jet features

    International Nuclear Information System (INIS)

    Loennblad, L.; Peterson, C.; Pi, H.; Roegnvaldsson, T.

    1991-01-01

    Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b.c. and light quarks. (orig.)

  3. Self-organized topology of recurrence-based complex networks

    International Nuclear Information System (INIS)

    Yang, Hui; Liu, Gang

    2013-01-01

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks

  4. Self-organized topology of recurrence-based complex networks.

    Science.gov (United States)

    Yang, Hui; Liu, Gang

    2013-12-01

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

  5. Video interpretability rating scale under network impairments

    Science.gov (United States)

    Kreitmair, Thomas; Coman, Cristian

    2014-01-01

    This paper presents the results of a study of the impact of network transmission channel parameters on the quality of streaming video data. A common practice for estimating the interpretability of video information is to use the Motion Imagery Quality Equation (MIQE). MIQE combines a few technical features of video images (such as: ground sampling distance, relative edge response, modulation transfer function, gain and signal-to-noise ratio) to estimate the interpretability level. One observation of this study is that the MIQE does not fully account for video-specific parameters such as spatial and temporal encoding, which are relevant to appreciating degradations caused by the streaming process. In streaming applications the main artifacts impacting the interpretability level are related to distortions in the image caused by lossy decompression of video data (due to loss of information and in some cases lossy re-encoding by the streaming server). One parameter in MIQE that is influenced by network transmission errors is the Relative Edge Response (RER). The automated calculation of RER includes the selection of the best edge in the frame, which in case of network errors may be incorrectly associated with a blocked region (e.g. low resolution areas caused by loss of information). A solution is discussed in this document to address this inconsistency by removing corrupted regions from the image analysis process. Furthermore, a recommendation is made on how to account for network impairments in the MIQE, such that a more realistic interpretability level is estimated in case of streaming applications.

  6. Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions

    Science.gov (United States)

    Semenov, Sergey N.; Kraft, Lewis J.; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E.; Kang, Kyungtae; Fox, Jerome M.; Whitesides, George M.

    2016-09-01

    Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving

  7. Nanoporous ionic organic networks: from synthesis to materials applications

    OpenAIRE

    Sun, Jian-Ke; Antonietti, Markus; Yuan, Jiayin

    2016-01-01

    The past decade has witnessed rapid progress in the synthesis of nanoporous organic networks or polymer frameworks for various potential applications. Generally speaking, functionalization of porous networks to add extra properties and enhance materials performance could be achieved either during the pore formation (thus a concurrent approach) or by post-synthetic modification (a sequential approach). Nanoporous organic networks which include ion pairs bound in a covalent manner are of specia...

  8. Globalization of Innovation and the Rise of Network Organization

    DEFF Research Database (Denmark)

    Hu, Yimei

    2016-01-01

    ’s innovation purposes. Such organizational structure is contrast with traditional hierarchical organizational structure, and featured with flexibility, market mechanism, internal trust, etc. Secondly, a network organization refers to various forms of interorganizational designs such as strategic alliances......In order to cope with the fierce global competition, more and more multinational corporations thrive to gain and sustain their global competitive advantages through establishing a so-called network organization to facilitate global innovation. However, as a popular notion appearing in multiple...... theoretical streams, there exist distant and even highly debatable understandings on network organization. This chapter concludes with a three-level framework to facilitate our understanding on network organization. Firstly, a network organization can be an intraorganizational design to cope with firm...

  9. Organization of signal flow in directed networks

    International Nuclear Information System (INIS)

    Bányai, M; Bazsó, F; Négyessy, L

    2011-01-01

    Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps

  10. Social networks of professionals in health care organizations: a review.

    Science.gov (United States)

    Tasselli, Stefano

    2014-12-01

    In this article, we provide an overview of social network research in health care, with a focus on social interactions between professionals in organizations. We begin by introducing key concepts defining the social network approach, including network density, centrality, and brokerage. We then review past and current research on the antecedents of health care professionals' social networks-including demographic attributes, professional groups, and organizational arrangements-and their consequences-including satisfaction at work, leadership, behaviors, knowledge transfer, diffusion of innovation, and performance. Finally, we examine future directions for social network research in health care, focusing on micro-macro linkages and network dynamics. © The Author(s) 2014.

  11. Organizing Creativity : Creativity and Innovation under Constraints

    NARCIS (Netherlands)

    Caniëls, Marjolein C.J.; Rietzschel, Eric F.

    2015-01-01

    The best way of organizing creativity within organizations remains somewhat enigmatic to scholars, particularly when it comes to the role of constraints. On the one hand, creative organizations are often associated with freedom, autonomy, weak rules and few boundaries. On the other hand, several

  12. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  13. Antagonistic neural networks underlying differentiated leadership roles

    Science.gov (United States)

    Boyatzis, Richard E.; Rochford, Kylie; Jack, Anthony I.

    2014-01-01

    The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks – the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success. PMID:24624074

  14. Antagonistic Neural Networks Underlying Differentiated Leadership Roles

    Directory of Open Access Journals (Sweden)

    Richard Eleftherios Boyatzis

    2014-03-01

    Full Text Available The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950’s. Recent research in neuroscience suggests that the division between task oriented and socio-emotional oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks -- the Task Positive Network (TPN and the Default Mode Network (DMN. Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

  15. Antagonistic neural networks underlying differentiated leadership roles.

    Science.gov (United States)

    Boyatzis, Richard E; Rochford, Kylie; Jack, Anthony I

    2014-01-01

    The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks - the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

  16. Modular networks with hierarchical organization: The dynamical ...

    Indian Academy of Sciences (India)

    terms hierarchy and modularity have been used almost interchangeably, although, as shown in figure 1, they represent distinct properties of the network. However, it is interesting to note that these two properties have been found to coexist in many networks occurring in real life [3–6], including the Internet [7,8] and the ...

  17. Interaction intimacy organizes networks of antagonistic interactions in different ways.

    Science.gov (United States)

    Pires, Mathias M; Guimarães, Paulo R

    2013-01-06

    Interaction intimacy, the degree of biological integration between interacting individuals, shapes the ecology and evolution of species interactions. A major question in ecology is whether interaction intimacy also shapes the way interactions are organized within communities. We combined analyses of network structure and food web models to test the role of interaction intimacy in determining patterns of antagonistic interactions, such as host-parasite, predator-prey and plant-herbivore interactions. Networks describing interactions with low intimacy were more connected, more nested and less modular than high-intimacy networks. Moreover, the performance of the models differed across networks with different levels of intimacy. All models reproduced well low-intimacy networks, whereas the more elaborate models were also capable of reproducing networks depicting interactions with higher levels of intimacy. Our results indicate the key role of interaction intimacy in organizing antagonisms, suggesting that greater interaction intimacy might be associated with greater complexity in the assembly rules shaping ecological networks.

  18. SOUNET: Self-Organized Underwater Wireless Sensor Network.

    Science.gov (United States)

    Kim, Hee-Won; Cho, Ho-Shin

    2017-02-02

    In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

  19. SOUNET: Self-Organized Underwater Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Hee-won Kim

    2017-02-01

    Full Text Available In this paper, we propose an underwater wireless sensor network (UWSN named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR, and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

  20. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  1. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

    Science.gov (United States)

    Valdivieso Caraguay, Ángel Leonardo; García Villalba, Luis Javier

    2017-01-01

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors. PMID:28362346

  2. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Ángel Leonardo Valdivieso Caraguay

    2017-03-01

    Full Text Available This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.

  3. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks.

    Science.gov (United States)

    Caraguay, Ángel Leonardo Valdivieso; Villalba, Luis Javier García

    2017-03-31

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.

  4. GENASIS national and international monitoring networks for persistent organic pollutants

    Science.gov (United States)

    Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav

    2010-05-01

    Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a

  5. Nonprofit Organizations in Disaster Response and Management: A Network Analysis

    Directory of Open Access Journals (Sweden)

    NAIM KAPUCU

    2018-01-01

    Full Text Available This paper tracks changes in the national disaster management system with regard to the nonprofit sector by looking at the roles ascribed to nonprofit organizations in the Federal Response Plan (FRP, National Response Plan (NRP, and National Response Framework (NRF. Additionally, the data collected from news reports and organizational after action reports about the inter-organizational interactions of emergency management agencies during the September 11th attacks and Hurricane Katrina are analyzed by using network analysis tools. The findings of the study indicate that there has been an increase in the interactions of the National Voluntary Organizations Active in Disasters (NVOAD network member organizations on par with policy changes in the NRP to involve nonprofit organizations in the national disaster planning process. In addition, those organizations close to the center of the network experienced enhanced communication and resource acquisition allowing them to successfully accomplish their missions, a finding that supports the development of strong network connections.

  6. Intruder Activity Analysis under Unreliable Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Tae-Sic Yoo; Humberto E. Garcia

    2007-09-01

    This paper addresses the problem of counting intruder activities within a monitored domain by a sensor network. The deployed sensors are unreliable. We characterize imperfect sensors with misdetection and false-alarm probabilities. We model intruder activities with Markov Chains. A set of Hidden Markov Models (HMM) models the imperfect sensors and intruder activities to be monitored. A novel sequential change detection/isolation algorithm is developed to detect and isolate a change from an HMM representing no intruder activity to another HMM representing some intruder activities. Procedures for estimating the entry time and the trace of intruder activities are developed. A domain monitoring example is given to illustrate the presented concepts and computational procedures.

  7. Blue emitting organic semiconductors under high pressure

    DEFF Research Database (Denmark)

    Knaapila, Matti; Guha, Suchismita

    2016-01-01

    This review describes essential optical and emerging structural experiments that use high GPa range hydrostatic pressure to probe physical phenomena in blue-emitting organic semiconductors including π-conjugated polyfluorene and related compounds. The work emphasizes molecular structure and inter......This review describes essential optical and emerging structural experiments that use high GPa range hydrostatic pressure to probe physical phenomena in blue-emitting organic semiconductors including π-conjugated polyfluorene and related compounds. The work emphasizes molecular structure...

  8. Emotional intelligence skills for maintaining social networks in healthcare organizations.

    Science.gov (United States)

    Freshman, Brenda; Rubino, Louis

    2004-01-01

    For healthcare organizations to survive in these increasingly challenging times, leadership and management must face mounting interpersonal concerns. The authors present the boundaries of internal and external social networks with respect to leadership and managerial functions: Social networks within the organization are stretched by reductions in available resources and structural ambiguity, whereas external social networks are stressed by interorganizational competitive pressures. The authors present the development of emotional intelligence skills in employees as a strategic training objective that can strengthen the internal and external social networks of healthcare organizations. The authors delineate the unique functions of leadership and management with respect to the application of emotional intelligence skills and discuss training and future research implications for emotional intelligence skill sets and social networks.

  9. Extracting hierarchical organization of complex networks by dynamics towards synchronization

    Science.gov (United States)

    Wang, Xiao-Hua; Jiao, Li-Cheng; Wu, Jian-She

    2009-07-01

    Based on the dynamics towards synchronization in hierarchical networks, we present an efficient method for extracting hierarchical organization in complex network. In the synchronization process, hierarchical structures corresponding to well defined communities of nodes emerge in different time scales, ordered in a hierarchical way. Thus, a new strategy for quantifying the dissimilarity between a pair of nodes in networks is introduced according to their time scales of synchronization. Then, using such a dissimilarity measure in conjunction with a hierarchical clustering method, our extracting method is proposed. The performance of our approach is tested on a set of computer generated and real-world networks with known hierarchical organization. The results demonstrate that our method enables us to offer insight into the complex networks with a multi-scale description. In addition, using a criterion of modularity, the method can also accurately find community structures in complex networks.

  10. Link predication based on matrix factorization by fusion of multi class organizations of the network.

    Science.gov (United States)

    Jiao, Pengfei; Cai, Fei; Feng, Yiding; Wang, Wenjun

    2017-08-21

    Link predication aims at forecasting the latent or unobserved edges in the complex networks and has a wide range of applications in reality. Almost existing methods and models only take advantage of one class organization of the networks, which always lose important information hidden in other organizations of the network. In this paper, we propose a link predication framework which makes the best of the structure of networks in different level of organizations based on nonnegative matrix factorization, which is called NMF 3 here. We first map the observed network into another space by kernel functions, which could get the different order organizations. Then we combine the adjacency matrix of the network with one of other organizations, which makes us obtain the objective function of our framework for link predication based on the nonnegative matrix factorization. Third, we derive an iterative algorithm to optimize the objective function, which converges to a local optimum, and we propose a fast optimization strategy for large networks. Lastly, we test the proposed framework based on two kernel functions on a series of real world networks under different sizes of training set, and the experimental results show the feasibility, effectiveness, and competitiveness of the proposed framework.

  11. Soil management practices under organic farming

    Science.gov (United States)

    Aly, Adel; Chami Ziad, Al; Hamdy, Atef

    2015-04-01

    Organic farming methods combine scientific knowledge of ecology and modern technology with traditional farming practices based on naturally occurring biological processes. Soil building practices such as crop rotations, intercropping, symbiotic associations, cover crops, organic fertilizers and minimum tillage are central to organic practices. Those practices encourage soil formation and structure and creating more stable systems. In farm nutrient and energy cycling is increased and the retentive abilities of the soil for nutrients and water are enhanced. Such management techniques also play an important role in soil erosion control. The length of time that the soil is exposed to erosive forces is decreased, soil biodiversity is increased, and nutrient losses are reduced, helping to maintain and enhance soil productivity. Organic farming as systematized and certifiable approach for agriculture, there is no surprise that it faces some challenges among both farmers and public sector. This can be clearly demonstrated particularly in the absence of the essential conditions needed to implement successfully the soil management practices like green manure and composting to improve soil fertility including crop rotation, cover cropping and reduced tillage. Those issues beside others will be fully discussed highlighting their beneficial impact on the environmental soil characteristics. Keywords: soil fertility, organic matter, plant nutrition

  12. A network perspective on the processes of empowered organizations.

    Science.gov (United States)

    Neal, Zachary P

    2014-06-01

    Organizational empowerment is a multi-faceted concept that involves processes occurring both within and between organizations that facilitate achievement of their goals. This paper takes a closer look at three interorganizational processes that lead to empowered organizations: building alliances, getting the word out, and capturing others' attention. These processes are located within the broader nomological network of empowerment and organizational empowerment, and are linked to particular patterns of interorganizational relationships that facilitate organizations' ability to engage in them. A new network-based measure, γ-centrality, is introduced to capture the particular network structure associated with each process to be assessed. It is demonstrated first in a hypothetical organizational network, then applied to take a closer look at organizational empowerment in the context of a coordinating council composed of human service agencies. The paper concludes with a discussion of the implications of relationships between these processes, and the potential for unintended consequences in the empowerment of organizations.

  13. Modelling the self-organization and collapse of complex networks

    Indian Academy of Sciences (India)

    Modelling the self-organization and collapse of complex networks. Sanjay Jain Department of Physics and Astrophysics, University of Delhi Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore Santa Fe Institute, Santa Fe, New Mexico.

  14. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

    Science.gov (United States)

    Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M

    2016-01-01

    Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene

  15. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    Directory of Open Access Journals (Sweden)

    Aaron M. Prescott

    2016-08-01

    underlying ethylene signaling. Analysis of each network topology results in predictions about changes that occur in network components that can be experimentally tested to give insights into which, if either, network underlies ethylene responses.

  16. Worker autonomy and the drama of digital networks in organizations

    NARCIS (Netherlands)

    Brey, Philip A.E.

    1999-01-01

    This essay considers the impact of digital networks in organizations on worker autonomy. Worker autonomy, the control that workers have over their own work situation, is claimed in this essay to be a key determinant for the quality of work, as well as an important moral goal. Digital networks pose

  17. 5G heterogeneous networks self-organizing and optimization

    CERN Document Server

    Rong, Bo; Kadoch, Michel; Sun, Songlin; Li, Wenjing

    2016-01-01

    This SpringerBrief provides state-of-the-art technical reviews on self-organizing and optimization in 5G systems. It covers the latest research results from physical-layer channel modeling to software defined network (SDN) architecture. This book focuses on the cutting-edge wireless technologies such as heterogeneous networks (HetNets), self-organizing network (SON), smart low power node (LPN), 3D-MIMO, and more. It will help researchers from both the academic and industrial worlds to better understand the technical momentum of 5G key technologies.

  18. Evolution, hierarchy and modular organization in complex networks

    Science.gov (United States)

    Ravasz, Erzsebet

    2005-07-01

    Large systems in nature and civilization share some important organizing principles uncovered in the framework of complex network research. Here we aim to present a few advances in understanding the generic topological characteristics of these systems. We start with an introduction to basic concepts of network research, continuing with a repertoire of well studied network examples and a brief history of previous modelling efforts. Next, we present a detailed investigation of scientific collaboration networks, with special focus on the role of internal links in determining the networks's scaling properties, and on limitations of certain measurements imposed by the database. Many real networks in nature and society share two generic properties: they are scale free and they display a high degree of clustering. We show that the scale free nature and high clustering of real networks are the consequence of a hierarchical organization, implying that small groups of nodes form increasingly large groups in a hierarchical manner, while maintaining a scale free topology. In hierarchical networks the clustering coefficient follows a strict scaling law, which can be used to identify the presence of a hierarchical organization in real networks. We find that several real networks, such as the World Wide Web, actor network, the Internet at the domain level and the semantic web obey this scaling law, indicating that hierarchy is a fundamental characteristic of many complex systems. We then focus on the metabolic network of 43 distinct organisms and show that many small, highly connected topological modules combine in a hierarchical manner into larger, less cohesive units, their number and degree of clustering following a power law. Within Escherichia coli we find that the uncovered hierarchical modularity closely overlaps with known metabolic functions. We show that enzyme essentiality is not randomly distributed in the metabolic network, on the contrary, essential enzymes tend to

  19. Organization of physical interactomes as uncovered by network schemas.

    Science.gov (United States)

    Banks, Eric; Nabieva, Elena; Chazelle, Bernard; Singh, Mona

    2008-10-01

    Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks.

  20. Collaborative Networks for biodiversity domain organizations

    NARCIS (Netherlands)

    Ermilova, E.; Afsarmanesh, H.

    2010-01-01

    European scientific research and development organizations, operating in the domains of biology, ecology, and biodiversity, strongly need to cooperate/collaborate with other centers. Unavailability of interoperation infrastructure as well as the needed collaboration environment among research

  1. Molecular organic networks: A step beyond flatland

    Science.gov (United States)

    Buck, Manfred

    2017-12-01

    Non-covalent interactions can organize planar molecules into two-dimensional arrays. It has now been shown that such arrays can be combined at the solid-liquid interface into bilayered heterostructures.

  2. Development and Organization of Neural Networks.

    Science.gov (United States)

    1988-01-01

    Storage Density, Bachmann, C. M., Cooper, L. N, Dembo , A., and Zeitouni, 0., Proc. Natl. Acad. Sci., Vol. 84, pp. 7529-7531, November, 1987, also ARO...Technical Report, June 22,1987. General Potential Surfaces and Neural Networks, Dembo , A, Zeftounl, 0., to be published in Phys. Rev. A, also ARO...A Relaxation Model for Memory with High Storage Density, Bachmann, C. M., Cooper, L. N, Dembo , A., and Zeitouni, 0., Proc. Natl. Acad. Sci., Vol. 84

  3. Value Systems Alignment Analysis in Collaborative Networked Organizations Management

    Directory of Open Access Journals (Sweden)

    Patricia Macedo

    2017-11-01

    Full Text Available The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assist managers in virtual and networked organizations management. The implementation of the assessment and analysis methods is supported by a set of software services integrated in the information system that supports the management of the networked organizations. A case study in the solar energy sector was conducted, and the data collected through this study allow us to confirm the practical applicability of the proposed methods and the software services.

  4. Developing neuronal networks: self-organized criticality predicts the future.

    Science.gov (United States)

    Pu, Jiangbo; Gong, Hui; Li, Xiangning; Luo, Qingming

    2013-01-01

    Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and "aging" process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.

  5. Extracting vascular networks under physiological constraints via integer programming.

    Science.gov (United States)

    Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D; Xiao, Xianghui; Stock, Stuart R; Klohs, Jan; Székely, Gábor; Andres, Bjoern; Menze, Bjoern H

    2014-01-01

    We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography (μMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.

  6. Modular genetic regulatory networks increase organization during pattern formation.

    Science.gov (United States)

    Mohamadlou, Hamid; Podgorski, Gregory J; Flann, Nicholas S

    2016-08-01

    Studies have shown that genetic regulatory networks (GRNs) consist of modules that are densely connected subnetworks that function quasi-autonomously. Modules may be recognized motifs that comprise of two or three genes with particular regulatory functions and connectivity or be purely structural and identified through connection density. It is unclear what evolutionary and developmental advantages modular structure and in particular motifs provide that have led to this enrichment. This study seeks to understand how modules within developmental GRNs influence the complexity of multicellular patterns that emerge from the dynamics of the regulatory networks. We apply an algorithmic complexity to measure the organization of the patterns. A computational study was performed by creating Boolean intracellular networks within a simulated epithelial field of embryonic cells, where each cell contains the same network and communicates with adjacent cells using contact-mediated signaling. Intracellular networks with random connectivity were compared to those with modular connectivity and with motifs. Results show that modularity effects network dynamics and pattern organization significantly. In particular: (1) modular connectivity alone increases complexity in network dynamics and patterns; (2) bistable switch motifs simplify both the pattern and network dynamics; (3) all other motifs with feedback loops increase multicellular pattern complexity while simplifying the network dynamics; (4) negative feedback loops affect the dynamics complexity more significantly than positive feedback loops. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  7. The Influence of Social Networking Technology in an Engineering Organization

    Science.gov (United States)

    Tepaske, Derrick Marcus

    2013-01-01

    Computer facilitated Social Networking (SN) is becoming more prevalent in our society, both in our personal and professional lives. As its use grows, there is a desire to determine how it will impact an organization. If it can positively impact an organization then it is an initiative that could be embraced and leveraged for any number of business…

  8. The puzzling resilience of transnational organized criminal networks

    DEFF Research Database (Denmark)

    Leuprecht, Christian; Aulthouse, Andrew; Walther, Olivier

    2016-01-01

    Why is transnational organized crime so difficult to dismantle? While organized crime networks within states have received some attention, actual transnational operations have not. In this article, we study the transnational drug and gun trafficking operations of the Shower Posse, a violent inter...

  9. Robust Optimization of Fourth Party Logistics Network Design under Disruptions

    Directory of Open Access Journals (Sweden)

    Jia Li

    2015-01-01

    Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.

  10. Comparing Notes: Collaborative Networks, Breeding Environments, and Organized Crime

    Science.gov (United States)

    Hernández, Alejandro

    Collaborative network theory can be useful in refining current understanding of criminal networks and aid in understanding their evolution. Drug trafficking organizations that operate in the region directly north of Colombia’s Valle del Cauca department and the “collection agencies” that operate in the Colombian city of Cali have abandoned hierarchical organizational structures and have become networked-based entities. Through the exposition of Camarinha-Matos and Afsarmanesh’s business networking ideas, this chapter examines the similarities and differences between the application of collaborative networks in licit enterprises, such as small and medium enterprises in Europe, and how the networks might be used by illicit criminal enterprises in Colombia.

  11. Analysis and Reduction of Complex Networks Under Uncertainty.

    Energy Technology Data Exchange (ETDEWEB)

    Ghanem, Roger G [University of Southern California

    2014-07-31

    This effort was a collaboration with Youssef Marzouk of MIT, Omar Knio of Duke University (at the time at Johns Hopkins University) and Habib Najm of Sandia National Laboratories. The objective of this effort was to develop the mathematical and algorithmic capacity to analyze complex networks under uncertainty. Of interest were chemical reaction networks and smart grid networks. The statements of work for USC focused on the development of stochastic reduced models for uncertain networks. The USC team was led by Professor Roger Ghanem and consisted of one graduate student and a postdoc. The contributions completed by the USC team consisted of 1) methodology and algorithms to address the eigenvalue problem, a problem of significance in the stability of networks under stochastic perturbations, 2) methodology and algorithms to characterize probability measures on graph structures with random flows. This is an important problem in characterizing random demand (encountered in smart grid) and random degradation (encountered in infrastructure systems), as well as modeling errors in Markov Chains (with ubiquitous relevance !). 3) methodology and algorithms for treating inequalities in uncertain systems. This is an important problem in the context of models for material failure and network flows under uncertainty where conditions of failure or flow are described in the form of inequalities between the state variables.

  12. Network communities as a new form of social organization in conditions of postmodern

    Directory of Open Access Journals (Sweden)

    N. V. Burmaha

    2016-03-01

    Full Text Available This article deals with the approach to interpretation of essence of the network community concept in which we propose to consider it as a new form of social organization that is substantiated by the specificity of how our society is functioning in conditions of Postmodern. There were explored two main approaches to network communities studying: the first approach considers social networks in a classic, traditional interpretation of modernity as a special kind of social structure, and the second one represents social networks as a specific virtual formation, a social structure of virtual Internet reality. There were revealed some common features of a social organization and a network community: presence of permanent communication between members of the group, united by certain common interests and goals, as well as presence of the certain hierarchy among all members of the community, and the rules of conduct, implementation of communication. Distinctive features: network community is more informal, offers its members considerable leeway in the implementation of their own goals and satisfying the needs, full virtualization of communication absence of direct interaction during communication, under conditions where the main resource for the interchange in network communities is information. It was shown that in the process of emergence, development and distribution of network communities, the fundamental role is played by modern communications - namely, unification them in a stable set of interconnected networks and, in particular network communities.

  13. Dispersal governs the reorganization of ecological networks under environmental change.

    Science.gov (United States)

    Thompson, Patrick L; Gonzalez, Andrew

    2017-05-08

    Ecological networks, such as food webs, mutualist webs and host-parasite webs, are reorganizing as species abundances and spatial distributions shift in response to environmental change. Current theoretical expectations for how this reorganization will occur are available for competition or for parts of interaction networks, but these may not extend to more complex networks. Here we use metacommunity theory to develop new expectations for how complex networks will reorganize under environmental change, and show that dispersal is crucial for determining the degree to which networks will retain their composition and structure. When dispersal between habitat patches is low, all types of species interactions act as a strong determinant for whether species can colonize suitable habitats. This colonization resistance drives species turnover, which breaks apart current networks and leads to the formation of new networks. However, when dispersal rates are increased, colonists arrive in high abundance in habitats where they are well adapted, so interactions with resident species contribute less to colonization success. Dispersal ensures that species associations are maintained as they shift in space, so networks retain similar composition and structure. The crucial role of dispersal reinforces the need to manage habitat connectivity to sustain species and interaction diversity into the future.

  14. Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

    Science.gov (United States)

    Chen, Jian-Huai; Yao, Zhi-Jian; Qin, Jiao-Long; Yan, Rui; Hua, Ling-Ling; Lu, Qing

    2016-01-01

    Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network. PMID:26960371

  15. Autonomous self-organizing resource manager for multiple networked platforms

    Science.gov (United States)

    Smith, James F., III

    2002-08-01

    A fuzzy logic based expert system for resource management has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar autonomous naval platforms defending their group against attackers. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. This paper provides an overview of the resource manager including the four fuzzy decision trees that make up the resource manager; the fuzzy EA model; genetic algorithm based optimization; co-evolutionary data mining through gaming; and mathematical, computational and hardware based validation. Methods of automatically designing new multi-platform EA techniques are considered. The expert system runs on each defending platform rendering it an autonomous system requiring no human intervention. There is no commanding platform. Instead the platforms work cooperatively as a function of battlespace geometry; sensor data such as range, bearing, ID, uncertainty measures for sensor output; intelligence reports; etc. Computational experiments will show the defending networked platform's ability to self- organize. The platforms' ability to self-organize is illustrated through the output of the scenario generator, a software package that automates the underlying data mining problem and creates a computer movie of the platforms' interaction for evaluation.

  16. Hubs with network motifs organize modularity dynamically in the protein-protein interaction network of yeast.

    Science.gov (United States)

    Jin, Guangxu; Zhang, Shihua; Zhang, Xiang-Sun; Chen, Luonan

    2007-11-21

    It has been recognized that modular organization pervades biological complexity. Based on network analysis, 'party hubs' and 'date hubs' were proposed to understand the basic principle of module organization of biomolecular networks. However, recent study on hubs has suggested that there is no clear evidence for coexistence of 'party hubs' and 'date hubs'. Thus, an open question has been raised as to whether or not 'party hubs' and 'date hubs' truly exist in yeast interactome. In contrast to previous studies focusing on the partners of a hub or the individual proteins around the hub, our work aims to study the network motifs of a hub or interactions among individual proteins including the hub and its neighbors. Depending on the relationship between a hub's network motifs and protein complexes, we define two new types of hubs, 'motif party hubs' and 'motif date hubs', which have the same characteristics as the original 'party hubs' and 'date hubs' respectively. The network motifs of these two types of hubs display significantly different features in spatial distribution (or cellular localizations), co-expression in microarray data, controlling topological structure of network, and organizing modularity. By virtue of network motifs, we basically solved the open question about 'party hubs' and 'date hubs' which was raised by previous studies. Specifically, at the level of network motifs instead of individual proteins, we found two types of hubs, motif party hubs (mPHs) and motif date hubs (mDHs), whose network motifs display distinct characteristics on biological functions. In addition, in this paper we studied network motifs from a different viewpoint. That is, we show that a network motif should not be merely considered as an interaction pattern but be considered as an essential function unit in organizing modules of networks.

  17. Inferring the gene network underlying the branching of tomato inflorescence.

    Directory of Open Access Journals (Sweden)

    Laura Astola

    Full Text Available The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.

  18. Biophysical controls on organic carbon fluxes in fluvial networks

    Science.gov (United States)

    Battin, Tom J.; Kaplan, Louis A.; Findlay, Stuart; Hopkinson, Charles S.; Marti, Eugenia; Packman, Aaron I.; Newbold, J. Denis; Sabater, Francesc

    2008-02-01

    Metabolism of terrestrial organic carbon in freshwater ecosystems is responsible for a large amount of carbon dioxide outgassing to the atmosphere, in contradiction to the conventional wisdom that terrestrial organic carbon is recalcitrant and contributes little to the support of aquatic metabolism. Here, we combine recent findings from geophysics, microbial ecology and organic geochemistry to show geophysical opportunity and microbial capacity to enhance the net heterotrophy in streams, rivers and estuaries. We identify hydrological storage and retention zones that extend the residence time of organic carbon during downstream transport as geophysical opportunities for microorganisms to develop as attached biofilms or suspended aggregates, and to metabolize organic carbon for energy and growth. We consider fluvial networks as meta-ecosystems to include the acclimation of microbial communities in downstream ecosystems that enable them to exploit energy that escapes from upstream ecosystems, thereby increasing the overall energy utilization at the network level.

  19. ORGANIZATION OF NETWORKED LEARNING IN MEDICINE

    Directory of Open Access Journals (Sweden)

    V. V. Krasnov

    2015-05-01

    effective communication in the group; training in t h e use of tools, methodologies and techniques for distance communications solutions to educational problems; real distant work under th e supervision of a teacher; independent remote interaction. The results of experiments show t hat without th e formation of team interaction skills training effectiveness of the networ k is low.

  20. Reconstructing cerebrovascular networks under local physiological constraints by integer programming.

    Science.gov (United States)

    Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D; Xiao, Xianghui; Stock, Stuart R; Klohs, Jan; Székely, Gábor; Andres, Bjoern; Menze, Bjoern H

    2015-10-01

    We introduce a probabilistic approach to vessel network extraction that enforces physiological constraints on the vessel structure. The method accounts for both image evidence and geometric relationships between vessels by solving an integer program, which is shown to yield the maximum a posteriori (MAP) estimate to a probabilistic model. Starting from an overconnected network, it is pruning vessel stumps and spurious connections by evaluating the local geometry and the global connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network and learn the prior distributions of our probabilistic model and we perform experiments on in-vivo magnetic resonance microangiography (μMRA) images of mouse brains. We finally discuss properties of the networks obtained under different tracking and pruning approaches. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Hybrid Organic/Inorganic Thiol-ene-Based Photopolymerized Networks

    OpenAIRE

    Schreck, Kathleen M.; Leung, Diana; Bowman, Christopher N.

    2011-01-01

    The thiol-ene reaction serves as a more oxygen tolerant alternative to traditional (meth)acrylate chemistry for forming photopolymerized networks with numerous desirable attributes including energy absorption, optical clarity, and reduced shrinkage stress. However, when utilizing commercially available monomers, many thiol-ene networks also exhibit decreases in properties such as glass transition temperature (Tg) and crosslink density. In this study, hybrid organic/inorganic thiol-ene resins ...

  2. Organisms modeling: The question of radial basis function networks

    Directory of Open Access Journals (Sweden)

    Muzy Alexandre

    2014-01-01

    Full Text Available There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evalution of an usual machine learning technique (radial basis funtion(RBF networks in the context of systems and biological reactive organisms.

  3. 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

  4. Library User Education under the Circumstance of Network

    Science.gov (United States)

    Zhu, Tian-hui

    2009-01-01

    Based on the concept of user education, this paper discusses the necessity of user education in library under the circumstance of network, describes the contents and forms of user education and puts forward the problems that should be paid attention to during education. [This paper was supported by scientific research project of Qufu Normal…

  5. Security Evaluation of the Cyber Networks under Advanced Persistent Threats

    NARCIS (Netherlands)

    Yang, L.; Li, Pengdeng; Yang, Xiaofan; Tang, Yuan Yan

    2017-01-01

    Advanced persistent threats (APTs) pose a grave threat to cyberspace, because they deactivate all the conventional cyber defense mechanisms. This paper addresses the issue of evaluating the security of the cyber networks under APTs. For this purpose, a dynamic model capturing the APT-based

  6. Inferring dynamic gene networks under varying conditions for transcriptomic network comparison.

    Science.gov (United States)

    Shimamura, Teppei; Imoto, Seiya; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru

    2010-04-15

    Elucidating the differences between cellular responses to various biological conditions or external stimuli is an important challenge in systems biology. Many approaches have been developed to reverse engineer a cellular system, called gene network, from time series microarray data in order to understand a transcriptomic response under a condition of interest. Comparative topological analysis has also been applied based on the gene networks inferred independently from each of the multiple time series datasets under varying conditions to find critical differences between these networks. However, these comparisons often lead to misleading results, because each network contains considerable noise due to the limited length of the time series. We propose an integrated approach for inferring multiple gene networks from time series expression data under varying conditions. To the best of our knowledge, our approach is the first reverse-engineering method that is intended for transcriptomic network comparison between varying conditions. Furthermore, we propose a state-of-the-art parameter estimation method, relevance-weighted recursive elastic net, for providing higher precision and recall than existing reverse-engineering methods. We analyze experimental data of MCF-7 human breast cancer cells stimulated by epidermal growth factor or heregulin with several doses and provide novel biological hypotheses through network comparison. The software NETCOMP is available at http://bonsai.ims.u-tokyo.ac.jp/ approximately shima/NETCOMP/.

  7. Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

    OpenAIRE

    Khawaldeh, Saed; Pervaiz, Usama; Elsharnoby, Mohammed; Alchalabi, Alaa Eddin; Al-Zubi, Nayel

    2017-01-01

    Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algo...

  8. The Security of Organizations and Individuals in Online Social Networks

    OpenAIRE

    Elyashar, Aviad

    2016-01-01

    The serious privacy and security problems related to online social networks (OSNs) are what fueled two complementary studies as part of this thesis. In the first study, we developed a general algorithm for the mining of data of targeted organizations by using Facebook (currently the most popular OSN) and socialbots. By friending employees in a targeted organization, our active socialbots were able to find new employees and informal organizational links that we could not find by crawling with ...

  9. Common and distinct brain networks underlying verbal and visual creativity.

    Science.gov (United States)

    Zhu, Wenfeng; Chen, Qunlin; Xia, Lingxiang; Beaty, Roger E; Yang, Wenjing; Tian, Fang; Sun, Jiangzhou; Cao, Guikang; Zhang, Qinglin; Chen, Xu; Qiu, Jiang

    2017-04-01

    Creativity is imperative to the progression of human civilization, prosperity, and well-being. Past creative researches tends to emphasize the default mode network (DMN) or the frontoparietal network (FPN) somewhat exclusively. However, little is known about how these networks interact to contribute to creativity and whether common or distinct brain networks are responsible for visual and verbal creativity. Here, we use functional connectivity analysis of resting-state functional magnetic resonance imaging data to investigate visual and verbal creativity-related regions and networks in 282 healthy subjects. We found that functional connectivity within the bilateral superior parietal cortex of the FPN was negatively associated with visual and verbal creativity. The strength of connectivity between the DMN and FPN was positively related to both creative domains. Visual creativity was negatively correlated with functional connectivity within the precuneus of the pDMN and right middle frontal gyrus of the FPN, and verbal creativity was negatively correlated with functional connectivity within the medial prefrontal cortex of the aDMN. Critically, the FPN mediated the relationship between the aDMN and verbal creativity, and it also mediated the relationship between the pDMN and visual creativity. Taken together, decreased within-network connectivity of the FPN and DMN may allow for flexible between-network coupling in the highly creative brain. These findings provide indirect evidence for the cooperative role of the default and executive control networks in creativity, extending past research by revealing common and distinct brain systems underlying verbal and visual creative cognition. Hum Brain Mapp 38:2094-2111, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. Functional organization of intrinsic connectivity networks in Chinese-chess experts.

    Science.gov (United States)

    Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

    2014-04-16

    The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Dynamical Response of Networks Under External Perturbations: Exact Results

    Science.gov (United States)

    Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

    2015-04-01

    We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

  12. Organic Synthesis under Solvent-free Condition. An Environmentally ...

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 11. Organic Synthesis under Solvent-free Condition: An Environmentally Benign Procedure – II. Gopalpur Nagendrappa. General Article Volume 7 Issue 11 November 2002 pp 64-69 ...

  13. Collaborative networked organizations - Concepts and practice in manufacturing enterprises

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.; Galeano, N.; Molina, A.

    2009-01-01

    Participation in networks has nowadays become very important for any organization that strives to achieve a differentiated competitive advantage, especially if the company is small or medium sized. Collaboration is a key issue to rapidly answer market demands in a manufacturing company, through

  14. Ecological Citizenship and Sustainable Consumption: Examining Local Organic Food Networks

    Science.gov (United States)

    Seyfang, Gill

    2006-01-01

    Sustainable consumption is gaining in currency as a new environmental policy objective. This paper presents new research findings from a mixed-method empirical study of a local organic food network to interrogate the theories of both sustainable consumption and ecological citizenship. It describes a mainstream policy model of sustainable…

  15. Protecting nature : organizations and networks in Europe and the USA.

    NARCIS (Netherlands)

    Koppen, van C.S.A.; Markham, W.T.

    2007-01-01

    This book offers a comparative analysis of organizations and networks involved in nature protection in France, Germany, Italy, the Netherlands, Norway, Poland, Sweden, the UK and the USA. It traces their development from their origins, more than a century ago, to the present day. Throughout this

  16. Applying Real Options Thinking to Information Security in Networked Organizations

    NARCIS (Netherlands)

    Daneva, Maia

    2006-01-01

    An information security strategy of an organization participating in a networked business sets out the plans for designing a variety of actions that ensure confidentiality, availability, and integrity of company’s key information assets. The actions are concerned with authentication and

  17. International agri-food chains and networks. Management and Organization

    NARCIS (Netherlands)

    Bijman, J.; Omta, S.W.F.; Trienekens, J.H.; Wijnands, J.H.M.; Wubben, E.F.M.

    2006-01-01

    This book brings together a rich collection of papers on management and organization in agri-food chains and networks. Producers, processors, traders and retailers of agricultural and food products operate in an economic and institutional environment that is increasingly dominated by global

  18. Organic Synthesis under Solvent-free Condition. An Environmentally ...

    Indian Academy of Sciences (India)

    GENERAL I ARTICLE. Organic Synthesis under Solvent-free Condition. An Environmentally Benign Procedure - II. The author is a Professor of Organic Chemistry at. Bangalore University,. Bangalore. His main area of research is organosilicon chemistry with particular attention to developing new synthetic procedures and.

  19. Mixed Transportation Network Design under a Sustainable Development Perspective

    Directory of Open Access Journals (Sweden)

    Jin Qin

    2013-01-01

    Full Text Available A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%.

  20. Node vulnerability of water distribution networks under cascading failures

    International Nuclear Information System (INIS)

    Shuang, Qing; Zhang, Mingyuan; Yuan, Yongbo

    2014-01-01

    Water distribution networks (WDNs) are important in modern lifeline system. Its stability and reliability are critical for guaranteeing high living quality and continuous operation of urban functions. The aim of this paper is to evaluate the nodal vulnerability of WDNs under cascading failures. Vulnerability is defined to analyze the effects of the consequent failures. A cascading failure is a step-by-step process which is quantitatively investigated by numerical simulation with intentional attack. Monitored pressures in different nodes and flows in different pipes have been used to estimate the network topological structure and the consequences of nodal failure. Based on the connectivity loss of topological structure, the nodal vulnerability has been evaluated. A load variation function is established to record the nodal failure reason and describe the relative differences between the load and the capacity. The proposed method is validated by an illustrative example. The results revealed that the network vulnerability should be evaluated with the consideration of hydraulic analysis and network topology. In the case study, 70.59% of the node failures trigger the cascading failures with different failure processes. It is shown that the cascading failures result in severe consequences in WDNs. - Highlights: • The aim of this paper is to evaluate the nodal vulnerability of water distribution networks under cascading failures. • Monitored pressures and flows have been used to estimate the network topological structure and the consequences of nodal failure. • Based on the connectivity loss of topological structure, the nodal vulnerability has been evaluated. • A load variation function is established to record the failure reason and describe the relative differences between load and capacity. • The results show that 70.59% of the node failures trigger the cascading failures with different failure processes

  1. Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

    KAUST Repository

    Alfadly, Modar M.

    2018-04-12

    Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

  2. The Network Structure Underlying the Earth Observation Assessment

    Science.gov (United States)

    Vitkin, S.; Doane, W. E. J.; Mary, J. C.

    2017-12-01

    The Earth Observations Assessment (EOA 2016) is a multiyear project designed to assess the effectiveness of civil earth observation data sources (instruments, sensors, models, etc.) on societal benefit areas (SBAs) for the United States. Subject matter experts (SMEs) provided input and scored how data sources inform products, product groups, key objectives, SBA sub-areas, and SBAs in an attempt to quantify the relationships between data sources and SBAs. The resulting data were processed by Integrated Applications Incorporated (IAI) using MITRE's PALMA software to create normalized relative impact scores for each of these relationships. However, PALMA processing obscures the natural network representation of the data. Any network analysis that might identify patterns of interaction among data sources, products, and SBAs is therefore impossible. Collaborating with IAI, we cleaned and recreated a network from the original dataset. Using R and Python we explore the underlying structure of the network and apply frequent itemset mining algorithms to identify groups of data sources and products that interact. We reveal interesting patterns and relationships in the EOA dataset that were not immediately observable from the EOA 2016 report and provide a basis for further exploration of the EOA network dataset.

  3. Sustainable and Resilient Supply Chain Network Design under Disruption Risks

    Directory of Open Access Journals (Sweden)

    Sonia Irshad Mari

    2014-09-01

    Full Text Available Sustainable supply chain network design is a rich area for academic research that is still in its infancy and has potential to affect supply chain performance. Increasing regulations for carbon and waste management are forcing firms to consider their supply chains from ecological and social objectives, but in reality, however, facilities and the links connecting them are disrupted from time to time, due to poor weather, natural or manmade disasters or a combination of any other factors. Supply chain systems drop their sustainability objectives while coping with these unexpected disruptions. Hence, the new challenges for supply chain managers are to design an efficient and effective supply chain network that will be resilient enough to bounce back from any disruption and that also should have sufficient vigilance to offer same sustainability under a disruption state. This paper focuses on ecological sustainability, because an environmental focus in a supply chain system is more important and also links with other pillars of sustainability, as the products need to be produced, packed and transported in an ethical way, which should not harm social balance and the environment. Owing to importance of the considered issue, this paper attempts to introduce a network optimization model for a sustainable and resilient supply chain network by incorporating (1 sustainability via carbon emissions and embodied carbon footprints and (2 resilience by incorporating location-specific risks. The proposed goal programming (GP model optimizes the total cost, while considering the resilience and sustainability of the supply chain network.

  4. Modeling the Propagation of Mobile Phone Virus under Complex Network

    OpenAIRE

    Yang, Wei; Wei, Xi-liang; Guo, Hao; An, Gang; Guo, Lei; Yao, Yu

    2014-01-01

    Mobile phone virus is a rogue program written to propagate from one phone to another, which can take control of a mobile device by exploiting its vulnerabilities. In this paper the propagation model of mobile phone virus is tackled to understand how particular factors can affect its propagation and design effective containment strategies to suppress mobile phone virus. Two different propagation models of mobile phone viruses under the complex network are proposed in this paper. One is intende...

  5. Nanoporous ionic organic networks: from synthesis to materials applications.

    Science.gov (United States)

    Sun, Jian-Ke; Antonietti, Markus; Yuan, Jiayin

    2016-11-21

    The past decade has witnessed rapid progress in the synthesis of nanoporous organic networks or polymer frameworks for various potential applications. Generally speaking, functionalization of porous networks to add extra properties and enhance materials performance could be achieved either during the pore formation (thus a concurrent approach) or by post-synthetic modification (a sequential approach). Nanoporous organic networks which include ion pairs bound in a covalent manner are of special importance and possess extreme application profiles. Within these nanoporous ionic organic networks (NIONs), here with a pore size in the range from sub-1 nm to 100 nm, we observe a synergistic coupling of the electrostatic interaction of charges, the nanoconfinement within pores and the addressable functional units in soft matter resulting in a wide variety of functions and applications, above all catalysis, energy storage and conversion, as well as environment-related operations. This review aims to highlight the recent progress in this area, and seeks to raise original perspectives that will stimulate future advancements at both the fundamental and applied level.

  6. Self-organization of social hierarchy on interaction networks

    International Nuclear Information System (INIS)

    Fujie, Ryo; Odagaki, Takashi

    2011-01-01

    In order to examine the effects of interaction network structures on the self-organization of social hierarchy, we introduce the agent-based model: each individual as on a node of a network has its own power and its internal state changes by fighting with its neighbors and relaxation. We adopt three different networks: regular lattice, small-world network and scale-free network. For the regular lattice, we find the emergence of classes distinguished by the internal state. The transition points where each class emerges are determined analytically, and we show that each class is characterized by the local ranking relative to their neighbors. We also find that the antiferromagnetic-like configuration emerges just above the critical point. For the heterogeneous networks, individuals become winners (or losers) in descending order of the number of their links. By using mean-field analysis, we reveal that the transition point is determined by the maximum degree and the degree distribution in its neighbors

  7. Evolution of cooperation under social pressure in multiplex networks

    Science.gov (United States)

    Pereda, María

    2016-09-01

    In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

  8. Connectomics and neuroticism: an altered functional network organization.

    Science.gov (United States)

    Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard C; Ormel, Johan; Riese, Harriëtte; Aleman, André

    2015-01-01

    The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weighted brain-wide graphs were constructed to examine changes in the functional network structure and functional connectivity strength. Furthermore, graphs were partitioned into modules to specifically investigate connectivity within and between functional subnetworks related to emotion processing and cognitive control. Subsequently, complex network measures (ie, efficiency and modularity) were calculated on the brain-wide graphs and modules, and correlated with neuroticism scores. Compared with low neurotic individuals, high neurotic individuals exhibited a whole-brain network structure resembling more that of a random network and had overall weaker functional connections. Furthermore, in these high neurotic individuals, functional subnetworks could be delineated less clearly and the majority of these subnetworks showed lower efficiency, while the affective subnetwork showed higher efficiency. In addition, the cingulo-operculum subnetwork demonstrated more ties with other functional subnetworks in association with neuroticism. In conclusion, the 'neurotic brain' has a less than optimal functional network organization and shows signs of functional disconnectivity. Moreover, in high compared with low neurotic individuals, emotion and salience subnetworks have a more prominent role in the information exchange, while sensory(-motor) and cognitive control subnetworks have a less prominent role.

  9. 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...

  10. Self-Organization in Coupled Map Scale-Free Networks

    Science.gov (United States)

    Liang, Xiao-Ming; Lü, Hua-Ping; Liu, Zong-Hua

    2008-02-01

    We study the self-organization of phase synchronization in coupled map scale-free networks with chaotic logistic map at each node and find that a variety of ordered spatiotemporal patterns emerge spontaneously in a regime of coupling strength. These ordered behaviours will change with the increase of the average links and are robust to both the system size and parameter mismatch. A heuristic theory is given to explain the mechanism of self-organization and to figure out the regime of coupling for the ordered spatiotemporal patterns.

  11. Taxonomic Classification for Living Organisms Using Convolutional Neural Networks.

    Science.gov (United States)

    Khawaldeh, Saed; Pervaiz, Usama; Elsharnoby, Mohammed; Alchalabi, Alaa Eddin; Al-Zubi, Nayel

    2017-11-17

    Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential for using it in many other applications in genome analysis.

  12. Analysis and Reduction of Complex Networks Under Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Knio, Omar M

    2014-04-09

    This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

  13. Development of Shale Gas Supply Chain Network under Market Uncertainties

    Directory of Open Access Journals (Sweden)

    Jorge Chebeir

    2017-02-01

    Full Text Available The increasing demand of energy has turned the shale gas and shale oil into one of the most promising sources of energy in the United States. In this article, a model is proposed to address the long-term planning problem of the shale gas supply chain under uncertain conditions. A two-stage stochastic programming model is proposed to describe and optimize the shale gas supply chain network. Inherent uncertainty in final products’ prices, such as natural gas and natural gas liquids (NGL, is treated through the utilization of a scenario-based method. A binomial option pricing model is utilized to approximate the stochastic process through the generation of scenario trees. The aim of the proposed model is to generate an appropriate and realistic supply chain network configuration as well as scheduling of different operations throughout the planning horizon of a shale gas development project.

  14. Connectomics and Neuroticism: An Altered Functional Network Organization

    OpenAIRE

    Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard C; Ormel, Johan; Riese, Harriëtte; Aleman, André

    2014-01-01

    The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weig...

  15. Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Marzouk, Youssef M. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Coles, T. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Spantini, A. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Tosatto, L. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

    2013-09-30

    The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local and long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing

  16. The Production of Goat Milk under Organic Requests

    Directory of Open Access Journals (Sweden)

    Roger Stan

    2011-10-01

    Full Text Available Organic farming has turned into a very important subject who consists in a food production label and it has become very popular. That is because, especially in the EU the majority of the dairy goat farms want or have already applied the organic farming in order to benefit not only from the good price of milk but also from the given positive image. The main issue of this study is the high production of goat milk using organic farming under specific regulations. Therefore, the organic farming is based on a safe environment, 100% organic feedstuffs, healthy animals (by prevention of diseases, natural mating, reduced stress in animal rearing, modern stables and milking equipment. A few feeding rations were established to improve the quantity and quality of goat milk.

  17. Connection Management and Recovery Strategies under Epidemic Network Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2014-01-01

    The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust ...... of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections requiring recovery, which translates in improved quality of service to customers....... manner under attacks. This work proposes four policies for failure handling in a connection-oriented optical transport network, under Generalized MultiProtocol Label Switching control plane, and evaluates their performance under multiple correlated large-scale failures. We employ the Susceptible......-Infected-Disabled epidemic failure spreading model and look into possible tradeoffs between resiliency and resource efficiency. Via extensive simulations we show that there exist a clear tradeoff between policy performance and network resource consumption, which must be addressed by network operators for improved robustness...

  18. Acclimation of Culturable Bacterial Communities under the Stresses of Different Organic Compounds

    Science.gov (United States)

    Wang, Hui; Zhang, Shuangfei; Pratush, Amit; Ye, Xueying; Xie, Jinli; Wei, Huan; Sun, Chongran; Hu, Zhong

    2018-01-01

    The phylogenetic diversity of bacterial communities in response to environmental disturbances such as organic pollution has been well studied, but little is known about the way in which organic contaminants influence the acclimation of functional bacteria. In the present study, tolerance assays for bacterial communities from the sediment in the Pearl River Estuary were conducted with the isolation of functional bacteria using pyrene and different estrogens as environmental stressors. Molecular ecological networks and phylogenetic trees were constructed using both 16S rRNA gene sequences of cultured bacterial strains and 16S rRNA gene-based pyrosequencing data to illustrate the successions of bacterial communities and their acclimations to the different organic compounds. A total of 111 bacterial strains exhibiting degradation and endurance capabilities in response to the pyrene estrogen-induced stress were successfully isolated and were mainly affiliated with three orders, Pseudomonadales, Vibrionales, and Rhodobacterales. Molecular ecological networks and phylogenetic trees showed various adaptive abilities of bacteria to the different organic compounds. For instance, some bacterial OTUs could be found only in particular organic compound-treated groups while some other OTUs could tolerate stresses from different organic compounds. Furthermore, the results indicated that some new phylotypes were emerged under stresses of different organic pollutions and these new phylotypes could adapt to the contaminated environments and contribute significantly to the microbial community shifts. Overall, this study demonstrated a crucial role of the community succession and the acclimation of functional bacteria in the adaptive responses to various environmental disturbances. PMID:29520254

  19. Optimal Retrofit Scheme for Highway Network under Seismic Hazards

    Directory of Open Access Journals (Sweden)

    Yongxi Huang

    2014-06-01

    Full Text Available Many older highway bridges in the United States (US are inadequate for seismic loads and could be severely damaged or collapsed in a relatively small earthquake. According to the most recent American Society of Civil Engineers’ infrastructure report card, one-third of the bridges in the US are rated as structurally deficient and many of these structurally deficient bridges are located in seismic zones. To improve this situation, at-risk bridges must be identified and evaluated and effective retrofitting programs should be in place to reduce their seismic vulnerabilities. In this study, a new retrofit strategy decision scheme for highway bridges under seismic hazards is developed and seamlessly integrate the scenario-based seismic analysis of bridges and the traffic network into the proposed optimization modeling framework. A full spectrum of bridge retrofit strategies is considered based on explicit structural assessment for each seismic damage state. As an empirical case study, the proposed retrofit strategy decision scheme is utilized to evaluate the bridge network in one of the active seismic zones in the US, Charleston, South Carolina. The developed modeling framework, on average, will help increase network throughput traffic capacity by 45% with a cost increase of only $15million for the Mw 5.5 event and increase the capacity fourfold with a cost of only $32m for the Mw 7.0 event.

  20. Modeling the Propagation of Mobile Phone Virus under Complex Network

    Directory of Open Access Journals (Sweden)

    Wei Yang

    2014-01-01

    Full Text Available Mobile phone virus is a rogue program written to propagate from one phone to another, which can take control of a mobile device by exploiting its vulnerabilities. In this paper the propagation model of mobile phone virus is tackled to understand how particular factors can affect its propagation and design effective containment strategies to suppress mobile phone virus. Two different propagation models of mobile phone viruses under the complex network are proposed in this paper. One is intended to describe the propagation of user-tricking virus, and the other is to describe the propagation of the vulnerability-exploiting virus. Based on the traditional epidemic models, the characteristics of mobile phone viruses and the network topology structure are incorporated into our models. A detailed analysis is conducted to analyze the propagation models. Through analysis, the stable infection-free equilibrium point and the stability condition are derived. Finally, considering the network topology, the numerical and simulation experiments are carried out. Results indicate that both models are correct and suitable for describing the spread of two different mobile phone viruses, respectively.

  1. Modeling the propagation of mobile phone virus under complex network.

    Science.gov (United States)

    Yang, Wei; Wei, Xi-liang; Guo, Hao; An, Gang; Guo, Lei; Yao, Yu

    2014-01-01

    Mobile phone virus is a rogue program written to propagate from one phone to another, which can take control of a mobile device by exploiting its vulnerabilities. In this paper the propagation model of mobile phone virus is tackled to understand how particular factors can affect its propagation and design effective containment strategies to suppress mobile phone virus. Two different propagation models of mobile phone viruses under the complex network are proposed in this paper. One is intended to describe the propagation of user-tricking virus, and the other is to describe the propagation of the vulnerability-exploiting virus. Based on the traditional epidemic models, the characteristics of mobile phone viruses and the network topology structure are incorporated into our models. A detailed analysis is conducted to analyze the propagation models. Through analysis, the stable infection-free equilibrium point and the stability condition are derived. Finally, considering the network topology, the numerical and simulation experiments are carried out. Results indicate that both models are correct and suitable for describing the spread of two different mobile phone viruses, respectively.

  2. Spread of Epidemic on Complex Networks Under Voluntary Vaccination Mechanism

    Science.gov (United States)

    Xue, Shengjun; Ruan, Feng; Yin, Chuanyang; Zhang, Haifeng; Wang, Binghong

    Under the assumption that the decision of vaccination is a voluntary behavior, in this paper, we use two forms of risk functions to characterize how susceptible individuals estimate the perceived risk of infection. One is uniform case, where each susceptible individual estimates the perceived risk of infection only based on the density of infection at each time step, so the risk function is only a function of the density of infection; another is preferential case, where each susceptible individual estimates the perceived risk of infection not only based on the density of infection but only related to its own activities/immediate neighbors (in network terminology, the activity or the number of immediate neighbors is the degree of node), so the risk function is a function of the density of infection and the degree of individuals. By investigating two different ways of estimating the risk of infection for susceptible individuals on complex network, we find that, for the preferential case, the spread of epidemic can be effectively controlled; yet, for the uniform case, voluntary vaccination mechanism is almost invalid in controlling the spread of epidemic on networks. Furthermore, given the temporality of some vaccines, the waves of epidemic for two cases are also different. Therefore, our work insight that the way of estimating the perceived risk of infection determines the decision on vaccination options, and then determines the success or failure of control strategy.

  3. Modeling the Propagation of Mobile Phone Virus under Complex Network

    Science.gov (United States)

    Yang, Wei; Wei, Xi-liang; Guo, Hao; An, Gang; Guo, Lei

    2014-01-01

    Mobile phone virus is a rogue program written to propagate from one phone to another, which can take control of a mobile device by exploiting its vulnerabilities. In this paper the propagation model of mobile phone virus is tackled to understand how particular factors can affect its propagation and design effective containment strategies to suppress mobile phone virus. Two different propagation models of mobile phone viruses under the complex network are proposed in this paper. One is intended to describe the propagation of user-tricking virus, and the other is to describe the propagation of the vulnerability-exploiting virus. Based on the traditional epidemic models, the characteristics of mobile phone viruses and the network topology structure are incorporated into our models. A detailed analysis is conducted to analyze the propagation models. Through analysis, the stable infection-free equilibrium point and the stability condition are derived. Finally, considering the network topology, the numerical and simulation experiments are carried out. Results indicate that both models are correct and suitable for describing the spread of two different mobile phone viruses, respectively. PMID:25133209

  4. Experimental study and artificial neural network modeling of tartrazine removal by photocatalytic process under solar light.

    Science.gov (United States)

    Sebti, Aicha; Souahi, Fatiha; Mohellebi, Faroudja; Igoud, Sadek

    2017-07-01

    This research focuses on the application of an artificial neural network (ANN) to predict the removal efficiency of tartrazine from simulated wastewater using a photocatalytic process under solar illumination. A program is developed in Matlab software to optimize the neural network architecture and select the suitable combination of training algorithm, activation function and hidden neurons number. The experimental results of a batch reactor operated under different conditions of pH, TiO 2 concentration, initial organic pollutant concentration and solar radiation intensity are used to train, validate and test the networks. While negligible mineralization is demonstrated, the experimental results show that under sunlight irradiation, 85% of tartrazine is removed after 300 min using only 0.3 g/L of TiO 2 powder. Therefore, irradiation time is prolonged and almost 66% of total organic carbon is reduced after 15 hours. ANN 5-8-1 with Bayesian regulation back-propagation algorithm and hyperbolic tangent sigmoid transfer function is found to be able to predict the response with high accuracy. In addition, the connection weights approach is used to assess the importance contribution of each input variable on the ANN model response. Among the five experimental parameters, the irradiation time has the greatest effect on the removal efficiency of tartrazine.

  5. The large-scale organization of the hadron decay network

    International Nuclear Information System (INIS)

    Xu, Xinping; Liu, Feng

    2008-01-01

    The standard model of particle physics predicts a complex structure of decay modes for hadrons, which opens up an avenue for observing the internal forces governing the decay dynamics. In this paper, we present the decay modes of hadrons as a network in which the nodes are particles and directed links are pointing from the mother particles to daughter particles. Using the database of decay modes collected from the Particle Data Group, we try to unveil the topological structure and possible intrinsic nature of hadron decays in the light of recent investigations of complex networks. We study distributions of the numbers of daughter and mother particles, and explore scaling laws that may govern the underlying decay structure of the system. We find that it is a small-world network with symmetrical structure. We also study the influence of constraints arising from conservation laws on the network structure, and our analysis suggests that the constraints of conservations of momentum–energy, charge, lepton number and baryon number play important roles in the topology of the decay network. Finally, we classify the hadrons into communities according to their quark component, and uncover the relationship between the particle roles and connection patterns in the communities

  6. The Growing Hierarchical Neural Gas Self-Organizing Neural Network.

    Science.gov (United States)

    Palomo, Esteban J; Lopez-Rubio, Ezequiel

    2017-09-01

    The growing neural gas (GNG) self-organizing neural network stands as one of the most successful examples of unsupervised learning of a graph of processing units. Despite its success, little attention has been devoted to its extension to a hierarchical model, unlike other models such as the self-organizing map, which has many hierarchical versions. Here, a hierarchical GNG is presented, which is designed to learn a tree of graphs. Moreover, the original GNG algorithm is improved by a distinction between a growth phase where more units are added until no significant improvement in the quantization error is obtained, and a convergence phase where no unit creation is allowed. This means that a principled mechanism is established to control the growth of the structure. Experiments are reported, which demonstrate the self-organization and hierarchy learning abilities of our approach and its performance for vector quantization applications.

  7. Adaptive neural network motion control for aircraft under uncertainty conditions

    Science.gov (United States)

    Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

    2018-02-01

    We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

  8. Selfish cellular networks and the evolution of complex organisms.

    Science.gov (United States)

    Kourilsky, Philippe

    2012-03-01

    Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  9. Hybrid Organic/Inorganic Thiol-ene-Based Photopolymerized Networks.

    Science.gov (United States)

    Schreck, Kathleen M; Leung, Diana; Bowman, Christopher N

    2011-09-15

    The thiol-ene reaction serves as a more oxygen tolerant alternative to traditional (meth)acrylate chemistry for forming photopolymerized networks with numerous desirable attributes including energy absorption, optical clarity, and reduced shrinkage stress. However, when utilizing commercially available monomers, many thiol-ene networks also exhibit decreases in properties such as glass transition temperature (T(g)) and crosslink density. In this study, hybrid organic/inorganic thiol-ene resins incorporating silsesquioxane (SSQ) species into the photopolymerized networks were investigated as a route to improve these properties. Thiol- and ene-functionalized SSQs (SH-SSQ and allyl-SSQ, respectively) were synthesized via alkoxysilane hydrolysis/condensation chemistry, using a photopolymerizable monomer [either pentaerythriol tetrakis(3-mercaptopropionate) (PETMP) or 1,3,5-triallyl-1,3,5-triazine-2,4,6(1H,3H,5H)-trione (TATATO)] as the reaction solvent. The resulting SSQ-containing solutions (SSQ-PETMP and SSQ-TATATO) were characterized, and their incorporation into photopolymerized networks was evaluated.

  10. Performance of a Rain Barrel Sharing Network under Climate Change

    Directory of Open Access Journals (Sweden)

    Seong Jin Noh

    2015-07-01

    Full Text Available Rain barrels can be technically shared through social practices or mutual agreement between individual households. This study proposes the evaluation system for a rain barrel sharing network (RBSN considering three performance criteria of reliability, resiliency, and vulnerability, under plausible climate change scenarios. First, this study shows how the system can be improved in terms of the performance criteria using historical daily rainfall data based on the storage-reliability-yield relationship. This study then examined how the benefits from RBSN are affected by climate change after 100 years. Three climate change scenarios (A1B, A2 and B2 and three global circulation models were used for this purpose. The results showed that the reliability and vulnerability are improved due to sharing and their improvements become larger under climate change conditions. In contrast, the resiliency reduces slightly due to sharing and its reduction is attenuated under climate change conditions. In particular, vulnerability will be reduced significantly under climate change. These results suggest that the sharing of various water resources systems can be an effective climate change adaptation strategy that reduces vulnerability and increases the reliability of the system.

  11. Compensatory growth in slaughter pigs reared under organic conditions

    DEFF Research Database (Denmark)

    Fernández, José Adalberto; Nørgaard, Jan Værum

    2009-01-01

    BACKGROUND: Compensatory growth is the physiological process leading to accelerated growth following a period of growth retardation. This study assessed different feeding strategies that may induce compensatory growth. Pigs from two sire breeds, reared under organic conditions, were subjected to...... that although compensatory growth does occur by re-alimentation after feed restriction, the compensation is far from always complete. The latter is a crucial aspect that has to be taken into account when considering the application of feeding strategies expected to lead to compensatory growth in organic pig...... production. The expectation of compensatory growth alone does not necessarily justify the application of these strategies. Copyright © 2009 Society of Chemical Industry...

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

    Science.gov (United States)

    Tempas, Christopher D.

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

  13. Abnormal Brain Network Organization in Body Dysmorphic Disorder

    Science.gov (United States)

    Arienzo, Donatello; Leow, Alex; Brown, Jesse A; Zhan, Liang; GadElkarim, Johnson; Hovav, Sarit; Feusner, Jamie D

    2013-01-01

    Body dysmorphic disorder (BDD) is characterized by preoccupation with misperceived defects of appearance, causing significant distress and disability. Previous studies suggest abnormalities in information processing characterized by greater local relative to global processing. The purpose of this study was to probe whole-brain and regional white matter network organization in BDD, and to relate this to specific metrics of symptomatology. We acquired diffusion-weighted 34-direction MR images from 14 unmedicated participants with DSM-IV BDD and 16 healthy controls, from which we conducted whole-brain deterministic diffusion tensor imaging tractography. We then constructed white matter structural connectivity matrices to derive whole-brain and regional graph theory metrics, which we compared between groups. Within the BDD group, we additionally correlated these metrics with scores on psychometric measures of BDD symptom severity as well as poor insight/delusionality. The BDD group showed higher whole-brain mean clustering coefficient than controls. Global efficiency negatively correlated with BDD symptom severity. The BDD group demonstrated greater edge betweenness centrality for connections between the anterior temporal lobe and the occipital cortex, and between bilateral occipital poles. This represents the first brain network analysis in BDD. Results suggest disturbances in whole brain structural topological organization in BDD, in addition to correlations between clinical symptoms and network organization. There is also evidence of abnormal connectivity between regions involved in lower-order visual processing and higher-order visual and emotional processing, as well as interhemispheric visual information transfer. These findings may relate to disturbances in information processing found in previous studies. PMID:23322186

  14. Pro-cognitive drug effects modulate functional brain network organization

    Directory of Open Access Journals (Sweden)

    Carsten eGiessing

    2012-08-01

    Full Text Available Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with fMRI. Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e. the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the global workspace theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs might be related to higher

  15. Pro-cognitive drug effects modulate functional brain network organization

    Science.gov (United States)

    Giessing, Carsten; Thiel, Christiane M.

    2012-01-01

    Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the “global workspace” theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs

  16. Neurological impressions on the organization of language networks in the human brain.

    Science.gov (United States)

    Oliveira, Fabricio Ferreira de; Marin, Sheilla de Medeiros Correia; Bertolucci, Paulo Henrique Ferreira

    2017-01-01

    More than 95% of right-handed individuals, as well as almost 80% of left-handed individuals, have left hemisphere dominance for language. The perisylvian networks of the dominant hemisphere tend to be the most important language systems in human brains, usually connected by bidirectional fibres originated from the superior longitudinal fascicle/arcuate fascicle system and potentially modifiable by learning. Neuroplasticity mechanisms take place to preserve neural functions after brain injuries. Language is dependent on a hierarchical interlinkage of serial and parallel processing areas in distinct brain regions considered to be elementary processing units. Whereas aphasic syndromes typically result from injuries to the dominant hemisphere, the extent of the distribution of language functions seems to be variable for each individual. Review of the literature Results: Several theories try to explain the organization of language networks in the human brain from a point of view that involves either modular or distributed processing or sometimes both. The most important evidence for each approach is discussed under the light of modern theories of organization of neural networks. Understanding the connectivity patterns of language networks may provide deeper insights into language functions, supporting evidence-based rehabilitation strategies that focus on the enhancement of language organization for patients with aphasic syndromes.

  17. Organization of anti-phase synchronization pattern in neural networks: what are the key factors?

    Directory of Open Access Journals (Sweden)

    Dong eLi

    2011-12-01

    Full Text Available Anti-phase oscillation has been widely observed in cortical neuralnetwork. Elucidating the mechanism underlying the organization ofanti-phase pattern is of significance for better understanding morecomplicated pattern formations in brain networks. In dynamicalsystems theory, the organization of anti-phase oscillation patternhas usually been considered to relate to time-delay in coupling.This is consistent to conduction delays in real neural networks inthe brain due to finite propagation velocity of action potentials.However, other structural factors in cortical neural network, suchas modular organization (connection density and the coupling types(excitatory or inhibitory, could also play an important role. Inthis work, we investigate the anti-phase oscillation patternorganized on a two-module network of either neuronal cell model orneural mass model, and analyze the impact of the conduction delaytimes, the connection densities, and coupling types. Our resultsshow that delay times and coupling types can play key roles in thisorganization. The connection densities may have an influence on thestability if an anti-phase pattern exists due to the other factors.Furthermore, we show that anti-phase synchronization of slowoscillations can be achieved with small delay times if there isinteraction between slow and fast oscillations. These results aresignificant for further understanding more realistic spatiotemporaldynamics of cortico-cortical communications.

  18. Model of Learning Organizational Development of Primary School Network under the Office of Basic Education Commission

    Science.gov (United States)

    Sai-rat, Wipa; Tesaputa, Kowat; Sriampai, Anan

    2015-01-01

    The objectives of this study were 1) to study the current state of and problems with the Learning Organization of the Primary School Network, 2) to develop a Learning Organization Model for the Primary School Network, and 3) to study the findings of analyses conducted using the developed Learning Organization Model to determine how to develop the…

  19. Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Saed Khawaldeh

    2017-11-01

    Full Text Available Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential for using it in many other applications in genome analysis.

  20. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm.

    Science.gov (United States)

    Wu, Haizhou; Zhou, Yongquan; Luo, Qifang; Basset, Mohamed Abdel

    2016-01-01

    Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs). In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  1. Joint Secrecy for D2D Communications Underlying Cellular Networks

    KAUST Repository

    Hyadi, Amal

    2018-01-15

    In this work, we investigate the ergodic secrecy rate region of a block-fading spectrum-sharing system, where a D2D communication is underlying a cellular channel. We consider that both the primary and the secondary transmissions require their respective transmitted messages to be kept secret from a common eavesdropper under a joint secrecy constraint. The presented results are for three different scenarios, each corresponding to a particular requirement of the cellular system. First, we consider the case of a fair cellular system, and we show that the impact of jointly securing the transmissions can be balanced between the primary and the secondary systems. The second scenario examines the case when the primary network is demanding and requires the secondary transmission to be at a rate that is decodable by the primary receiver, while the last scenario assumes a joint transmission of artificial noise by the primary and the secondary transmitters. For each scenario, we present an achievable ergodic secrecy rate region that can be used as an indicator for the cellular and the D2D systems to agree under which terms the spectrum will be shared.

  2. Retrospective analysis of "new" flame retardants in the global atmosphere under the GAPS Network.

    Science.gov (United States)

    Lee, Sum Chi; Sverko, Ed; Harner, Tom; Pozo, Karla; Barresi, Enzo; Schachtschneider, JoAnne; Zaruk, Donna; DeJong, Maryl; Narayan, Julie

    2016-10-01

    A retrospective analysis was conducted on air samples that were collected in 2005 under the Global Atmospheric Passive Sampling (GAPS) Network around the time period when the Stockholm Convention on Persistent Organic Pollutants came into force. Results are presented for several new flame retardants, including hexabromocyclododecane (HBCD), which was recently listed under the Convention (2013). These results represent the first global-scale distributions in air for these compounds. The targeted compounds are shown to have unique global distributions in air, which highlights the challenges in understanding the sources and environmental fate of each chemical, and ultimately in their assessments as persistent organic pollutants. The study also demonstrates the feasibility of using the PUF disk passive air sampler to study these new flame retardants in air, many of which exist entirely in the particle-phase as demonstrated in this study using a KOA-based partitioning model. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  3. Work of scientific and technological information under network environment

    International Nuclear Information System (INIS)

    Chen Yingxi; Huang Daifu; Yang Lifeng

    2010-01-01

    With the development of internet and information technology, the work of scientific and technological information is faced with great challenge. This article expounds the new changes of scientific and technological information in enterprise under network environment by giving a minute description on the situation the work faced and characteristic of the work. Not only does it carry out enthusiastic discussion upon problems which are present in the work of scientific and technological information in the company, but puts forward proposals and specific measures as well. Service theory is also offered by adjusting and reforming the resources construction, service ways and the job of providing contents. We should take vigorous action to the research work of scientific and technological information, changing the information directional service into knowledge providing service. (authors)

  4. Self-organizing Ising model of artificial financial markets with small-world network topology

    Science.gov (United States)

    Zhao, Haijie; Zhou, Jie; Zhang, Anghui; Su, Guifeng; Zhang, Yi

    2013-01-01

    We study a self-organizing Ising-like model of artificial financial markets with underlying small-world (SW) network topology. The asset price dynamics results from the collective decisions of interacting agents which are located on a small-world complex network (the nodes symbolize the agents of a financial market). The model incorporates the effects of imitation, the impact of external news and private information. We also investigate the influence of different network topologies, from regular lattice to random graph, on the asset price dynamics by adjusting the probability of the rewiring procedure. We find that a specific combination of model parameters reproduce main stylized facts of real-world financial markets.

  5. Book Review - V Pogoretskyy, Freedom of Transit and Access to Gas Pipeline Networks Under WTO Law (Cambridge University Press, 2017)

    NARCIS (Netherlands)

    Marhold, Anna

    2017-01-01

    In Freedom of Transit and Access to Pipeline Networks under WTO Law, the author appropriately introduces the topic by stating that energy is featuring increasingly prominently as a topic in international trade law. Indeed, while being a dormant issue in the World Trade Organization (“WTO” forum for

  6. Altered modular organization of structural cortical networks in children with autism.

    Directory of Open Access Journals (Sweden)

    Feng Shi

    Full Text Available Autism is a complex developmental disability that characterized by deficits in social interaction, language skills, repetitive stereotyped behaviors and restricted interests. Although great heterogeneity exists, previous findings suggest that autism has atypical brain connectivity patterns and disrupted small-world network properties. However, the organizational alterations in the autistic brain network are still poorly understood. We explored possible organizational alterations of 49 autistic children and 51 typically developing controls, by investigating their brain network metrics that are constructed upon cortical thickness correlations. Three modules were identified in controls, including cortical regions associated with brain functions of executive strategic, spatial/auditory/visual, and self-reference/episodic memory. There are also three modules found in autistic children with similar patterns. Compared with controls, autism demonstrates significantly reduced gross network modularity, and a larger number of inter-module connections. However, the autistic brain network demonstrates increased intra- and inter-module connectivity in brain regions including middle frontal gyrus, inferior parietal gyrus, and cingulate, suggesting one underlying compensatory mechanism associated with brain functions of self-reference and episodic memory. Results also show that there is increased correlation strength between regions inside frontal lobe, as well as impaired correlation strength between frontotemporal and frontoparietal regions. This alteration of correlation strength may contribute to the organization alteration of network structures in autistic brains.

  7. Self-organization towards optimally interdependent networks by means of coevolution

    International Nuclear Information System (INIS)

    Wang, Zhen; Szolnoki, Attila; Perc, Matjaž

    2014-01-01

    Coevolution between strategy and network structure is established as a means to arrive at the optimal conditions needed to resolve social dilemmas. Yet recent research has highlighted that the interdependence between networks may be just as important as the structure of an individual network. We therefore introduce the coevolution of strategy and network interdependence to see whether this can give rise to elevated levels of cooperation in the prisoner's dilemma game. We show that the interdependence between networks self-organizes so as to yield optimal conditions for the evolution of cooperation. Even under extremely adverse conditions, cooperators can prevail where on isolated networks they would perish. This is due to the spontaneous emergence of a two-class society, with only the upper class being allowed to control and take advantage of the interdependence. Spatial patterns reveal that cooperators, once arriving at the upper class, are much more competent than defectors in sustaining compact clusters of followers. Indeed, the asymmetric exploitation of interdependence confers to them a strong evolutionary advantage that may resolve even the toughest of social dilemmas. (paper)

  8. The use of soil monitoring networks to detect changes in soil organic carbon content

    Science.gov (United States)

    Keller, A.; Schwierz, C.; Schwab, P.; Ammann, S.; Meuli, R.; Rossier, N.; Papritz, A.

    2010-05-01

    Process-based carbon dynamic models are widely used to estimate and forecast temporal changes in soil organic carbon content (SOC). Often, these models are calibrated against measurements from long-term field experiments with controlled treatments at a local scale. Repeated SOC inventories at the sites of a soil monitoring network may provide additional valuable information about temporal changes at a regional scale for a broader range of environmental conditions (land use, soil type, climate, etc.). Recently, Saby et al. (2008) assessed the adequacy of European soil monitoring networks to detect changes in SOC. The minimum detectable changes (MDC) differed considerably among the networks, and the design turned out to be an important factor. However, Saby et al. derived their results from scenarios because the majority of the European monitoring networks performed only one sampling campaign so far. Data on SOC changes, gathered by repeated sampling at monitoring sites under controlled conditions including strict quality assurance protocols, are still rare, and little is known about random and systematic errors in the estimated changes. Furthermore, suitable (geo-) statistical procedures are required to extrapolate the SOC measurements and their change from the surveyed sites to the regional scale. In our presentation, we report (i) our experiences on MDC gained by repeated SOC measurements at selected sites of the Swiss Soil Monitoring Network (NABO), and (ii) we show how the SOC measurements recorded at the sites of the soil monitoring network of Canton Fribourg can be used for a mapping SOC and its change at the regional scale. For this purpose we a use robust geostatistical kriging approach which exploits the dependence of SOC on land use, altitude and climate. Saby P.A. et al. (2008). Will European soil-monitoring networks be able to detect changes in topsoil organic carbon content? Global Change Biology 14: 2432-2442.

  9. The topological organization of white matter network in internet gaming disorder individuals.

    Science.gov (United States)

    Zhai, Jinquan; Luo, Lin; Qiu, Lijun; Kang, Yongqiang; Liu, Bo; Yu, Dahua; Lu, Xiaoqi; Yuan, Kai

    2017-12-01

    White matter (WM) integrity abnormalities had been reported in Internet gaming disorder (IGD). Diffusion tensor imaging (DTI) tractography allows identification of WM tracts, potentially providing information about the integrity and organization of relevant underlying WM fiber tracts' architectures, which has been used to investigate the connectivity of cortical and subcortical structures in several brain disorders. Unfortunately, relatively little is known about the thoroughly circuit-level characterization of topological property changes of WM network with IGD. Sixteen right-hand adolescents with IGD participated in our study, according to the diagnostic criteria of IGD in DSM-5. Meanwhile, 16 age and gender-matched healthy controls were also enrolled. DTI tractography was employed to generate brain WM networks in IGD individuals and healthy controls. The 90 cortical and subcortical regions derived from AAL template were chosen as the nodes. The network parameters (i.e., Network strength, clustering coefficient, shortest path length, global efficiency, local efficiency, regional efficiency) were calculated and then correlated with the Internet addiction test (IAT) scores in IGD. IGD group showed decreased global efficiency, local efficiency and increased shortest path length. Further analysis revealed the reduced nodal efficiency in frontal cortex, anterior cingulate cortex and pallidium in IGD. In addition, the global efficiency of WM network was correlated with the IAT scores in IGD (r = -0.5927; p = 0.0155). We reported the abnormal topological organization of WM network in IGD and the association with the severity of IGD, which may provide new insights into the neural mechanism of IGD from WM network level.

  10. Synchronized clusters in coupled map networks: Self-organized and driven phase synchronization

    OpenAIRE

    Jalan, Sarika; Amritkar, R. E.

    2003-01-01

    We study the synchronization of coupled maps on a variety of networks including regular one and two dimensional networks, scale free networks, small world networks, tree networks, and random networks. For small coupling strengths nodes show turbulent behavior but form phase synchronized clusters as coupling increases. We identify two different ways of cluster formation, self-organized clusters which have mostly intra-cluster couplings and driven clusters which have mostly inter-cluster coupli...

  11. In Search of a Network Organization for TNC’s Innovation

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    organization among many kinds of innovation networks based on review of relative literatures. Then this paper moves one step further to introduce a network perspective, i.e. network is the context of firms as well as TNCs, and market and hierarchy can be analyzed from a network approach. Further on, this paper......During the past three decades, there are massive researches on innovation networks and network organizations. However, researchers are holding different understandings, some of which even conflict with each other, thus this paper makes an inductive conceptual analysis to clarify what is a network...... discusses the theoretical foundation of network organization, and proposes that since a focal firm has different strength of power in different levels of network, it will have different roles and may not always have the power to “manage” an innovation network....

  12. Silica Gel-Mediated Organic Reactions under Organic Solvent-Free Conditions

    Directory of Open Access Journals (Sweden)

    Satoaki Onitsuka

    2012-09-01

    Full Text Available Silica gel was found to be an excellent medium for some useful organic transformations under organic solvent-free conditions, such as (1 the Friedel-Crafts-type nitration of arenes using commercial aqueous 69% nitric acid alone at room temperature, (2 one-pot Wittig-type olefination of aldehydes with activated organic halides in the presence of tributyl- or triphenylphosphine and Hunig’s base, and (3 the Morita-Baylis-Hillman reaction of aldehydes with methyl acrylate. After the reactions, the desired products were easily obtained in good to excellent yields through simple manipulation.

  13. Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

    Science.gov (United States)

    Wang, Lin; Liu, Gaozhi

    2018-02-01

    This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

  14. Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks

    Science.gov (United States)

    Moon, Hankyu; Lu, Tsai-Ching

    2015-03-01

    Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of--how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description -- of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.

  15. Network catastrophe: self-organized patterns reveal both the instability and the structure of complex networks.

    Science.gov (United States)

    Moon, Hankyu; Lu, Tsai-Ching

    2015-03-30

    Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of-how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description - of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.

  16. Organics on Mars : Laboratory studies of organic material under simulated martian conditions

    NARCIS (Netherlands)

    Kate, Inge Loes ten

    2006-01-01

    The search for organic molecules and traces of life on Mars has been a major topic in planetary science for several decades, and is the future perspective of several missions to Mars. In order to determine where and what those missions should be looking for, laboratory experiments under simulated

  17. Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

    Science.gov (United States)

    Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

    2015-03-01

    During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

  18. Organic Matter Responses to Radiation under Lunar Conditions.

    Science.gov (United States)

    Matthewman, Richard; Crawford, Ian A; Jones, Adrian P; Joy, Katherine H; Sephton, Mark A

    2016-11-01

    Large bodies, such as the Moon, that have remained relatively unaltered for long periods of time have the potential to preserve a record of organic chemical processes from early in the history of the Solar System. A record of volatiles and impactors may be preserved in buried lunar regolith layers that have been capped by protective lava flows. Of particular interest is the possible preservation of prebiotic organic materials delivered by ejected fragments of other bodies, including those originating from the surface of early Earth. Lava flow layers would shield the underlying regolith and any carbon-bearing materials within them from most of the effects of space weathering, but the encapsulated organic materials would still be subject to irradiation before they were buried by regolith formation and capped with lava. We have performed a study to simulate the effects of solar radiation on a variety of organic materials mixed with lunar and meteorite analog substrates. A fluence of ∼3 × 10 13 protons cm -2 at 4-13 MeV, intended to be representative of solar energetic particles, has little detectable effect on low-molecular-weight (≤C 30 ) hydrocarbon structures that can be used to indicate biological activity (biomarkers) or the high-molecular-weight hydrocarbon polymer poly(styrene-co-divinylbenzene), and has little apparent effect on a selection of amino acids (≤C 9 ). Inevitably, more lengthy durations of exposure to solar energetic particles may have more deleterious effects, and rapid burial and encapsulation will always be more favorable to organic preservation. Our data indicate that biomarker compounds that may be used to infer biological activity on their parent planet can be relatively resistant to the effects of radiation and may have a high preservation potential in paleoregolith layers on the Moon. Key Words: Radiation-Moon-Regolith-Amino acids-Biomarkers. Astrobiology 16, 900-912.

  19. Organic Matter Responses to Radiation under Lunar Conditions

    Science.gov (United States)

    Matthewman, Richard; Crawford, Ian A.; Jones, Adrian P.; Joy, Katherine H.; Sephton, Mark A.

    2016-11-01

    Large bodies, such as the Moon, that have remained relatively unaltered for long periods of time have the potential to preserve a record of organic chemical processes from early in the history of the Solar System. A record of volatiles and impactors may be preserved in buried lunar regolith layers that have been capped by protective lava flows. Of particular interest is the possible preservation of prebiotic organic materials delivered by ejected fragments of other bodies, including those originating from the surface of early Earth. Lava flow layers would shield the underlying regolith and any carbon-bearing materials within them from most of the effects of space weathering, but the encapsulated organic materials would still be subject to irradiation before they were buried by regolith formation and capped with lava. We have performed a study to simulate the effects of solar radiation on a variety of organic materials mixed with lunar and meteorite analog substrates. A fluence of ˜3 × 1013 protons cm-2 at 4-13 MeV, intended to be representative of solar energetic particles, has little detectable effect on low-molecular-weight (≤C30) hydrocarbon structures that can be used to indicate biological activity (biomarkers) or the high-molecular-weight hydrocarbon polymer poly(styrene-co-divinylbenzene), and has little apparent effect on a selection of amino acids (≤C9). Inevitably, more lengthy durations of exposure to solar energetic particles may have more deleterious effects, and rapid burial and encapsulation will always be more favorable to organic preservation. Our data indicate that biomarker compounds that may be used to infer biological activity on their parent planet can be relatively resistant to the effects of radiation and may have a high preservation potential in paleoregolith layers on the Moon.

  20. NOISY IMAGE SEGMENTATION USING A SELF-ORGANIZING MAP NETWORK

    Directory of Open Access Journals (Sweden)

    Saleh Gorjizadeh

    2015-05-01

    Full Text Available Image segmentation is an essential step in image processing. Many image segmentation methods are available but most of these methods are not suitable for noisy images or they require priori knowledge, such as knowledge on the type of noise. In order to overcome these obstacles, a new image segmentation algorithm is proposed by using a self-organizing map (SOM with some changes in its structure and training data. In this paper, we choose a pixel with its spatial neighbors and two statistical features, mean and median, computed based on a block of pixels as training data for each pixel. This approach helps SOM network recognize a model of noise, and consequently, segment noisy image as well by using spatial information and two statistical features. Moreover, a two cycle thresholding process is used at the end of learning phase to combine or remove extra segments. This way helps the proposed network to recognize the correct number of clusters/segments automatically. A performance evaluation of the proposed algorithm is carried out on different kinds of image, including medical data imagery and natural scene. The experimental results show that the proposed algorithm has advantages in accuracy and robustness against noise in comparison with the well-known unsupervised algorithms.

  1. Conventionalization of the organic sesame network from Burkina Faso: shrinking into mainstream

    NARCIS (Netherlands)

    Glin, L.C.; Mol, A.P.J.; Oosterveer, P.J.M.

    2013-01-01

    This research examines the structure and development of the organic sesame network from Burkina Faso to explain the declining trend in organic sesame export. The paper addresses particularly the question whether the organic sesame network is structurally (re)shaped as a conventional mainstream

  2. Gaussian process regression for sensor networks under localization uncertainty

    Science.gov (United States)

    Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

    2013-01-01

    In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

  3. Transcriptional regulatory networks underlying gene expression changes in Huntington's disease.

    Science.gov (United States)

    Ament, Seth A; Pearl, Jocelynn R; Cantle, Jeffrey P; Bragg, Robert M; Skene, Peter J; Coffey, Sydney R; Bergey, Dani E; Wheeler, Vanessa C; MacDonald, Marcy E; Baliga, Nitin S; Rosinski, Jim; Hood, Leroy E; Carroll, Jeffrey B; Price, Nathan D

    2018-03-26

    Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD We reconstructed a genome-scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF-target gene modules associated with age- and CAG repeat length-dependent gene expression changes in Htt CAG knock-in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF-target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD-related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP-seq) of mouse striatum. We found CAG repeat length-dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

  4. A bilateral frontoparietal network underlies visuospatial analogical reasoning.

    Science.gov (United States)

    Watson, Christine E; Chatterjee, Anjan

    2012-02-01

    Our ability to reason by analogy facilitates problem solving and allows us to communicate ideas efficiently. In this study, we examined the neural correlates of analogical reasoning and, more specifically, the contribution of rostrolateral prefrontal cortex (RLPFC) to reasoning. This area of the brain has been hypothesized to integrate relational information, as in analogy, or the outcomes of subgoals, as in multi-tasking and complex problem solving. Using fMRI, we compared visuospatial analogical reasoning to a control task that was as complex and difficult as the analogies and required the coordination of subgoals but not the integration of relations. We found that analogical reasoning more strongly activated bilateral RLPFC, suggesting that anterior prefrontal cortex is preferentially recruited by the integration of relational knowledge. Consistent with the need for inhibition during analogy, bilateral, and particularly right, inferior frontal gyri were also more active during analogy. Finally, greater activity in bilateral inferior parietal cortex during the analogy task is consistent with recent evidence for the neural basis of spatial relation knowledge. Together, these findings indicate that a network of frontoparietal areas underlies analogical reasoning; we also suggest that hemispheric differences may emerge depending on the visuospatial or verbal/semantic nature of the analogies. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. Efficient organ localization using multi-label convolutional neural networks in thorax-abdomen CT scans

    Science.gov (United States)

    Efrain Humpire-Mamani, Gabriel; Arindra Adiyoso Setio, Arnaud; van Ginneken, Bram; Jacobs, Colin

    2018-04-01

    Automatic localization of organs and other structures in medical images is an important preprocessing step that can improve and speed up other algorithms such as organ segmentation, lesion detection, and registration. This work presents an efficient method for simultaneous localization of multiple structures in 3D thorax-abdomen CT scans. Our approach predicts the location of multiple structures using a single multi-label convolutional neural network for each orthogonal view. Each network takes extra slices around the current slice as input to provide extra context. A sigmoid layer is used to perform multi-label classification. The output of the three networks is subsequently combined to compute a 3D bounding box for each structure. We used our approach to locate 11 structures of interest. The neural network was trained and evaluated on a large set of 1884 thorax-abdomen CT scans from patients undergoing oncological workup. Reference bounding boxes were annotated by human observers. The performance of our method was evaluated by computing the wall distance to the reference bounding boxes. The bounding boxes annotated by the first human observer were used as the reference standard for the test set. Using the best configuration, we obtained an average wall distance of 3.20~+/-~7.33 mm in the test set. The second human observer achieved 1.23~+/-~3.39 mm. For all structures, the results were better than those reported in previously published studies. In conclusion, we proposed an efficient method for the accurate localization of multiple organs. Our method uses multiple slices as input to provide more context around the slice under analysis, and we have shown that this improves performance. This method can easily be adapted to handle more organs.

  6. Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

    Directory of Open Access Journals (Sweden)

    Mitra Darvish

    2014-05-01

    Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

  7. Acting discursively: the development of UK organic food and farming policy networks.

    Science.gov (United States)

    TOMLINSON, Isobel Jane

    2010-01-01

    This paper documents the early evolution of UK organic food and farming policy networks and locates this empirical focus in a theoretical context concerned with understanding the contemporary policy-making process. While policy networks have emerged as a widely acknowledged empirical manifestation of governance, debate continues as to the concept's explanatory utility and usefulness in situations of network and policy transformation since, historically, policy networks have been applied to "static" circumstances. Recognizing this criticism, and in drawing on an interpretivist perspective, this paper sees policy networks as enacted by individual actors whose beliefs and actions construct the nature of the network. It seeks to make links between the characteristics of the policy network and the policy outcomes through the identification of discursively constructed "storylines" that form a tool for consensus building in networks. This study analyses the functioning of the organic policy networks through the discursive actions of policy-network actors.

  8. Self-Organization of Networks Via Synchrony-Dependent Plasticity

    Science.gov (United States)

    Waddell, Jack; Zochowski, Michal

    2006-03-01

    We employ an adaptive parameter control technique based on a previously developed measure that detects phase/lag synchrony in the system to dynamically modify the structure of a network of non-identical, weakly coupled Rössler oscillators. Two processes are simulated: adaptation, under which the initially different properties (such as frequency) of the units converge, and aggregation, in which coupling between units is altered and clusters of interconnected elements are formed based on the temporal correlations. We show that adaptation speed depends on connectivity and topology, with more global connections resulting in greater temporal order and faster convergence of adaptation. We find that aggregation leads to unidirectional clusters, and that asymmetric aggregation (with differing rates for increasing or decreasing coupling strength) has an optimum ratio of rates to make denser clusters that maintain their selectivity. Combining adaptation and aggregation results in clusters of identical oscillators with bi-directional coupling. An optimum ratio of process rates results in stable coupling between the units. Change from this ratio may result in annihilation of the network for slow aggregation, or more numerous, denser, and more transient clusters for faster aggregation.

  9. Extrinsic photoresponse enhancement under additional intrinsic photoexcitation in organic semiconductors

    Energy Technology Data Exchange (ETDEWEB)

    Kounavis, P., E-mail: pkounavis@upatras.gr [Department of Electrical and Computer Engineering, School of Engineering, University of Patras, 26504 Patras (Greece)

    2016-06-28

    Dual light beam photoresponse experiments are employed to explore the photoresponse under simultaneous extrinsic and intrinsic photoexcitation of organic semiconductors. The photoresponse of a red modulated light extrinsic photoexcitation is found that can be significantly enhanced under an additional blue bias-light intrinsic photoexcitation in two terminal pentacene films on glass substrates. From the frequency resolved photoresponse, it is deduced that the phenomenon of photoresponse enhancement can be attributed to an increase in the extrinsic photogeneration rate of the red modulated light and/or an improvement of the drift velocity of carriers under an additional blue light intrinsic photoexcitation. The possible predominant extrinsic photogeneration mechanism, which can be compatible with the observed dependence of the photoresponse enhancement on the frequency and on the light intensities of the red and blue light excitation, is the singlet exciton dissociation through electron transfer to acceptor-like traps. Moreover, an improvement in the drift velocity of carriers traversing grain boundaries with potential energy barriers, which may be reduced by trapping of minority carriers created from the intrinsic photoexcitation, may partly contribute to the photoresponse enhancement.

  10. Robustness of networks against propagating attacks under vaccination strategies

    International Nuclear Information System (INIS)

    Hasegawa, Takehisa; Masuda, Naoki

    2011-01-01

    We study the effect of vaccination on the robustness of networks against propagating attacks that obey the susceptible–infected–removed model. By extending the generating function formalism developed by Newman (2005 Phys. Rev. Lett. 95 108701), we analytically determine the robustness of networks that depends on the vaccination parameters. We consider the random defense where nodes are vaccinated randomly and the degree-based defense where hubs are preferentially vaccinated. We show that, when vaccines are inefficient, the random graph is more robust against propagating attacks than the scale-free network. When vaccines are relatively efficient, the scale-free network with the degree-based defense is more robust than the random graph with the random defense and the scale-free network with the random defense

  11. Application of social network analysis in the assessment of organization infrastructure for service delivery: a three district case study from post-conflict northern Uganda.

    Science.gov (United States)

    Ssengooba, Freddie; Kawooya, Vincent; Namakula, Justine; Fustukian, Suzanne

    2017-10-01

    In post-conflict settings, service coverage indices are unlikely to be sustained if health systems are built on weak and unstable inter-organization networks-here referred to as infrastructure. The objective of this study was to assess the inter-organization infrastructure that supports the provision of selected health services in the reconstruction phase after conflict in northern Uganda. Applied social network analysis was used to establish the structure, size and function among organizations supporting the provision of (1) HIV treatment, (2) maternal delivery services and (3) workforce strengthening. Overall, 87 organizations were identified from 48 respondent organizations in the three post-conflict districts in northern Uganda. A two-stage snowball approach was used starting with service provider organizations in each district. Data included a list of organizations and their key attributes related to the provision of each service for the year 2012-13. The findings show that inter-organization networks are mostly focused on HIV treatment and least for workforce strengthening. The networks for HIV treatment and maternal services were about 3-4 times denser relative to the network for workforce strengthening. The network for HIV treatment accounted for 69-81% of the aggregated network in Gulu and Kitgum districts. In contrast, the network for workforce strengthening contributed the least (6% and 10%) in these two districts. Likewise, the networks supporting a young district (Amuru) was under invested with few organizations and sparse connections. Overall, organizations exhibited a broad range of functional roles in supporting HIV treatment compared to other services in the study. Basic information about the inter-organization setup (infrastructure)-can contribute to knowledge for building organization networks in more equitable ways. More connected organizations can be leveraged for faster communication and resource flow to boost the delivery of health services

  12. Social contact networks and disease eradicability under voluntary vaccination.

    Directory of Open Access Journals (Sweden)

    Ana Perisic

    2009-02-01

    Full Text Available Certain theories suggest that it should be difficult or impossible to eradicate a vaccine-preventable disease under voluntary vaccination: Herd immunity implies that the individual incentive to vaccinate disappears at high coverage levels. Historically, there have been examples of declining coverage for vaccines, such as MMR vaccine and whole-cell pertussis vaccine, that are consistent with this theory. On the other hand, smallpox was globally eradicated by 1980 despite voluntary vaccination policies in many jurisdictions. Previous modeling studies of the interplay between disease dynamics and individual vaccinating behavior have assumed that infection is transmitted in a homogeneously mixing population. By comparison, here we simulate transmission of a vaccine-preventable SEIR infection through a random, static contact network. Individuals choose whether to vaccinate based on infection risks from neighbors, and based on vaccine risks. When neighborhood size is small, rational vaccinating behavior results in rapid containment of the infection through voluntary ring vaccination. As neighborhood size increases (while the average force of infection is held constant, a threshold is reached beyond which the infection can break through partially vaccinated rings, percolating through the whole population and resulting in considerable epidemic final sizes and a large number vaccinated. The former outcome represents convergence between individually and socially optimal outcomes, whereas the latter represents their divergence, as observed in most models of individual vaccinating behavior that assume homogeneous mixing. Similar effects are observed in an extended model using smallpox-specific natural history and transmissibility assumptions. This work illustrates the significant qualitative differences between behavior-infection dynamics in discrete contact-structured populations versus continuous unstructured populations. This work also shows how disease

  13. Blue emitting organic semiconductors under high pressure: status and outlook

    Science.gov (United States)

    Knaapila, Matti; Guha, Suchismita

    2016-06-01

    This review describes essential optical and emerging structural experiments that use high GPa range hydrostatic pressure to probe physical phenomena in blue-emitting organic semiconductors including π-conjugated polyfluorene and related compounds. The work emphasizes molecular structure and intermolecular self-organization that typically determine transport and optical emission in π-conjugated oligomers and polymers. In this context, hydrostatic pressure through diamond anvil cells has proven to be an elegant tool to control structure and interactions without chemical intervention. This has been highlighted by high pressure optical spectroscopy whilst analogous x-ray diffraction experiments remain less frequent. By focusing on a class of blue-emitting π-conjugated polymers, polyfluorenes, this article reviews optical spectroscopic studies under hydrostatic pressure, addressing the impact of molecular and intermolecular interactions on optical excitations, electron-phonon interaction, and changes in backbone conformations. This picture is connected to the optical high pressure studies of other π-conjugated systems and emerging x-ray scattering experiments from polyfluorenes which provides a structure-property map of pressure-driven intra- and interchain interactions. Key obstacles to obtain further advances are identified and experimental methods to resolve them are suggested.

  14. Blue emitting organic semiconductors under high pressure: status and outlook.

    Science.gov (United States)

    Knaapila, Matti; Guha, Suchismita

    2016-06-01

    This review describes essential optical and emerging structural experiments that use high GPa range hydrostatic pressure to probe physical phenomena in blue-emitting organic semiconductors including π-conjugated polyfluorene and related compounds. The work emphasizes molecular structure and intermolecular self-organization that typically determine transport and optical emission in π-conjugated oligomers and polymers. In this context, hydrostatic pressure through diamond anvil cells has proven to be an elegant tool to control structure and interactions without chemical intervention. This has been highlighted by high pressure optical spectroscopy whilst analogous x-ray diffraction experiments remain less frequent. By focusing on a class of blue-emitting π-conjugated polymers, polyfluorenes, this article reviews optical spectroscopic studies under hydrostatic pressure, addressing the impact of molecular and intermolecular interactions on optical excitations, electron-phonon interaction, and changes in backbone conformations. This picture is connected to the optical high pressure studies of other π-conjugated systems and emerging x-ray scattering experiments from polyfluorenes which provides a structure-property map of pressure-driven intra- and interchain interactions. Key obstacles to obtain further advances are identified and experimental methods to resolve them are suggested.

  15. Distributed and organized decision making under resource boundedness

    International Nuclear Information System (INIS)

    Sawaragi, Tetsuo

    1994-01-01

    The coming bottleneck to be overcome in the era of the distributed and open-architectured environment will be the establishment of the rational design and coordination of the total system where multiple decision makers, problem solvers and automated machinery components coexist interacting with each other. In such an environment, they are not achieving some absolute standard of performance with unlimited amounts of resources nor with simple algorithms, but is doing as well as possible given what resources one has. In this article, we focus on the potentials of decision theory as a tool for tackling with the limited rationality under resource boundedness. First, the bottlenecks for establishing the organized and distributed decision making are summarized, and the importance of the formalization of decision activities of intelligent agents is stressed to establish an efficient and effective cooperation by distributed and organized decision making and/or problem solving. Some of the practical systems developed based on such a principle are reviewed briefly with respect to the real-time man-machine collaboration and the cooperative computational framework for the intelligent mobile robots. (author)

  16. RENDEZVOUS: Self-Organizing Services in an Active Network

    National Research Council Canada - National Science Library

    Wetherall, David

    2004-01-01

    .... Not only do we believe that active network techniques have much to offer the overlay, proxy and interposition models that are prevalent in the Internet, but for the most part previous active networks...

  17. Analysis of Network Vulnerability Under Joint Node and Link Attacks

    Science.gov (United States)

    Li, Yongcheng; Liu, Shumei; Yu, Yao; Cao, Ting

    2018-03-01

    The security problem of computer network system is becoming more and more serious. The fundamental reason is that there are security vulnerabilities in the network system. Therefore, it’s very important to identify and reduce or eliminate these vulnerabilities before they are attacked. In this paper, we are interested in joint node and link attacks and propose a vulnerability evaluation method based on the overall connectivity of the network to defense this attack. Especially, we analyze the attack cost problem from the attackers’ perspective. The purpose is to find the set of least costs for joint links and nodes, and their deletion will lead to serious network connection damage. The simulation results show that the vulnerable elements obtained from the proposed method are more suitable for the attacking idea of the malicious persons in joint node and link attack. It is easy to find that the proposed method has more realistic protection significance.

  18. Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder.

    Science.gov (United States)

    Saad, Jacqueline F; Griffiths, Kristi R; Kohn, Michael R; Clarke, Simon; Williams, Leanne M; Korgaonkar, Mayuresh S

    2017-01-01

    Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I ( n  = 16) or as ADHD-C ( n  = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be

  19. Brain networks underlying mental imagery of auditory and visual information.

    Science.gov (United States)

    Zvyagintsev, Mikhail; Clemens, Benjamin; Chechko, Natalya; Mathiak, Krystyna A; Sack, Alexander T; Mathiak, Klaus

    2013-05-01

    Mental imagery is a complex cognitive process that resembles the experience of perceiving an object when this object is not physically present to the senses. It has been shown that, depending on the sensory nature of the object, mental imagery also involves correspondent sensory neural mechanisms. However, it remains unclear which areas of the brain subserve supramodal imagery processes that are independent of the object modality, and which brain areas are involved in modality-specific imagery processes. Here, we conducted a functional magnetic resonance imaging study to reveal supramodal and modality-specific networks of mental imagery for auditory and visual information. A common supramodal brain network independent of imagery modality, two separate modality-specific networks for imagery of auditory and visual information, and a common deactivation network were identified. The supramodal network included brain areas related to attention, memory retrieval, motor preparation and semantic processing, as well as areas considered to be part of the default-mode network and multisensory integration areas. The modality-specific networks comprised brain areas involved in processing of respective modality-specific sensory information. Interestingly, we found that imagery of auditory information led to a relative deactivation within the modality-specific areas for visual imagery, and vice versa. In addition, mental imagery of both auditory and visual information widely suppressed the activity of primary sensory and motor areas, for example deactivation network. These findings have important implications for understanding the mechanisms that are involved in generation of mental imagery. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  20. Self-organized criticality occurs in non-conservative neuronal networks during `up' states

    Science.gov (United States)

    Millman, Daniel; Mihalas, Stefan; Kirkwood, Alfredo; Niebur, Ernst

    2010-10-01

    During sleep, under anaesthesia and in vitro, cortical neurons in sensory, motor, association and executive areas fluctuate between so-called up and down states, which are characterized by distinct membrane potentials and spike rates. Another phenomenon observed in preparations similar to those that exhibit up and down states-such as anaesthetized rats, brain slices and cultures devoid of sensory input, as well as awake monkey cortex-is self-organized criticality (SOC). SOC is characterized by activity `avalanches' with a branching parameter near unity and size distribution that obeys a power law with a critical exponent of about -3/2. Recent work has demonstrated SOC in conservative neuronal network models, but critical behaviour breaks down when biologically realistic `leaky' neurons are introduced. Here, we report robust SOC behaviour in networks of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression. We show analytically and numerically that these networks typically have two stable activity levels, corresponding to up and down states, that the networks switch spontaneously between these states and that up states are critical and down states are subcritical.

  1. Networking by entrepreneurs: patterns of tie formation for emerging organizations

    NARCIS (Netherlands)

    Elfring, T.; Hulsink, W.

    2007-01-01

    There are two conflicting patterns of network development of founding entrepreneurs that emerge from existing literature. One of them evolves from an identity-based network dominated by strong ties into an intentionally managed network rich in weak ties. The other involves the opposite, with weak

  2. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks ...

  3. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the ...

  4. Investigation of organic matter migrating from polymeric pipes into drinking water under different flow manners.

    Science.gov (United States)

    Zhang, Ling; Liu, Shuming; Liu, Wenjun

    2014-02-01

    Polymeric pipes, such as unplasticized polyvinyl chloride (uPVC) pipes, polypropylene random (PPR) pipes and polyethylene (PE) pipes are increasingly used for drinking water distribution lines. Plastic pipes may include some additives like metallic stabilizers and other antioxidants for the protection of the material during its production and use. Thus, some compounds can be released from those plastic pipes and cast a shadow on drinking water quality. This work develops a new procedure to investigate three types of polymer pipes (uPVC, PE and PPR) with respect to the migration of total organic carbon (TOC) into drinking water. The migration test was carried out in stagnant conditions with two types of migration processes, a continuous migration process and a successive migration process. These two types of migration processes are specially designed to mimic the conditions of different flow manners in drinking water pipelines, i.e., the situation of continuous stagnation with long hydraulic retention times and normal flow status with regular water renewing in drinking water networks. The experimental results showed that TOC release differed significantly with different plastic materials and under different flow manners. The order of materials with respect to the total amount of TOC migrating into drinking water was observed as PE > PPR > uPVC under both successive and continuous migration conditions. A higher amount of organic migration from PE and PPR pipes was likely to occur due to more organic antioxidants being used in pipe production. The results from the successive migration tests indicated the trend of the migration intensity of different pipe materials over time, while the results obtained from the continuous migration tests implied that under long stagnant conditions, the drinking water quality could deteriorate quickly with the consistent migration of organic compounds and the dramatic consumption of chlorine to a very low level. Higher amounts of TOC

  5. Business-IT alignment domains and principles for networked organizations: A qualitative multiple case study

    NARCIS (Netherlands)

    Santana Tapia, R.G.; Daneva, Maia; van Eck, Pascal; Castro Cárdenas, N.; van Oene, L.

    2008-01-01

    Applying principles for business-IT alignment in networked organizations seems to be key for their survival in competitive environments. In this paper, we present a qualitative multiple case study conducted in three collaborative networked organizations: (i) an outsourcing relation between an

  6. Robust Evaluation for Transportation Network Capacity under Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Muqing Du

    2017-01-01

    Full Text Available As more and more cities in worldwide are facing the problems of traffic jam, governments have been concerned about how to design transportation networks with adequate capacity to accommodate travel demands. To evaluate the capacity of a transportation system, the prescribed origin and destination (O-D matrix for existing travel demand has been noticed to have a significant effect on the results of network capacity models. However, the exact data of the existing O-D demand are usually hard to be obtained in practice. Considering the fluctuation of the real travel demand in transportation networks, the existing travel demand is represented as uncertain parameters which are defined within a bounded set. Thus, a robust reserve network capacity (RRNC model using min–max optimization is formulated based on the demand uncertainty. An effective heuristic approach utilizing cutting plane method and sensitivity analysis is proposed for the solution of the RRNC problem. Computational experiments and simulations are implemented to demonstrate the validity and performance of the proposed robust model. According to simulation experiments, it is showed that the link flow pattern from the robust solutions to network capacity problems can reveal the probability of high congestion for each link.

  7. DESIGN OF ORGANIZATION AND REALIZATION OF PEDAGOGICAL VIDEO-PRACTICE WITH THE USE OF NETWORK EDUCATIONAL RESOURCE OF ORGANIZATION

    Directory of Open Access Journals (Sweden)

    Константин Михайлович Корнеев

    2017-12-01

    Full Text Available In article the processes proceeding at the organization and carrying out video experts which are subject to modeling are opened requirements to modeling of the organization and carrying out pedagogical video experts are formulated.The order and structure of information exchange between organizers pedagogical video experts during preparation and between its participants are stated during. Development of pourochny planning for the period of passing pedagogical video experts according to the training program, thematic and pourochny planning of the teacher of basic school is discussed. Modeling of the organization and carrying out pedagogical video experts with use of a network educational resource of the organization is analyzed. Requirements to process of modeling of the organization and carrying out pedagogical video experts decide on use of a network educational resource of the organization and development of model.

  8. 76 FR 78216 - Organ Procurement and Transplantation Network

    Science.gov (United States)

    2011-12-16

    ... organs covered by section 301 of NOTA. (73 FR 11420.) HRSA also sought feedback on the optimal way to... of the organ relating to the organ's utility for reconstruction, repair, or replacement--examples of... replacement or supplementation of a recipient's organ with an organ that performs the same basic function or...

  9. Similarity between community structures of different online social networks and its impact on underlying community detection

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2015-03-01

    As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

  10. Resolving Anatomical and Functional Structure in Human Brain Organization: Identifying Mesoscale Organization in Weighted Network Representations

    Science.gov (United States)

    Lohse, Christian; Bassett, Danielle S.; Lim, Kelvin O.; Carlson, Jean M.

    2014-01-01

    Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease. PMID:25275860

  11. Value Systems Alignment Analysis in Collaborative Networked Organizations Management

    OpenAIRE

    Patricia Macedo; Luis Camarinha-Matos

    2017-01-01

    The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assis...

  12. Factors Underlying Farmers’ Decisions to Participate in Networks

    Directory of Open Access Journals (Sweden)

    Bianka Kühne

    2013-11-01

    Full Text Available 800x600 The objective of this elicitation study is to provide insights into farmers’ beliefs which influence their participation in knowledge exchange and innovation networks to enable the enhancement of network participation. A set of facilitating and impeding factors was obtained. Participants identified (a 13 categories of behavioural beliefs (e.g. ‘You learn something’ and ‘Low perceived return on investment’, (b 4 groups of normative beliefs (influence of colleagues, spouses, network coordinators and chain partners and (c 11 control beliefs (facilitators or barriers related to, for example, ‘Network skills’, ‘No time’ and ‘Perceived restraint by farmers in communicating openly and honestly’. Normal 0 21 false false false DE X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0pt 5.4pt 0pt 5.4pt; mso-para-margin:0pt; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}

  13. Genetic Algorithm for Multiuser Discrete Network Design Problem under Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Wu Juan

    2012-01-01

    Full Text Available Discrete network design is an important part of urban transportation planning. The purpose of this paper is to present a bilevel model for discrete network design. The upper-level model aims to minimize the total travel time under a stochastic demand to design a discrete network. In the lower-level model, demands are assigned to the network through a multiuser traffic equilibrium assignment. Generally, discrete network could affect path selections of demands, while the results of the multiuser traffic equilibrium assignment need to reconstruct a new discrete network. An iterative approach including an improved genetic algorithm and Frank-Wolfe algorithm is used to solve the bi-level model. The numerical results on Nguyen Dupuis network show that the model and the related algorithms were effective for discrete network design.

  14. Good Communication: The Other Social Network for Successful IT Organizations

    Science.gov (United States)

    Trubitt, Lisa; Overholtzer, Jeff

    2009-01-01

    Social networks of the electronic variety have become thoroughly embedded in contemporary culture. People have woven these networks into their daily routines, using Facebook, Twitter, LinkedIn, online gaming environments, and other tools to build and maintain complex webs of professional and personal relationships. Chief Information Officers…

  15. Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

    Directory of Open Access Journals (Sweden)

    Zhicong Zhang

    2018-01-01

    Full Text Available We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

  16. Defense strategies for asymmetric networked systems under composite utilities

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Nageswara S. [ORNL; Ma, Chris Y. T. [Hang Seng Management College, Hon Kong; Hausken, Kjell [University of Stavanger, Norway; He, Fei [Texas A& M University, Kingsville, TX, USA; Yau, David K. Y. [Singapore University of Technology and Design; Zhuang, Jun [University at Buffalo (SUNY)

    2017-11-01

    We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the infrastructure failure probability giventhe failure of an individual system or network, and (b) first order differential conditions on system survival probabilities that characterize component-level correlations. We formulate an infrastructure survival game between an attacker and a provider, who attacks and reinforces individual components, respectively. They use the composite utility functions composed of a survival probability term and a cost term, and the previously studiedsum-form and product-form utility functions are their special cases. At Nash Equilibrium, we derive expressions for individual system survival probabilities and the expected total number of operational components. We apply and discuss these estimates for a simplified model of distributed cloud computing infrastructure

  17. Assessing mechanical vulnerability in water distribution networks under multiple failures

    Science.gov (United States)

    Berardi, Luigi; Ugarelli, Rita; Røstum, Jon; Giustolisi, Orazio

    2014-03-01

    Understanding mechanical vulnerability of water distribution networks (WDN) is of direct relevance for water utilities since it entails two different purposes. On the one hand, it might support the identification of severe failure scenarios due to external causes (e.g., natural or intentional events) which result into the most critical consequences on WDN supply capacity. On the other hand, it aims at figure out the WDN portions which are more prone to be affected by asset disruptions. The complexity of such analysis stems from the number of possible scenarios with single and multiple simultaneous shutdowns of asset elements leading to modifications of network topology and insufficient water supply to customers. In this work, the search for the most disruptive combinations of multiple asset failure events is formulated and solved as a multiobjective optimization problem. The higher vulnerability failure scenarios are detected as those causing the lower supplied demand due to the lower number of simultaneous failures. The automatic detection of WDN topology, subsequent to the detachments of failed elements, is combined with pressure-driven analysis. The methodology is demonstrated on a real water distribution network. Results show that, besides the failures causing the detachment of reservoirs, tanks, or pumps, there are other different topological modifications which may cause severe WDN service disruptions. Such information is of direct relevance to support planning asset enhancement works and improve the preparedness to extreme events.

  18. Network architecture underlying maximal separation of neuronal representations

    Directory of Open Access Journals (Sweden)

    Ron A Jortner

    2013-01-01

    Full Text Available One of the most basic and general tasks faced by all nervous systems is extracting relevant information from the organism’s surrounding world. While physical signals available to sensory systems are often continuous, variable, overlapping and noisy, high-level neuronal representations used for decision-making tend to be discrete, specific, invariant, and highly separable. This study addresses the question of how neuronal specificity is generated. Inspired by experimental findings on network architecture in the olfactory system of the locust, I construct a highly simplified theoretical framework which allows for analytic solution of its key properties. For generalized feed-forward systems, I show that an intermediate range of connectivity values between source- and target-populations leads to a combinatorial explosion of wiring possibilities, resulting in input spaces which are, by their very nature, exquisitely sparsely populated. In particular, connection probability ½, as found in the locust antennal-lobe–mushroom-body circuit, serves to maximize separation of neuronal representations across the target Kenyon-cells, and explains their specific and reliable responses. This analysis yields a function expressing response specificity in terms of lower network-parameters; together with appropriate gain control this leads to a simple neuronal algorithm for generating arbitrarily sparse and selective codes and linking network architecture and neural coding. I suggest a way to easily construct ecologically meaningful representations from this code.

  19. Dissolved organic matter enhances microbial mercury methylation under sulfidic conditions

    Science.gov (United States)

    Graham, Andrew M.; Aiken, George R.; Gilmour, Cynthia

    2012-01-01

    Dissolved organic matter (DOM) is generally thought to lower metal bioavailability in aquatic systems due to the formation of metal–DOM complexes that reduce free metal ion concentrations. However, this model may not be pertinent for metal nanoparticles, which are now understood to be ubiquitous, sometimes dominant, metal species in the environment. The influence of DOM on Hg bioavailability to microorganisms was examined under conditions (0.5–5.0 nM Hg and 2–10 μM sulfide) that favor the formation of β-HgS(s) (metacinnabar) nanoparticles. We used the methylation of stable-isotope enriched 201HgCl2 by Desulfovibrio desulfuricans ND132 in short-term washed cell assays as a sensitive, environmentally significant proxy for Hg uptake. Suwannee River humic acid (SRHA) and Williams Lake hydrophobic acid (WLHPoA) substantially enhanced (2- to 38-fold) the bioavailability of Hg to ND132 over a wide range of Hg/DOM ratios (9.4 pmol/mg DOM to 9.4 nmol/mg DOM), including environmentally relevant ratios. Methylmercury (MeHg) production by ND132 increased linearly with either SRHA or WLHPoA concentration, but SRHA, a terrestrially derived DOM, was far more effective at enhancing Hg-methylation than WLHPoA, an aquatic DOM dominated by autochthonous sources. No DOM-dependent enhancement in Hg methylation was observed in Hg–DOM–sulfide solutions amended with sufficient l-cysteine to prevent β-HgS(s) formation. We hypothesize that small HgS particles, stabilized against aggregation by DOM, are bioavailable to Hg-methylating bacteria. Our laboratory experiments provide a mechanism for the positive correlations between DOC and MeHg production observed in many aquatic sediments and wetland soils.

  20. A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

    Directory of Open Access Journals (Sweden)

    Warren D Anderson

    2017-07-01

    Full Text Available Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension. We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

  1. Invulnerability of grown Peer-to-Peer networks under progressive targeted attacks

    Science.gov (United States)

    Peng, Hao; Zhao, Dandan; Han, Jianmin; Lu, Jianfeng

    2015-06-01

    Security issues of Peer-to-Peer (P2P) networks have attracted more and more research in recent years. In this paper, using complex features of P2P networks, we shift the focus to the study of invulnerability of grown P2P networks under progressive targeted attacks. Based on dynamic process and reverse percolation theory, we present several mechanisms that attacked P2P networks can adopt to minimize the disasters aftermath progressive targeted attacks. In this process, we proposed: (i) the dynamics of grown P2P networks under targeted attacks can make sure an attacked P2P network restore a power-law (PL) characteristic to a normal level; (ii) a global degree restoring process from the aftermath of progressive targeted attacks can restore the status of set of high degree peers to normal; (iii) a reverse percolation process glues the fragmented small connected component of a destroyed grown P2P network into a giant connected component (GCC). Experimental results show that an attacked grown P2P network can restore the key characteristics, such as power-law characteristic of original P2P network, the set of high degree peers and the giant connected component, to a regular status. In this way, we can illustrate the invulnerability of progressive targeted attacks on grown P2P networks which is particularly useful in designing complex P2P networks.

  2. Public management and network specificity: Effects of colleges’ ties with professional organizations on graduates’ labour market success and satisfaction

    NARCIS (Netherlands)

    Akkerman, Agnes; Torenvlied, René

    2013-01-01

    Research on managerial networking in the public sector reports positive effects of network activity on performance. However, little is known about which network relations influence different aspects of performance. We argue that for specific organizational goals, organizations should direct their

  3. Small-world organization of self-similar modules in functional brain networks

    Science.gov (United States)

    Sigman, Mariano; Gallos, Lazaros; Makse, Hernan

    2012-02-01

    The modular organization of the brain implies the parallel nature of brain computations. These modules have to remain functionally independent, but at the same time they need to be sufficiently connected to guarantee the unitary nature of brain perception. Small-world architectures have been suggested as probable structures explaining this behavior. However, there is intrinsic tension between shortcuts generating small-worlds and the persistence of modularity. In this talk, we study correlations between the activity in different brain areas. We suggest that the functional brain network formed by the percolation of strong links is highly modular. Contrary to the common view, modules are self-similar and therefore are very far from being small-world. Incorporating the weak ties to the network converts it into a small-world preserving an underlying backbone of well-defined modules. Weak ties are shown to follow a pattern that maximizes information transfer with minimal wiring costs. This architecture is reminiscent of the concept of weak-ties strength in social networks and provides a natural solution to the puzzle of efficient infomration flow in the highly modular structure of the brain.

  4. Computational neural networks: enhancing supervised learning algorithms via self-organization.

    Science.gov (United States)

    Holdaway, R M; White, M W

    1990-04-01

    A neural network processing scheme is proposed which utilizes a self-organizing Kohonen feature map as the front end to a feedforward classifier network. The results of a series of benchmarking studies based upon artificial statistical pattern recognition tasks indicate that the proposed architecture performs significantly better than conventional feedforward classifier networks when the decision regions are disjoint. This is attributed to the fact that the self-organization process allows internal units in the succeeding classifier network to be sensitive to a specific set of features in the input space at the outset of training.

  5. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    Science.gov (United States)

    Ross, Muriel D.; Meyer, Glenn; Lam, Tony; Cutler, Lynn; Vaziri, Parshaw

    1990-01-01

    Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

  6. Artificial neural networks to evaluate organic and inorganic contamination in agricultural soils.

    Science.gov (United States)

    Bonelli, Maria Grazia; Ferrini, Mauro; Manni, Andrea

    2017-11-01

    The assessment of organic and inorganic contaminants in agricultural soils is a difficult challenge due to the large-scale dimensions of the areas under investigation and the great number of samples needed for analysis. On-site screening techniques, such as Field Portable X-ray Fluorescence (FPXRF) spectrometry, can be used for inorganic compounds, such as heavy metals. This method is not destructive and allows a rapid qualitative characterization, identifying hot spots from where to collect soil samples for analysis by traditional laboratory techniques. Recently, fast methods such as immuno-assays for the determination of organic compounds, such as dioxins, furans and PCBs, have been employed, but several limitations compromise their performance. The aim of the present study was to find a method able to screen contaminants in agricultural soil, using FPXRF spectrometry for metals and a statistical procedure, such as the Artificial Neural Networks technique, to estimate unknown concentrations of organic compounds based on statistical relationships between the organic and inorganic pollutants. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

    Science.gov (United States)

    Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

    2012-03-26

    Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

  8. 1 Soil Organic Carbon Dynamics under different plantation crops of ...

    African Journals Online (AJOL)

    Using the SOC as indicator, the soil organic matter content needs to be improved upon for sustainable productivity. ... microorganisms which are involved in litter degradation process. However, there. J S Ogeh* ... by the linear regression study. Keywords: Soil organic carbon, plantation crops, different ages, tropics, cashew,.

  9. Electromechanical properties of carbon nanotube networks under compression

    Czech Academy of Sciences Publication Activity Database

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

    2011-01-01

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

  10. An Adaptive-PSO-Based Self-Organizing RBF Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Lu, Wei; Hou, Ying; Qiao, Jun-Fei

    2018-01-01

    In this paper, a self-organizing radial basis function (SORBF) neural network is designed to improve both accuracy and parsimony with the aid of adaptive particle swarm optimization (APSO). In the proposed APSO algorithm, to avoid being trapped into local optimal values, a nonlinear regressive function is developed to adjust the inertia weight. Furthermore, the APSO algorithm can optimize both the network size and the parameters of an RBF neural network simultaneously. As a result, the proposed APSO-SORBF neural network can effectively generate a network model with a compact structure and high accuracy. Moreover, the analysis of convergence is given to guarantee the successful application of the APSO-SORBF neural network. Finally, multiple numerical examples are presented to illustrate the effectiveness of the proposed APSO-SORBF neural network. The results demonstrate that the proposed method is more competitive in solving nonlinear problems than some other existing SORBF neural networks.

  11. Networking

    OpenAIRE

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

    2016-01-01

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

  12. The Contribution of Network Organization and Integration to the Development of Cognitive Control.

    Directory of Open Access Journals (Sweden)

    Scott Marek

    2015-12-01

    Full Text Available Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI, graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

  13. The Contribution of Network Organization and Integration to the Development of Cognitive Control.

    Science.gov (United States)

    Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

    2015-12-01

    Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

  14. A systematic framework for enterprise-wide optimization: Synthesis and design of processing network under uncertainty

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2013-01-01

    In this paper, a systematic framework for synthesis and design of processing networks under uncertaintyis presented. Through the framework, an enterprise-wide optimization problem is formulated and solvedunder uncertain conditions, to identify the network (composed of raw materials, process techn...

  15. Evaluation of organic Substrates for wheat production under rainfed conditions

    International Nuclear Information System (INIS)

    Muhammad, S.; Tanveer, S.K.; Anjum, A.S.; Javed, A.; Ullah, M.A.

    2013-01-01

    A study was carried out to evaluate the effect of different organic amendments and bio-fertilisers on organic wheat crop at National Agricultural Research Center (NARC), Islamabad during the year 2008-2009. Randomised Complete Block Design (RCBD) with four replications was used. The soil at NARC is slightly alkaline. Organic matter ranges from 0.31-2.50 % in the surface soils and 0.15-2.50 % in sub-soils. Most soils at NARC have low soil organic matter content. The treatments included (a) organic fertilizers 3: 16:1.5 (N:P:K), 15kg N, 85kg P/sub 2/O/sub 5/and 7kg K per acre),(b) organic fertilizers (NPK),15kg N, 85kg P/sub 2/O/sub 5/and 7gK+ Humic acid (8/acre as basel dose and foliar spray), (c) compost (well decomposed and fermented with yeast mixed with molasses) 1000kg/acre (1.5% N,1.2% P/sub 2/ O/sub 5/ and 0.8% K), (d) a control. Different organic products including bio-trace, humic acid (granulated form, i.e. lignatic coal treated with 10% potassium hydroxide) and humic acid alkaline solution in water were applied in the form of foliar spray on the crop (treatments 1 and 3) at six leaves stage, after 1.5 months and at spike emergence stage. The use of organic fertiliser with compost alone or in combination increased growth parameters as well as wheat yield, with maximum biomass (5,788kg/ha). Minimum biomass was recorded in the control treatment. The soil chemical, physical and biological properties were improved with addition of all types of organic substrates. The soil quality relates with its characteristics and microbial dynamism. (author)

  16. [Latin program for organ donation: the intensivists are networking].

    Science.gov (United States)

    Revelly, J-P; Heidegger, C-P; Eckert, P; Moretti, D; Chevrolet, J-C; Chioléro, R

    2008-12-10

    The new Swiss federal law on organ and transplantation strengthens the responsibilities of the intensive care units. In Italian and French speaking parts of Switzerland, the Programme Latin pour le Don d'Organe (PLDO) has been launched to foster a wider collaboration between intensivists and donation coordinators. The PLDO aims at optimising knowledge and expertise in organ donation through improvements in identification, notification and management of organ donors and their next of kin. The PLDO dispenses education to all professionals involved. Such organisation should allow increasing the number of organs available, while improving healthcare professionals experience and next of kin emotion throughout the donation process.

  17. Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

    International Nuclear Information System (INIS)

    Zhou Liming; Zhang Yingyue; Chen Tianlun

    2005-01-01

    Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse, the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.

  18. A neural network model for the self-organization of cortical grating cells.

    Science.gov (United States)

    Bauer, C; Burger, T; Stetter, M; Lang, E W

    2000-01-01

    A neural network model with incremental Hebbian learning of afferent and lateral synaptic couplings is proposed,which simulates the activity-dependent self-organization of grating cells in upper layers of striate cortex. These cells, found in areas V1 and V2 of the visual cortex of monkeys, respond vigorously and exclusively to bar gratings of a preferred orientation and periodicity. Response behavior to varying contrast and to an increasing number of bars in the grating show threshold and saturation effects. Their location with respect to the underlying orientation map and their nonlinear response behavior are investigated. The number of emerging grating cells is controlled in the model by the range and strength of the lateral coupling structure.

  19. Timing of product introduction in network economies under heterogeneous demand

    DEFF Research Database (Denmark)

    Winther, Christian Dahl

    as a function of time and the scope for private rents. First, the paper derives a function showing the intertemporal evolution in market shares as a function of the choices made by the newcomer. Second, under incompatibility of standards each level of research is associated with both a minimum and a maximum...

  20. Network Analysis as a Communication Audit Instrument: Uncovering Communicative Strengths and Weaknesses Within Organizations

    NARCIS (Netherlands)

    Koning, K.H.; de Jong, Menno D.T.

    2015-01-01

    Network analysis is one of the instruments in the communication audit toolbox to diagnose communication problems within organizations. To explore its contribution to a communication audit, the authors conducted a network analysis within three secondary schools, comparing its results with those of

  1. Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

    Science.gov (United States)

    Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen

    2014-01-01

    Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.

  2. Auditing information structures in organizations: A review of data collection techniques for network analysis

    NARCIS (Netherlands)

    Koning, K.H.; de Jong, Menno D.T.

    2005-01-01

    Network analysis is one of the current techniques for investigating organizational communication. Despite the amount of how-to literature about using network analysis to assess information flows and relationships in organizations, little is known about the methodological strengths and weaknesses of

  3. Screening of Soybean (Glycine max L.) Advanced Lines under Organic Management in Turkey

    OpenAIRE

    Kir, Alev; Karagul, Eylem Tugay; Buyukkileci, Ceylan; Kalin, Ahmet

    2015-01-01

    The breeding research of soybean (Glycine max L.) began with advanced lines of “Soybean Breeding Project” supported by MFAL-GDAR in 2013 under organic management for comparing grain legume crops of organic breeding programme of COBRA (Coordinating Organic Plant Breeding Activities for Diversity) project because of priority for this species to be produced organically in Turkey for organic sector at Organic Open Field Experimental Area of AARI located in the Mediterranean Region. Main objective...

  4. The efficiency of the marketing planning model in the network organizations

    OpenAIRE

    Katarzyna Rupik

    2008-01-01

    The aim of the paper is to raise the discussion about the efficiency criteria for the network organizations, which are the reference point for the evaluation of marketing planning efficiency in those organizations. Raising the problem of the nets’ efficiency is to increase the integrative role of the marketing planning within the management of other business processes, not only within the inter-functional (crossfunctional) level, but also within the level of the network relationships (cross-r...

  5. A Study of Tacit Knowledge Transfer Based on Complex Networks Technology in Hierarchical Organizations

    Science.gov (United States)

    Cheng, Tingting; Wang, Hengshan; Wang, Lubang

    In reality, most economic entities are hierarchical organizations. But in the hierarchical organizations tacit knowledge can be transferred across different hierarchies even across different departments. By use of complex networks technology, a hierarchical organization’s framework is modeled in this paper. Through quantifying a number of technical datas we analyze and have a research on the transfer distance and the optimum tacit knowledge transfer path in hierarchy networks.

  6. Epidemic Survivability: Characterizing Networks Under Epidemic-like Failure Propagation Scenarios

    DEFF Research Database (Denmark)

    Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

    2013-01-01

    in telecommunication networks has not been extensively considered, nowadays, with the increasing computation capacity and complexity of operating systems of modern network devices (routers, switches, etc.), the study of possible epidemic-like failure scenarios must be taken into account. When epidemics occur......, such as in other multiple failure scenarios, identifying the level of vulnerability offered by a network is one of the main challenges. In this paper, we present epidemic survivability, a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Moreover......, this metric is able to identify the set of nodes which are more vulnerable under an epidemic attack. In addition, two applications of epidemic survivability are provided. First, we introduce epidemic criticality, a novel robustness metric for epidemic failure scenarios. A case study shows the utility...

  7. Information Diffusion in Facebook-Like Social Networks Under Information Overload

    Science.gov (United States)

    Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

    2013-07-01

    Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

  8. Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

    Science.gov (United States)

    Del Papa, Bruno; Priesemann, Viola; Triesch, Jochen

    2017-01-01

    Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions - matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model's performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN's spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.

  9. Some potentialities of living organisms under simulated Martian conditions.

    Science.gov (United States)

    Lozina-Lozinsky, L K; Bychenkova, V N; Zaar, E I; Levin, V L; Rumyantseva, V M

    1971-01-01

    Temperature, humidity, pressure, composition of the atmosphere and radiation are the main factors conditioning life on the surface of Mars. When studying the Martian ecology, one must know the total effect of these factors. One may expect that, as a result of adaptation to low temperatures, there is a corresponding shift in the temperature optimum of enzymatic activity. Dryness is the main obstacle to active life. We suggest the presence of some soil moisture and water vapour. Moreover, there can be areas of permafrost. This minimum supply of water and periodic fluctuations of humidity may create conditions for the existence of drought-resistant organisms. Decreased atmospheric pressure alone does not affect micro-organisms, plants, protozoa and even insects. Ciliates reproduce in a flowing atmosphere of pure nitrogen containing 0.0002-0.0005% oxygen as an impurity. Protozoa may also develop in an atmosphere of 98-99% carbon dioxide mixed with 1% O2. Therefore, even traces of oxygen in the Martian atmosphere would be sufficient for aerobic unicellular organisms. Cells and organisms on earth have acquired various ways of protection from uv light, and therefore may increase their resistance further by adaptation or selection. The resistance of some organisms to ionizing radiation is high enough to enable them to endure hard ionizing radiation of the sun. Experiments with unicellular [correction of unicellar] organisms show that the effect of short wave uv radiation depends on the intensity of visible light, long-wave solar uv radiation, temperatures, cell repair processes, and the state of cell components, i.e. whether the cell was frozen, dried or hydrated.

  10. Memory under stress: from single systems to network changes.

    Science.gov (United States)

    Schwabe, Lars

    2017-02-01

    Stressful events have profound effects on learning and memory. These effects are mainly mediated by catecholamines and glucocorticoid hormones released from the adrenals during stressful encounters. It has been known for long that both catecholamines and glucocorticoids influence the functioning of the hippocampus, a critical hub for episodic memory. However, areas implicated in other forms of memory, such as the insula or the dorsal striatum, can be affected by stress as well. Beyond changes in single memory systems, acute stress triggers the reconfiguration of large scale neural networks which sets the stage for a shift from thoughtful, 'cognitive' control of learning and memory toward more reflexive, 'habitual' processes. Stress-related alterations in amygdala connectivity with the hippocampus, dorsal striatum, and prefrontal cortex seem to play a key role in this shift. The bias toward systems proficient in threat processing and the implementation of well-established routines may facilitate coping with an acute stressor. Overreliance on these reflexive systems or the inability to shift flexibly between them, however, may represent a risk factor for psychopathology in the long-run. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

    Science.gov (United States)

    Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

    2015-01-01

    The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

  12. Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

    Directory of Open Access Journals (Sweden)

    Kaat Alaerts

    Full Text Available The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON. Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD have deficits in the social domain and exhibit alterations in this neural network.Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC.Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength. Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD.While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

  13. On design principles for self-organizing network functions

    NARCIS (Netherlands)

    Altman, Z.; Amirijoo, M.; Gunnarsson, F.; Hoffmann, H.; Kovács, I.Z.; Laselva, D.; Sas, B.; Spaey, K.; Tall, A.; Berg, H. van den; Zetterberg, K.

    2014-01-01

    With an increasing number of SON functions deployed in cellular radio networks, conflicts between the actions proposed by independently-designed and distributed SON functions may arise. The process of minimizing the occurrence, and the consequences, of such conflicts is referred to as SON

  14. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... Caenorhabditis elegans (Chatterjee and Sinha 2007) and the protein interaction network of Escherichia coli (Lin et al. 2009). Recently, this decomposition technique has been used to disentangle the hierarchical structure of Internet router-level connection topology (Zhang et al. 2009), to show that software ...

  15. Connectomics and neuroticism : an altered functional network organization

    NARCIS (Netherlands)

    Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard; Ormel, Johan; Riese, Harriëtte; Aleman, André

    The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network

  16. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein.

  17. A Graph theoretical approach to study the organization of the cortical networks during different mathematical tasks.

    Science.gov (United States)

    Klados, Manousos A; Kanatsouli, Kassia; Antoniou, Ioannis; Babiloni, Fabio; Tsirka, Vassiliki; Bamidis, Panagiotis D; Micheloyannis, Sifis

    2013-01-01

    The two core systems of mathematical processing (subitizing and retrieval) as well as their functionality are already known and published. In this study we have used graph theory to compare the brain network organization of these two core systems in the cortical layer during difficult calculations. We have examined separately all the EEG frequency bands in healthy young individuals and we found that the network organization at rest, as well as during mathematical tasks has the characteristics of Small World Networks for all the bands, which is the optimum organization required for efficient information processing. The different mathematical stimuli provoked changes in the graph parameters of different frequency bands, especially the low frequency bands. More specific, in Delta band the induced network increases it's local and global efficiency during the transition from subitizing to retrieval system, while results suggest that difficult mathematics provoke networks with higher cliquish organization due to more specific demands. The network of the Theta band follows the same pattern as before, having high nodal and remote organization during difficult mathematics. Also the spatial distribution of the network's weights revealed more prominent connections in frontoparietal regions, revealing the working memory load due to the engagement of the retrieval system. The cortical networks of the alpha brainwaves were also more efficient, both locally and globally, during difficult mathematics, while the fact that alpha's network was more dense on the frontparietal regions as well, reveals the engagement of the retrieval system again. Concluding, this study gives more evidences regarding the interaction of the two core systems, exploiting the produced functional networks of the cerebral cortex, especially for the difficult mathematics.

  18. On the underlying assumptions of threshold Boolean networks as a model for genetic regulatory network behavior.

    Science.gov (United States)

    Tran, Van; McCall, Matthew N; McMurray, Helene R; Almudevar, Anthony

    2013-01-01

    Boolean networks (BoN) are relatively simple and interpretable models of gene regulatory networks. Specifying these models with fewer parameters while retaining their ability to describe complex regulatory relationships is an ongoing methodological challenge. Additionally, extending these models to incorporate variable gene decay rates, asynchronous gene response, and synergistic regulation while maintaining their Markovian nature increases the applicability of these models to genetic regulatory networks (GRN). We explore a previously-proposed class of BoNs characterized by linear threshold functions, which we refer to as threshold Boolean networks (TBN). Compared to traditional BoNs with unconstrained transition functions, these models require far fewer parameters and offer a more direct interpretation. However, the functional form of a TBN does result in a reduction in the regulatory relationships which can be modeled. We show that TBNs can be readily extended to permit self-degradation, with explicitly modeled degradation rates. We note that the introduction of variable degradation compromises the Markovian property fundamental to BoN models but show that a simple state augmentation procedure restores their Markovian nature. Next, we study the effect of assumptions regarding self-degradation on the set of possible steady states. Our findings are captured in two theorems relating self-degradation and regulatory feedback to the steady state behavior of a TBN. Finally, we explore assumptions of synchronous gene response and asynergistic regulation and show that TBNs can be easily extended to relax these assumptions. Applying our methods to the budding yeast cell-cycle network revealed that although the network is complex, its steady state is simplified by the presence of self-degradation and lack of purely positive regulatory cycles.

  19. An effective method to improve the robustness of small-world networks under attack

    International Nuclear Information System (INIS)

    Zhang Zheng-Zhen; Xu Wen-Jun; Lin Jia-Ru; Zeng Shang-You

    2014-01-01

    In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario. (interdisciplinary physics and related areas of science and technology)

  20. Light fraction of soil organic matter under different management ...

    African Journals Online (AJOL)

    A study on light fraction organic matter was carried out on the soil from three different management systems namely; Gmelina arborea, Tectona grandis and Leucaena leucocephala plantations in the University of Agriculture, Abeokuta Nigeria. Soil samples were collected in each of the three management site at five auger ...

  1. Fertilization management in bean crop under organic production system

    Directory of Open Access Journals (Sweden)

    Leandro Barradas Pereira

    2015-03-01

    Full Text Available Nowadays the food production systems tend to include the sustainable management of soil and water. One of the main obstacles to the organic cultivation of common bean is the fertilization management. This study aimed to evaluate doses of organic fertilizer containing slaughterhouse residues (1.0 t ha-1, 1.5 t ha-1, 2.0 t ha-1 and 2.5 t ha-1. The experimental design was randomized blocks in a 4x2x2 factorial scheme, with 16 treatments and 4 replications. Plant dry weight; foliar diagnose; initial and final plant population; number of pods per plant, grains per plant and grains per pod; 1000-grain weight; and grain yield were evaluated. It was concluded that the methods and time of organic fertilizer application do not affect the production components and yield in common bean. The dose of 2.5 t ha-1 of organic fertilizer provided the highest common bean yield in 2012, but it did not express its maximum production capacity.

  2. The Role of Network Administrative Organizations in the Development of Social Capital in Inter‐Organizational Food Networks

    Directory of Open Access Journals (Sweden)

    Virginie M. Lefebvre

    2013-02-01

    Full Text Available This paper is concerned with the role of network administrative organizations (NAOs in the development of social capital in inter‐organizational networks aiming at supporting their members to innovate in the food sector through interacting with one another. A multi‐case study approach is used whereby three Belgian inter‐organizational networks are investigated i.e. Wagralim, Réseau‐Club and Flanders Food. Our study shows that there are many options available to NAOs to build social capital within the networks they are responsible for; options which we propose to categorize in three main distinct groups: creation of boundary objects, careful selection of members and effective communication.

  3. Utilization of extended bayesian networks in decision making under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Van Eeckhout, Edward M [Los Alamos National Laboratory; Leishman, Deborah A [Los Alamos National Laboratory; Gibson, William L [Los Alamos National Laboratory

    2009-01-01

    Bayesian network tool (called IKE for Integrated Knowledge Engine) has been developed to assess the probability of undesirable events. The tool allows indications and observables from sensors and/or intelligence to feed directly into hypotheses of interest, thus allowing one to quantify the probability and uncertainty of these events resulting from very disparate evidence. For example, the probability that a facility is processing nuclear fuel or assembling a weapon can be assessed by examining the processes required, establishing the observables that should be present, then assembling information from intelligence, sensors and other information sources related to the observables. IKE also has the capability to determine tasking plans, that is, prioritize which observable should be collected next to most quickly ascertain the 'true' state and drive the probability toward 'zero' or 'one.' This optimization capability is called 'evidence marshaling.' One example to be discussed is a denied facility monitoring situation; there is concern that certain process(es) are being executed at the site (due to some intelligence or other data). We will show how additional pieces of evidence will then ascertain with some degree of certainty the likelihood of this process(es) as each piece of evidence is obtained. This example shows how both intelligence and sensor data can be incorporated into the analysis. A second example involves real-time perimeter security. For this demonstration we used seismic, acoustic, and optical sensors linked back to IKE. We show how these sensors identified and assessed the likelihood of 'intruder' versus friendly vehicles.

  4. Identifying Opinion Leaders to Promote Organ Donation on Social Media: Network Study

    Science.gov (United States)

    Salmon, Charles T

    2018-01-01

    Background In the recent years, social networking sites (SNSs, also called social media) have been adopted in organ donation campaigns, and recruiting opinion leaders for such campaigns has been found effective in promoting behavioral changes. Objective The aim of this paper was to focus on the dissemination of organ donation tweets on Weibo, the Chinese equivalent of Twitter, and to examine the opinion leadership in the retweet network of popular organ donation messages using social network analysis. It also aimed to investigate how personal and social attributes contribute to a user’s opinion leadership on the topic of organ donation. Methods All messages about organ donation posted on Weibo from January 1, 2015 to December 31, 2015 were extracted using Python Web crawler. A retweet network with 505,047 nodes and 545,312 edges of the popular messages (n=206) was constructed and analyzed. The local and global opinion leaderships were measured using network metrics, and the roles of personal attributes, professional knowledge, and social positions in obtaining the opinion leadership were examined using general linear model. Results The findings revealed that personal attributes, professional knowledge, and social positions predicted individual’s local opinion leadership in the retweet network of popular organ donation messages. Alternatively, personal attributes and social positions, but not professional knowledge, were significantly associated with global opinion leadership. Conclusions The findings of this study indicate that health campaign designers may recruit peer leaders in SNS organ donation promotions to facilitate information sharing among the target audience. Users who are unverified, active, well connected, and experienced with information and communications technology (ICT) will accelerate the sharing of organ donation messages in the global environment. Medical professionals such as organ transplant surgeons who can wield a great amount of

  5. Identifying Opinion Leaders to Promote Organ Donation on Social Media: Network Study.

    Science.gov (United States)

    Shi, Jingyuan; Salmon, Charles T

    2018-01-09

    In the recent years, social networking sites (SNSs, also called social media) have been adopted in organ donation campaigns, and recruiting opinion leaders for such campaigns has been found effective in promoting behavioral changes. The aim of this paper was to focus on the dissemination of organ donation tweets on Weibo, the Chinese equivalent of Twitter, and to examine the opinion leadership in the retweet network of popular organ donation messages using social network analysis. It also aimed to investigate how personal and social attributes contribute to a user's opinion leadership on the topic of organ donation. All messages about organ donation posted on Weibo from January 1, 2015 to December 31, 2015 were extracted using Python Web crawler. A retweet network with 505,047 nodes and 545,312 edges of the popular messages (n=206) was constructed and analyzed. The local and global opinion leaderships were measured using network metrics, and the roles of personal attributes, professional knowledge, and social positions in obtaining the opinion leadership were examined using general linear model. The findings revealed that personal attributes, professional knowledge, and social positions predicted individual's local opinion leadership in the retweet network of popular organ donation messages. Alternatively, personal attributes and social positions, but not professional knowledge, were significantly associated with global opinion leadership. The findings of this study indicate that health campaign designers may recruit peer leaders in SNS organ donation promotions to facilitate information sharing among the target audience. Users who are unverified, active, well connected, and experienced with information and communications technology (ICT) will accelerate the sharing of organ donation messages in the global environment. Medical professionals such as organ transplant surgeons who can wield a great amount of influence on their direct connections could also effectively

  6. Formation Features of the Customer Segments for the Network Organizations in the Smart Era

    Directory of Open Access Journals (Sweden)

    Elena V. Yaroshenko

    2017-01-01

    Full Text Available Modern network society is based on the advances of information era of Smart, connecting information and communication technologies, intellectual resources and new forms of managing in the global electronic space. It leads to domination of network forms of the organization of economic activity. Many experts prove the importance of segmentation process of consumers when developing competitive strategy of the organization. Every company needs a competent segmentation of the customer base, allowing to concentrate the attention on satisfaction of requirements of the most perspective client segments. The network organizations have specific characteristics; therefore, it is important to understand how they can influence on the formation of client profiles. It causes the necessity of the network organizations’ research in terms of management of high-profitable client segments.The aim of this study is to determine the characteristics of the market segmentation and to choose the key customers for the network organizations. This purpose has defined the statement and the solution of the following tasks: to explore characteristic features of the network forms of the organization of economic activity of the companies, their prospects, Smart technologies’ influence on them; to reveal the work importance with different client profiles; to explore the existing methods and tools of formation of key customer segments; to define criteria for selection of key groups; to reveal the characteristics of customer segments’ formation for the network organizations.In the research process, methods of the system analysis, a method of analogies, methods of generalizations, a method of the expert evaluations, methods of classification and clustering were applied.This paper explores the characteristics and principles of functioning of network organizations, the appearance of which is directly linked with the development of Smart society. It shows the influence on the

  7. Tackling learning intractability through topological organization and regulation of cortical networks.

    Science.gov (United States)

    Thangavelautham, Jekanthan; D'Eleuterio, Gabriele M T

    2012-04-01

    A key challenge in evolving control systems for robots using neural networks is training tractability. Evolving monolithic fixed topology neural networks is shown to be intractable with limited supervision in high dimensional search spaces. Common strategies to overcome this limitation are to provide more supervision by encouraging particular solution strategies, manually decomposing the task and segmenting the search space and network. These strategies require a supervisor with domain knowledge and may not be feasible for difficult tasks where novel concepts are required. The alternate strategy is to use self-organized task decomposition to solve difficult tasks with limited supervision. The artificial neural tissue (ANT) approach presented here uses self-organized task decomposition to solve tasks. ANT inspired by neurobiology combines standard neural networks with a novel wireless signaling scheme modeling chemical diffusion of neurotransmitters. These chemicals are used to dynamically activate and inhibit wired network of neurons using a coarse-coding framework. Using only a global fitness function that does not encourage a predefined solution, modular networks of neurons are shown to self-organize and perform task decomposition. This approach solves the sign-following task found to be intractable with conventional fixed and variable topology networks. In this paper, key attributes of the ANT architecture that perform self-organized task decomposition are shown. The architecture is robust and scalable to number of neurons, synaptic connections, and initialization parameters.

  8. Basal organic phosphorus mineralization in soils under different farming systems

    OpenAIRE

    Oehl, F.; Frossard, E.; Fliessbach, A.; Dubois, D.; Oberson, A.

    2004-01-01

    Soil organic P (Po) mineralization plays an important role in soil P cycling. Quantitative information on the release of available inorganic P (Pi) by this process is difficult to obtain because any mineralized Pi gets rapidly sorbed. We applied a new approach to quantify basal soil Po mineralization, based on 33PO4 isotopic dilution during 10 days of incubation, in soils differing in microbiological activity. The soils originated from a 20 years old field experiment, including a conventional...

  9. Self-Organized Stationary Patterns in Networks of Bistable Chemical Reactions.

    Science.gov (United States)

    Kouvaris, Nikos E; Sebek, Michael; Mikhailov, Alexander S; Kiss, István Z

    2016-10-10

    Experiments with networks of discrete reactive bistable electrochemical elements organized in regular and nonregular tree networks are presented to confirm an alternative to the Turing mechanism for the formation of self-organized stationary patterns. The results show that the pattern formation can be described by the identification of domains that can be activated individually or in combinations. The method also enabled the localization of chemical reactions to network substructures and the identification of critical sites whose activation results in complete activation of the system. Although the experiments were performed with a specific nickel electrodissolution system, they reproduced all the salient dynamic behavior of a general network model with a single nonlinearity parameter. Thus, the considered pattern-formation mechanism is very robust, and similar behavior can be expected in other natural or engineered networked systems that exhibit, at least locally, a treelike structure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. High-Dimensional Neural Network Potentials for Organic Reactions and an Improved Training Algorithm.

    Science.gov (United States)

    Gastegger, Michael; Marquetand, Philipp

    2015-05-12

    Artificial neural networks (NNs) represent a relatively recent approach for the prediction of molecular potential energies, suitable for simulations of large molecules and long time scales. By using NNs to fit electronic structure data, it is possible to obtain empirical potentials of high accuracy combined with the computational efficiency of conventional force fields. However, as opposed to the latter, changing bonding patterns and unusual coordination geometries can be described due to the underlying flexible functional form of the NNs. One of the most promising approaches in this field is the high-dimensional neural network (HDNN) method, which is especially adapted to the prediction of molecular properties. While HDNNs have been mostly used to model solid state systems and surface interactions, we present here the first application of the HDNN approach to an organic reaction, the Claisen rearrangement of allyl vinyl ether to 4-pentenal. To construct the corresponding HDNN potential, a new training algorithm is introduced. This algorithm is termed "element-decoupled" global extended Kalman filter (ED-GEKF) and is based on the decoupled Kalman filter. Using a metadynamics trajectory computed with density functional theory as reference data, we show that the ED-GEKF exhibits superior performance - both in terms of accuracy and training speed - compared to other variants of the Kalman filter hitherto employed in HDNN training. In addition, the effect of including forces during ED-GEKF training on the resulting potentials was studied.

  11. Small Faith-Related Organizations as Partners in Local Social Service Networks

    Directory of Open Access Journals (Sweden)

    David Campbell

    2016-05-01

    Full Text Available Efforts to enlist small faith-related organizations as partners in public service delivery raise many questions. Using community social service networks as the unit of analysis, this paper asks one with broader relevance to nonprofit sector managers: What factors support and constrain effective integration of these organizations into a local service delivery network? The evidence and illustrations come from longitudinal case studies of five faith-related organizations who received their first government contract as part of a California faith-based initiative. By comparing the organizational development and network partnership trajectories of these organizations over more than a decade, the analysis identifies four key variables influencing partnership dynamics and outcomes: organizational niche within the local network; leadership connections and network legitimacy; faith-inspired commitments and persistence; and core organizational competencies and capacities. The evidence supports shifting the focus of faith-based initiatives to emphasize local planning and network development, taking into account how these four variables apply to specific organizations and their community context.

  12. Knowledge Sharing in Non-Knowledge Intensive Organizations: When Social Networks do not Matter?

    NARCIS (Netherlands)

    J. van der Capellen (Joey); O.R. Koppius (Otto); K. Dittrich (Koen)

    2011-01-01

    textabstractConsiderable attention has been paid to the network determinants of knowledge sharing. However, most, if not all, of the studies investigating the determinants of knowledge sharing are either focused on knowledge-intensive organizations such as consultancy firms or R&D organizations, or

  13. Leadership of Self-Organized Networks Lessons from the War on Terror

    Science.gov (United States)

    Wheatley, Margaret J.

    2007-01-01

    In the past few decades, scientists have developed a rich understanding of how living systems organize and function. They describe life's capacity to self-organize as networks of interdependent relationships, to learn and adapt, and to grow more capable and orderly over time. These dynamics and descriptions stand in stark contrast to how we humans…

  14. Are specific testing protocols required for organic onion varieties? Analysis of onion variety testing under conventional and organic growing conditions

    NARCIS (Netherlands)

    Lammerts Van Bueren, E.; Osman, A.M.; Tiemens-Hulscher, M.; Struik, P.C.; Burgers, S.L.G.E.; Broek, van den R.C.F.M.

    2012-01-01

    Organic growers need information on variety performance under their growing conditions. A 4-year onion variety research project was carried out to investigate whether setting up a variety testing system combining conventional and organic variety trials is feasible and efficient rather than

  15. Use of Artificial Neural Network Models to Predict Indicator Organism Concentrations in an Urban Watershed

    Science.gov (United States)

    Mas, D. M.; Ahlfeld, D. P.

    2004-05-01

    Forecasting stream water quality is important for numerous aspects of resource protection and management. Fecal coliform and enteroccocus are primary indicator organisms used to assess potential pathogen contamination. Consequently, modeling the occurrence and concentration of fecal coliform and enterococcus is an important tool in watershed management. In addition, analyzing the relationship between model input and predicted indicator organisms is useful for elucidating possible sources of contamination and mechanisms of transport. While many process-based, statistical, and empirical models exist for water quality prediction, artificial neural network (ANN) models are increasingly being used for forecasting of water resources variables because ANNs are often capable of modeling complex systems for which behavioral rules are either unknown or difficult to simulate. The performance of ANNs compared to more established modeling approaches such as multiple linear regression (MLR) remains an importance research question. Data collected the U.S. Geological Survey in the lower Charles River in Massachusetts, USA in 1999-2000 was examined to determine correlation between various water quality constituents and indicator organisms and to explore the relationship between rainfall characteristics and indicator organism concentrations. Using the results of the statistical analysis to guide the selection of explanatory variables, MLR was performed to develop predictive equations for wet weather and dry weather conditions. The results show that the best-performing predictor variables are generally consistent for both indicator organisms considered. In addition, the regression equations show increasing indicator organism concentrations as a function of suspended sediment concentrations and length of time since last precipitation event, suggesting accumulation and wash off as a key mechanism of pathogen transport under wet weather conditions. This research also presents the

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-08-01

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

  17. Functional MRI as a tool for investigating networks underlying the orienting reflex

    International Nuclear Information System (INIS)

    Lagopoulos, J.; Ward, P.B.; Rennie, C.; University of Sydney,; Williams, L.; Gordon, E.

    2001-01-01

    Full text: The 'Orienting Reflex' (OR) indexed by skin conductance response (SCR) is a physiological response to novel stimuli, orienting the organism to examine the stimulus in detail. The OR is also associated with lowering of thresholds in sensory-motor networks and preparation for action. The specific anatomical origins of the OR have long been speculated upon, and have primarily been derived from lesion studies on animals. Our group have developed a system to simultaneously acquire a measure of electrodermal orienting (SCR) with fMRI whilst the subject is undertaking an auditory oddball paradigm. The spatial and temporal resolution achievable with fMRI allows elucidation of the networks underlying the generation of ORs and their consequent inhibition with stimulus repetition. We tested five right handed healthy volunteers on an event related FMR paradigm using echoplanar MR images acquired on a 1.5T MRI scanner retrofitted with advanced NMR hardware using a standard head coil. The auditory oddball paradigm was delivered to the volunteers using a Silent Scan system with a button press response for target detection. SCR data was acquired simultaneously using an SCR device specifically designed for use in an MR environment. The significance (p<0.001)activation maps for the targets associated with an OR vs targets which did not elicit an OR, indicate a unilateral activation in the anterior thalamus, anterior cingulate gyrus and lateral orbitofrontal cortex. Target stimuli with no OR (versus background stimuli) revealed activations bilaterally in the supramarginal gyrus, the right thalamus and the anterior cingulate gyrus. Copyright (2001) Australian Neuroscience Society

  18. Organizing principles underlying microorganism's growth-robustness trade-off.

    Science.gov (United States)

    Bolli, Alessandro; Salvador, Armindo

    2014-10-01

    Growth Robustness Reciprocity (GRR) is an intriguing microbial manifestation: the impairment of microorganism's growth enhances their ability to resist acute stresses, and vice-versa. This is caused by regulatory interactions that determine higher expression of protection mechanisms in response to low growth rates. But because such regulatory mechanisms are species-specific, GRR must result from convergent evolution. Why does natural selection favor such an outcome? We used mathematical models of optimal cellular resource allocation to identify the general principles underlying GRR. Non-linear optimization allowed to predict allocation patterns of biosynthetic resources (ribosomes devoted to the synthesis of each cell component) that maximize growth. These models predict the down-regulation of stress defenses under high substrate availabilities and low stress levels. Under these conditions, stress tolerance ensues from growth-related damage dilution: the higher the substrate availability, the fastest the dilution of damaged proteins by newly synthesized proteins, the lower the accumulation of damaged components into the cell. In turn, under low substrate availability growth is too slow for effective damage dilution, and the expression of the defenses up to some optimal level then increases growth. As a consequence, slow-growing cells are pre-adapted to withstand acute stresses. Therefore, the observed negative correlation between growth and stress tolerance can be explained as a consequence of optimal resource allocation for maximal growth. We acknowledge fellowship SFRH/BPD/90065/2012 and grants PEst-C/SAU/LA0001/2013-2014 and FCOMP-01-0124-FEDER-020978 financed by FEDER through the "Programa Operacional Factores de Competitividade, COMPETE" and by national funds through "FCT, Fundação para a Ciência e a Tecnologia" (project PTDC/QUI-BIQ/119657/2010). Copyright © 2014. Published by Elsevier Inc.

  19. Emergence of heterogeneity and political organization in information exchange networks.

    Science.gov (United States)

    Guttenberg, Nicholas; Goldenfeld, Nigel

    2010-04-01

    We present a simple model of the emergence of the division of labor and the development of a system of resource subsidy from an agent-based model of directed resource production with variable degrees of trust between the agents. The model has three distinct phases corresponding to different forms of societal organization: disconnected (independent agents), homogeneous cooperative (collective state), and inhomogeneous cooperative (collective state with a leader). Our results indicate that such levels of organization arise generically as a collective effect from interacting agent dynamics and may have applications in a variety of systems including social insects and microbial communities.

  20. The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

    International Nuclear Information System (INIS)

    Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

    2016-01-01

    Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

  1. A systematic molecular circuit design method for gene networks under biochemical time delays and molecular noises

    Directory of Open Access Journals (Sweden)

    Chang Yu-Te

    2008-11-01

    Full Text Available Abstract Background Gene networks in nanoscale are of nonlinear stochastic process. Time delays are common and substantial in these biochemical processes due to gene transcription, translation, posttranslation protein modification and diffusion. Molecular noises in gene networks come from intrinsic fluctuations, transmitted noise from upstream genes, and the global noise affecting all genes. Knowledge of molecular noise filtering and biochemical process delay compensation in gene networks is crucial to understand the signal processing in gene networks and the design of noise-tolerant and delay-robust gene circuits for synthetic biology. Results A nonlinear stochastic dynamic model with multiple time delays is proposed for describing a gene network under process delays, intrinsic molecular fluctuations, and extrinsic molecular noises. Then, the stochastic biochemical processing scheme of gene regulatory networks for attenuating these molecular noises and compensating process delays is investigated from the nonlinear signal processing perspective. In order to improve the robust stability for delay toleration and noise filtering, a robust gene circuit for nonlinear stochastic time-delay gene networks is engineered based on the nonlinear robust H∞ stochastic filtering scheme. Further, in order to avoid solving these complicated noise-tolerant and delay-robust design problems, based on Takagi-Sugeno (T-S fuzzy time-delay model and linear matrix inequalities (LMIs technique, a systematic gene circuit design method is proposed to simplify the design procedure. Conclusion The proposed gene circuit design method has much potential for application to systems biology, synthetic biology and drug design when a gene regulatory network has to be designed for improving its robust stability and filtering ability of disease-perturbed gene network or when a synthetic gene network needs to perform robustly under process delays and molecular noises.

  2. Uranium mining and metallurgy library information service under the network environment

    International Nuclear Information System (INIS)

    Tang Lilei

    2012-01-01

    This paper analyzes the effect of the network environment on the uranium mining and metallurgy of the information service. Introduces some measures such as strengthening professional characteristic literature resources construction, changing the service mode, building up information navigation, deepening service, meet the individual needs of users, raising librarian's quality, promoting the co-construction and sharing of library information resources, and puts forward the development idea of uranium mining and metallurgy library information service under the network environment. (author)

  3. 78 FR 40033 - Organ Procurement and Transplantation Network

    Science.gov (United States)

    2013-07-03

    ... to the organ's utility for reconstruction, repair, or replacement--examples of minimal manipulation include cutting, grinding, and shaping of a VCA); (6) for homologous use (i.e., the replacement or... identify best practices for optimal VCA transplant outcomes. 7. Risks of VCA Transplantation to Recipients...

  4. Power, surveillance and digital network media in organizations

    DEFF Research Database (Denmark)

    Tække, Jesper

    With the focus on organizations, this article describes power in relation to mediated surveillance using Luhmann’s systems theory, poststructuralist theory and theory of media sociography. It aims to sketch out the main issues in contemporary surveillance discourse and illustrate the current...

  5. Assessing business-IT alignment in networked organizations

    NARCIS (Netherlands)

    Santana Tapia, R.G.

    2009-01-01

    Concerns such as identifying ways to control costs, improve quality, increase effectiveness, and manage risk have become increasingly important for organizations as they face more and more pressure to gain and maintain their competitive edge. Business-IT alignment (B-ITa) is recognized as a solution

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

    Directory of Open Access Journals (Sweden)

    Gabriel Koch Ocker

    2015-08-01

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

  7. Molecular evolution constraints in the floral organ specification gene regulatory network module across 18 angiosperm genomes.

    Science.gov (United States)

    Davila-Velderrain, Jose; Servin-Marquez, Andres; Alvarez-Buylla, Elena R

    2014-03-01

    The gene regulatory network of floral organ cell fate specification of Arabidopsis thaliana is a robust developmental regulatory module. Although such finding was proposed to explain the overall conservation of floral organ types and organization among angiosperms, it has not been confirmed that the network components are conserved at the molecular level among flowering plants. Using the genomic data that have accumulated, we address the conservation of the genes involved in this network and the forces that have shaped its evolution during the divergence of angiosperms. We recovered the network gene homologs for 18 species of flowering plants spanning nine families. We found that all the genes are highly conserved with no evidence of positive selection. We studied the sequence conservation features of the genes in the context of their known biological function and the strength of the purifying selection acting upon them in relation to their placement within the network. Our results suggest an association between protein length and sequence conservation, evolutionary rates, and functional category. On the other hand, we found no significant correlation between the strength of purifying selection and gene placement. Our results confirm that the studied robust developmental regulatory module has been subjected to strong functional constraints. However, unlike previous studies, our results do not support the notion that network topology plays a major role in constraining evolutionary rates. We speculate that the dynamical functional role of genes within the network and not just its connectivity could play an important role in constraining evolution.

  8. Power Flow Calculation for Traction Networks under Regenerative Braking Condition Based on Locomotive-Traction Network Coupling

    OpenAIRE

    Han Xudong; Gao Shibin; Hu Haitao; Wang Bin

    2013-01-01

    The regenerative braking technology is widely applied in high-speed electric multiple units (EMUs). And the voltage rise problem at end of the traction network would be caused by regenerative braking attracts more and more attention. The arm of this paper is to analyze the power flow calculation for EMUs under regenerative braking condition. Power flow calculation was done for two different EMU operation conditions by using a “locomotive-traction network” coupling model. In this model, a cons...

  9. Identification of Inter-Organ Vascular Network: Vessels Bridging between Organs

    OpenAIRE

    Omae, Madoka; Takada, Norio; Yamamoto, Shohei; Nakajima, Hiroyuki; Sato, Thomas N.

    2013-01-01

    Development and homeostasis of organs and whole body is critically dependent on the circulatory system. In particular, the circulatory system, the railways shuttling oxygen and nutrients among various organs, is indispensible for inter-organ humoral communication. Since the modern view of the anatomy and mechanics of the circulatory system was established in 17(th) century, it has been assumed that humoral factors are carried to and from organs via vascular branches of the central arteries an...

  10. 29 CFR 451.4 - Labor organizations under section 3(j).

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 2 2010-07-01 2010-07-01 false Labor organizations under section 3(j). 451.4 Section 451.4... 1959 § 451.4 Labor organizations under section 3(j). (a) General. Section 3(j) sets forth five... one of these categories listed in section 3(j) is subject to the requirements of the Act. (b...

  11. Comparison of selection efficiency for spring barley (Hordeum vulgare L.) under organic and conventional farming conditions

    NARCIS (Netherlands)

    Kokare, Aina; Legzdina, Linda; Maliepaard, Chris; Niks, Rients E.; Lammerts van Bueren, Edith T.

    2017-01-01

    The main objective of this research was to analyze whether selection under conventional conditions (indirect selection) is as effective as selection under organic conditions (direct selection) to develop varieties suitable for organic farming systems. Two F3 barley (Hordeum vulgare L.) populations

  12. Beyond the network of plants volatile organic compounds

    OpenAIRE

    Vivaldo, Gianna; Masi, Elisa; Taiti, Cosimo; Caldarelli, Guido; Mancuso, Stefano

    2017-01-01

    Plants emission of volatile organic compounds (VOCs) is involved in a wide class of ecological functions, as VOCs play a crucial role in plants interactions with biotic and abiotic factors. Accordingly, they vary widely across species and underpin differences in ecological strategy. In this paper, VOCs spontaneously emitted by 109 plant species (belonging to 56 different families) have been qualitatively and quantitatively analysed in order to classify plants species. By using bipartite netwo...

  13. Disrupting Terrorist Networks: An Analysis of the PKK Terrorist Organization

    Science.gov (United States)

    2010-12-01

    Turkey (and the State’s Counter Measures), 361. 68 the refugees are able to find a job and provide their own financial support.271 Ultimately, the...concur, this embeddedness did not turn the PKK into a criminal group. In this part of the chapter, the study focused on the assisting factors that...PKK too. The next chapter will further analyze the role of geographical safe havens along with the embeddedness of the PKK terrorist organization in

  14. Nonprofit Organizations in Disaster Response and Management: A Network Analysis

    OpenAIRE

    NAIM KAPUCU; FARHOD YULDASHEV; MARY ANN FELDHEIM

    2018-01-01

    This paper tracks changes in the national disaster management system with regard to the nonprofit sector by looking at the roles ascribed to nonprofit organizations in the Federal Response Plan (FRP), National Response Plan (NRP), and National Response Framework (NRF). Additionally, the data collected from news reports and organizational after action reports about the inter-organizational interactions of emergency management agencies during the September 11 th attacks ...

  15. Performance Evaluation of Survivability Strategies for Elastic Optical Networks under Physical Layer Impairments

    Directory of Open Access Journals (Sweden)

    Jurandir Lacerda Jr

    2017-08-01

    Full Text Available This paper carried out a performance evaluation study that compares two survivability strategies (DPP and SM-RSA for elastic optical networks with and without physical layer impairments. The evaluated scenarios include three representative topologies for elastic optical network, NSFNET, EON and USA. It also analyzes the increase of blocking probability when the survivability strategies are evaluated under the realistic scenario that assumes physical layer impairments. For all studied topologies under physical layer impairments, the survivability strategies achieved blocking probability above 80%.

  16. The effect of organic diets on the performance of pullets maintained under semi-organic conditions.

    Science.gov (United States)

    Acamovic, T; Sandilands, V; Kyriazakis, I; Sparks, N

    2008-01-01

    The effects of organic diets, with or without supplements of betaine, saponin, fructo-oligosaccharide and methionine, on the health, performance and gut flora of pullets were investigated. A comparison was also made between birds fed organic diets and those fed a non-organic diet. Day-old Lohmann Tradition pullets were reared in 24 groups of 64 chicks indoors until 11 weeks, and then in 48 groups of 24 to 27 chicks with access to range until 17 weeks of age. Groups of birds were fed one of eight diets, a conventional rearing diet with supplementary amino acids, an organic basal diet, organic basal plus methionine and organic basal supplemented with one of the test ingredients. At most stages of growth the birds fed the conventional diet and those fed the basal diet with methionine performed better than those that had no supplemental methionine. Other dietary treatments had no consistently significant effect on growth, the microbial populations within the gastro-intestinal tract of the birds or the number of parasite eggs excreted. After 5 weeks with access to range, the birds that were fed three out of five diets regarded as deficient in sulphur amino acids achieved similar weights (P > 0.05) to birds that received diets adequate in sulphur amino acids. Health and welfare of birds fed organic diets was not adversely affected; however, an investigation of birds housed in larger flocks and taken into the laying phase, when physical demands on birds are greatest, is required.

  17. [The network organization of medical research in the US Armed Forces].

    Science.gov (United States)

    Golota, A S; Zubenko, A I; Ivchenko, E V; Krassiĭ, A B; Shalakhin, R A

    2014-03-01

    The current article is dedicated to the network mode of medical scientific research organization in the US Armed Forces exploring the Armed Forces Institute of Regenerative Medicine as an example. The following features of the institute are examined: the structure, definition of scientific research goals and tasks, financing, management, areas of research, the next generation of the institute. In conclusion some characteristic features of network scientific research establishment and required legal conditions are determined.

  18. Self-organized and driven phase synchronization in coupled map scale free networks

    OpenAIRE

    Jalan, Sarika; Amritkar, R. E.

    2002-01-01

    As a model of evolving networks, we study coupled logistic maps on scale free networks. For small coupling strengths nodes show turbulent behavior but form phase synchronized clusters as coupling increases. We identify two different ways of cluster formation. For small coupling strengths we get {\\it self-organized clusters} which have mostly intra-cluster couplings and for large coupling strengths there is a crossover and reorganization to {\\it driven clusters} which have mostly inter-cluster...

  19. Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

    OpenAIRE

    WenJun Zhang; QuHuan Li

    2014-01-01

    In present study we used self-organizing map (SOM) neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of ...

  20. Micro-connectomics: probing the organization of neuronal networks at the cellular scale.

    Science.gov (United States)

    Schröter, Manuel; Paulsen, Ole; Bullmore, Edward T

    2017-03-01

    Defining the organizational principles of neuronal networks at the cellular scale, or micro-connectomics, is a key challenge of modern neuroscience. In this Review, we focus on graph theoretical parameters of micro-connectome topology, often informed by economical principles that conceptually originated with Ramón y Cajal's conservation laws. First, we summarize results from studies in intact small organisms and in samples from larger nervous systems. We then evaluate the evidence for an economical trade-off between biological cost and functional value in the organization of neuronal networks. Various results suggest that many aspects of neuronal network organization are indeed the outcome of competition between these two fundamental selection pressures.

  1. Study of wet incineration of organic matters under ultrasounds

    International Nuclear Information System (INIS)

    Rey-Gaurez, F.

    2001-01-01

    The purpose of this study is to investigate the potentiality of power ultrasound for minimizing the volumes of solid waste and effluents generated by the spent nuclear fuel refining industry. In the first part, the advantages of power ultrasound for the decontamination of ion exchange resins (IER) is demonstrated: 1) sonication allows to remove 100 % of the 137 Cs and more than 20 % of the 60 Co initially present in the contaminated resins, 2) the decontamination is fast, 3) very simple experimental conditions are necessary (water, air or argon as saturating gas and weak electric intensity). The study of different chemical and sono-chemical parameters shows that decontamination seems to be related to the effects induced by cavitation: micro-streaming and solid erosion or disruption. In the second part, the selectivity of power ultrasound for the elimination of nitrogen (nitrate, nitro) aliphatic derivatives diluted in the PUREX process solvent is established. The nitrogen derivatives of butane or dodecane are removed under sonication while the solvent is scarcely damaged. The nitrogen derivatives of butane are quickly eliminated according to a thermal way in the cavitation bubble. A great number of kinetic data have been obtained and the influence of different parameters has been studied. The mechanisms are complex and initiated mainly by the homolytic cleavage of the O-N bond of butyl nitrate or nitrite and the C-N bond of nitrobutane. The elimination of nitrogen derivatives of dodecane is slower than the four-carbon component one. This preliminary kinetic study was difficult as the kinetic order was undetermined and a steady state concentration was reached after a short time of sonication. Unlike the four-carbon derivatives, the decomposition rate was not controlled by the boiling point of the long-chain derivatives. Nevertheless, good carbon balance (dodecane is the major product) has been obtained and led to potential mechanisms. (author) [fr

  2. Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

    Science.gov (United States)

    Harrington, Peter DEB.; Zheng, Peng

    1995-01-01

    Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

  3. Prediction based Greedy Perimeter Stateless Routing Protocol for Vehicular Self-organizing Network

    Science.gov (United States)

    Wang, Chunlin; Fan, Quanrun; Chen, Xiaolin; Xu, Wanjin

    2018-03-01

    PGPSR (Prediction based Greedy Perimeter Stateless Routing) is based on and extended the GPSR protocol to adapt to the high speed mobility of the vehicle auto organization network (VANET) and the changes in the network topology. GPSR is used in the VANET network environment, the network loss rate and throughput are not ideal, even cannot work. Aiming at the problems of the GPSR, the proposed PGPSR routing protocol, it redefines the hello and query packet structure, in the structure of the new node speed and direction information, which received the next update before you can take advantage of its speed and direction to predict the position of node and new network topology, select the right the next hop routing and path. Secondly, the update of the outdated node information of the neighbor’s table is deleted in time. The simulation experiment shows the performance of PGPSR is better than that of GPSR.

  4. Homeopathic and high dilution preparations for pest management to tomato crop under organic production system

    OpenAIRE

    Modolon,Tatiani A; Boff,Pedro; Boff,Mari Inês C; Miquelluti,David José

    2012-01-01

    Tomato crops (Solanum lycopersicum) under conventional production system are constantly treated against pest and diseases, with organic synthetic pesticides that are used may cause serious disturbance to environment and human health. This research was carried out in order to study the effect of homeopathic and high dilution preparations on pests and diseases management of tomato crop under organic production system. Two experiments were conducted under field conditions and one in greenhouse. ...

  5. Carbon in Humic Fractions of Organic Matter in Soil Treated with Organic Composts under Mango Cultivation

    Directory of Open Access Journals (Sweden)

    Joyce Reis Silva

    2016-01-01

    Full Text Available ABSTRACT Soil organic matter (SOM plays a key role in maintaining the productivity of tropical soils, providing energy and substrate for the biological activity and modifying the physical and chemical characteristics that ensure the maintenance of soil quality and the sustainability of ecosystems. This study assessed the medium-term effect (six years of the application of five organic composts, produced by combining different agro-industrial residues, on accumulation and chemical characteristics of soil organic matter. Treatments were applied in a long-term experiment of organic management of mango (OMM initiated in 2005 with a randomized block design with four replications. Two external areas, one with conventional mango cultivation (CMM and the other a fragment of regenerating Caatinga vegetation (RCF, were used as reference areas. Soil samples were collected in the three management systems from the 0.00-0.05, 0.05-0.10, and 0.10-0.20 m layers, and the total organic carbon content and chemical fractions of organic matter were evaluated by determining the C contents of humin and humic and fulvic acids. Organic compost application significantly increased the contents of total C and C in humic substances in the experimental plots, mainly in the surface layer. However, compost 3 (50 % coconut bagasse, 40 % goat manure, 10 % castor bean residues significantly increased the level of the non-humic fraction, probably due to the higher contents of recalcitrant material in the initial composition. The highest increases from application of the composts were in the humin, followed by the fulvic fraction. Compost application increased the proportion of higher molecular weight components, indicating higher stability of the organic matter.

  6. Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2014-06-01

    Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

  7. Energy-efficient Organization of Wireless Sensor Networks with Adaptive Forecasting

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2008-04-01

    Full Text Available Due to the wide potential applications of wireless sensor networks, this topic has attracted great attention. The strict energy constraints of sensor nodes result in great challenges for energy efficiency. This paper proposes an energy-efficient organization method. The organization of wireless sensor networks is formulated for target tracking. Target localization is achieved by collaborative sensing with multi-sensor fusion. The historical localization results are utilized for adaptive target trajectory forecasting. Combining autoregressive moving average (ARMA model and radial basis function networks (RBFNs, robust target position forecasting is performed. Moreover, an energyefficient organization method is presented to enhance the energy efficiency of wireless sensor networks. The sensor nodes implement sensing tasks are awakened in a distributed manner. When the sensor nodes transfer their observations to achieve data fusion, the routing scheme is obtained by ant colony optimization. Thus, both the operation and communication energy consumption can be minimized. Experimental results verify that the combination of ARMA model and RBFN can estimate the target position efficiently and energy saving is achieved by the proposed organization method in wireless sensor networks.

  8. Wettability, soil organic matter and structure-properties of typical chernozems under the forest and under the arable land

    Science.gov (United States)

    Bykova, Galina; Umarova, Aminat; Tyugai, Zemfira; Milanovskiy, Evgeny; Shein, Evgeny

    2017-04-01

    Intensive tillage affects the properties of soil: decrease in content of soil organic matter and in hydrophobicity of the soil's solid phase, the reduction of amount of water stable aggregates - all this leads to deterioration of the structure of the soil and affects the process of movement of moisture in the soil profile. One of the hypotheses of soil's structure formation ascribes the formation of water stable aggregates with the presence of hydrophobic organic substances on the surface of the soil's solid phase. The aim of this work is to study the effect of tillage on properties of typical chernozems (pachic Voronic Chernozems, Haplic Chernozems) (Russia, Kursk region), located under the forest and under the arable land. The determination of soil-water contact angle was performed by a Drop Shape Analyzer DSA100 (Krüss GmbH, Germany) by the static sessile drop method. For all samples the content of total and organic carbon by dry combustion in oxygen flow and the particle size distribution by the laser diffraction method on the device Analysette 22 comfort, FRITCH, Germany were determined. The estimation of aggregate composition was performed by dry sieving (AS 200, Retsch, Germany), the content of water stable aggregates was estimated by the Savvinov method. There was a positive correlation between the content of organic matter and soil's wettability in studied soils, a growth of contact angle with the increasing the content of organic matter. Under the forest the content of soil organic matter was changed from 6,41% on the surface up to 1,9% at the depth of 100 cm. In the Chernozem under the arable land the organic carbon content in arable horizon is almost two times less. The maximum of hydrophobicity (78.1o) was observed at the depth of 5 cm under the forest. In the profile under the arable land the contact angle value at the same depth was 50o. The results of the structure analysis has shown a decrease in the content of agronomically valuable and water

  9. Global stability analysis and robust design of multi-time-scale biological networks under parametric uncertainties.

    Science.gov (United States)

    Meyer-Baese, Anke; Koshkouei, Ali J; Emmett, Mark R; Goodall, David P

    2009-01-01

    Biological networks are prone to internal parametric fluctuations and external noises. Robustness represents a crucial property of these networks, which militates the effects of internal fluctuations and external noises. In this paper biological networks are formulated as coupled nonlinear differential systems operating at different time-scales under vanishing perturbations. In contrast to previous work viewing biological parametric uncertain systems as perturbations to a known nominal linear system, the perturbed biological system is modeled as nonlinear perturbations to a known nonlinear idealized system and is represented by two time-scales (subsystems). In addition, conditions for the existence of a global uniform attractor of the perturbed biological system are presented. By using an appropriate Lyapunov function for the coupled system, a maximal upper bound for the fast time-scale associated with the fast state is derived. The proposed robust system design principles are potentially applicable to robust biosynthetic network design. Finally, two examples of two important biological networks, a neural network and a gene regulatory network, are presented to illustrate the applicability of the developed theoretical framework.

  10. Coverage probability of cellular networks using interference alignment under imperfect CSI

    Directory of Open Access Journals (Sweden)

    Raoul F. Guiazon

    2016-11-01

    Full Text Available Interference alignment (IA is well understood to approach the capacity of interference channels, and believed to be crucial in cellular networks in which the ability to control and exploit interference is key. However, the achievable performance of IA in cellular networks depends on the quality of channel state information (CSI and how effective IA is in practical settings is not known. This paper studies the use of IA to mitigate inter-cell interference of cellular networks under imperfect CSI conditions. Our analysis is based on stochastic geometry where the structure of the base station (BS locations is considered by a Poisson point process (PPP. Our main contribution is the coverage probability of the network and simulation results confirm the accuracy.

  11. Securing ad hoc wireless sensor networks under Byzantine attacks by implementing non-cryptographic method

    Directory of Open Access Journals (Sweden)

    Shabir Ahmad Sofi

    2017-05-01

    Full Text Available Ad Hoc wireless sensor network (WSN is a collection of nodes that do not need to rely on predefined infrastructure to keep the network connected. The level of security and performance are always somehow related to each other, therefore due to limited resources in WSN, cryptographic methods for securing the network against attacks is not feasible. Byzantine attacks disrupt the communication between nodes in the network without regard to its own resource consumption. This paper discusses the performance of cluster based WSN comparing LEACH with Advanced node based clusters under byzantine attacks. This paper also proposes an algorithm for detection and isolation of the compromised nodes to mitigate the attacks by non-cryptographic means. The throughput increases after using the algorithm for isolation of the malicious nodes, 33% in case of Gray Hole attack and 62% in case of Black Hole attack.

  12. Dynamic Network Design Problem under Demand Uncertainty: An Adjustable Robust Optimization Approach

    Directory of Open Access Journals (Sweden)

    Hua Sun

    2014-01-01

    Full Text Available This paper develops an adjustable robust optimization approach for a network design problem explicitly incorporating traffic dynamics and demand uncertainty. In particular, a cell transmission model based network design problem of linear programming type is considered to describe dynamic traffic flows, and a polyhedral uncertainty set is used to characterize the demand uncertainty. The major contribution of this paper is to formulate such an adjustable robust network design problem as a tractable linear programming model and justify the model which is less conservative by comparing its solution performance with the robust solution from the usual robust model. The numerical results using one network from the literature demonstrate the modeling advantage of the adjustable robust optimization and provided strategic managerial insights for enacting capacity expansion policies under demand uncertainty.

  13. Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

    Science.gov (United States)

    Bi, Zedong; Zhou, Changsong

    2016-01-01

    Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

  14. Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

    Directory of Open Access Journals (Sweden)

    Zedong Bi

    2016-08-01

    Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.

  15. Enhancing network performance under single link failure with AS-disjoint BGP extension

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Romeral, S.; Ruepp, Sarah Renée

    2009-01-01

    In this paper we propose an enhancement of the BGP protocol for obtaining AS-disjoint paths in GMPLS multi-domain networks. We evaluate the benefits of having AS-disjoint paths under single inter-domain link failure for two main applications: routing of future connection requests during routing...... protocol re-convergence and applying multi-domain restoration as survivability mechanism in case of a single link failure. The proposed BGP modification is a simple and effective solution for disjoint path selection in connection-oriented multi-domain networks. Our results show that applying the proper...... failure notification method combined with our proposal reduces the blocking of new connection requests under protocol re-convergence. Furthermore. we show that our proposal is a valuable complementary process for increasing the network resilience....

  16. Problems of organization and development of the Latvian energy efficiency network

    International Nuclear Information System (INIS)

    Petrov, B.; Puikevica-Puikevska, I.

    1999-01-01

    The idea to create an Energy Efficiency Network (Network) was put forward in Canada. In 1989 similar activities started in Norway. Taking account the difficult economical situation in the Latvia industry, such a Network would help to develop our enterprises under conditions of competition. In the future, this Network is to ensure a stabile operation of the international level. Therefore Network's purposes are: to promote decision-making process with due account for the energy efficiency measures and environment-friendly energy use in industry; to encourage reducing the specific consumption of energy; to promote the information exchange among industrial enterprises as well as with new technology suppliers, and service and consulting enterprises. The task of Network is to process information on the activities of enterprises, to perform computations and to show the condition of every enterprise in the same branch of industry, by means of diagrams and tables, as well as to reveal weak points of the enterprise. The benefits of the Network participants: Network information data base allows the participants to compare their energy efficiency data with those of other enterprises in the same branch of industry; opportunity to receive information on the newest achievements in the energy efficiency measures; opportunity to familiarise themselves with the necessary project documentation, reports, ets. Network's activities are organised due consideration for particular needs of an enterprise reported directly by the participants of the enterprise. (author)

  17. Modelling the Cost Performance of a Given Logistics Network Operating Under Regular and Irregular Conditions

    NARCIS (Netherlands)

    Janic, M.

    2009-01-01

    This paper develops an analytical model for the assessment of the cost performance of a given logistics network operating under regular and irregular (disruptive) conditions. In addition, the paper aims to carry out a sensitivity analysis of this cost with respect to changes of the most influencing

  18. Robustness of the Drinking Water Distribution Network under Changing Future Demand

    NARCIS (Netherlands)

    Agudelo-Vera, C.; Blokker, M.; Vreeburg, J.; Bongard, T.; Hillegers, S.; Van der Hoek, J.P.

    2014-01-01

    A methodology to determine the robustness of the drinking water distribution system is proposed. The performance of three networks under ten future demand scenarios was tested, using head loss and residence time as indicators. The scenarios consider technological and demographic changes. Daily

  19. Creating and Using a Computer Networking and Systems Administration Laboratory Built under Relaxed Financial Constraints

    Science.gov (United States)

    Conlon, Michael P.; Mullins, Paul

    2011-01-01

    The Computer Science Department at Slippery Rock University created a laboratory for its Computer Networks and System Administration and Security courses under relaxed financial constraints. This paper describes the department's experience designing and using this laboratory, including lessons learned and descriptions of some student projects…

  20. Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

    NARCIS (Netherlands)

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

  1. Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

    OpenAIRE

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed models perform well in realistic settings

  2. Actin Microfilament Organization in the Transition Zone of Arabidopsis-ABD2-GFP Roots Under Clinorotation

    Science.gov (United States)

    Shevchenko, Galina

    2012-12-01

    Seedlings of Arabidopsis thaliana-ABD2-GFP were grown under slow clinorotation (2 rpm) and treated with actin and tubulin disrupting drugs in order to characterize the role of actin microfilaments in cell growth and gravisensing. Changes in microfilament organization and cell parameters have shown that the transition root zone (TZ) is rather sensitive to microfilament disruption in control plants. It is assumed that under clinorotation, organization of actin cytoskeleton in the TZ is coordinated in a different way than in the control. Organization of microfilaments depends upon organization of microtubules and clinorotation does not influence this interrelation significantly.

  3. Effects of Plectin Depletion on Keratin Network Dynamics and Organization.

    Directory of Open Access Journals (Sweden)

    Marcin Moch

    Full Text Available The keratin intermediate filament cytoskeleton protects epithelial cells against various types of stress and is involved in fundamental cellular processes such as signaling, differentiation and organelle trafficking. These functions rely on the cell type-specific arrangement and plasticity of the keratin system. It has been suggested that these properties are regulated by a complex cycle of assembly and disassembly. The exact mechanisms responsible for the underlying molecular processes, however, have not been clarified. Accumulating evidence implicates the cytolinker plectin in various aspects of the keratin cycle, i.e., by acting as a stabilizing anchor at hemidesmosomal adhesion sites and the nucleus, by affecting keratin bundling and branching and by linkage of keratins to actin filament and microtubule dynamics. In the present study we tested these hypotheses. To this end, plectin was downregulated by shRNA in vulvar carcinoma-derived A431 cells. As expected, integrin β4- and BPAG-1-positive hemidesmosomal structures were strongly reduced and cytosolic actin stress fibers were increased. In addition, integrins α3 and β1 were reduced. The experiments furthermore showed that loss of plectin led to a reduction in keratin filament branch length but did not alter overall mechanical properties as assessed by indentation analyses using atomic force microscopy and by displacement analyses of cytoplasmic superparamagnetic beads using magnetic tweezers. An increase in keratin movement was observed in plectin-depleted cells as was the case in control cells lacking hemidesmosome-like structures. Yet, keratin turnover was not significantly affected. We conclude that plectin alone is not needed for keratin assembly and disassembly and that other mechanisms exist to guarantee proper keratin cycling under steady state conditions in cultured single cells.

  4. Synthesis and Structural Characterization of Carboxylate-Based Metal-Organic Frameworks and Coordination Networks

    Science.gov (United States)

    Calderone, Paul

    Coordination networks (CNs) and metal-organic frameworks (MOFs) are crystalline materials composed of metal ions linked by multifunctional organic ligands. From these connections, infinite arrays of one-, two-, or three-dimensional networks can be formed. Exploratory synthesis and research of novel CNs and MOFs is of current interest because of their many possible industrial applications including gas storage, catalysis, magnetism, and luminescence. A variety of metal centers and organic ligands can be used to synthesize MOFs and CNs under a range of reaction conditions, leading to extraordinary structural diversity. The characteristics of the metals and linkers, such as properties and coordination preferences, play the biggest role in determining the structure and properties of the resulting network. Thus, the choice of metal and linker is dictated by the desired traits of the target network. The pervasive use of transition metal centers in MOF synthesis stems from their well-known coordination behavior with carboxylate-based linkers, thus facilitating design strategies. Conversely, CNs and MOFs based on s-block and lanthanide metals are less studied because each group presents unique challenges to structure prediction. Lanthanide metals have variable coordination spheres capable of accommodating up to twelve atoms, while the bonding in s-block metals takes on a mainly ionic character. In spite of these obstacles, lanthanide and s-block CNs are worthwhile synthetic targets because of their unique properties. Interesting photoluminescent and sensing materials can be developed using lanthanide metals, whereas low atomic weight s-block metals may afford an advantage in gravimetric advantages for gas storage applications. The aim of this research was to expand the current understanding of carboxylate-based CN and MOF synthesis by varying the metals, solvents, and temperatures used. To this end, magnesium-based CNs were examined using a variety of aromatic carboxylate

  5. Internal structure analysis of particle-double network gels used in a gel organ replica

    Science.gov (United States)

    Abe, Mei; Arai, Masanori; Saito, Azusa; Sakai, Kazuyuki; Kawakami, Masaru; Furukawa, Hidemitsu

    2016-04-01

    In recent years, the fabrication of patient organ replicas using 3D printers has been attracting a great deal of attention in medical fields. However, the cost of these organ replicas is very high as it is necessary to employ very expensive 3D printers and printing materials. Here we present a new gel organ replica, of human kidney, fabricated with a conventional molding technique, using a particle-double network hydrogel (P-DN gel). The replica is transparent and has the feel of a real kidney. It is expected that gel organ replicas produced this way will be a useful tool for the education of trainee surgeons and clinical ultrasonography technologists. In addition to developing a gel organ replica, the internal structure of the P-DN gel used is also discussed. Because the P-DN gel has a complex structure comprised of two different types of network, it has not been possible to investigate them internally in detail. Gels have an inhomogeneous network structure. If it is able to get a more uniform structure, it is considered that this would lead to higher strength in the gel. In the present study we investigate the structure of P-DN gel, using the gel organ replica. We investigated the internal structure of P-DN gel using Scanning Microscopic Light Scattering (SMILS), a non-contacting and non-destructive.

  6. Thermo-economic optimization of secondary distribution network of low temperature district heating network under local conditions of South Korea

    DEFF Research Database (Denmark)

    Park, Byung Sik; Imran, Muhammad; Hoon, Im-Yong

    2017-01-01

    A secondary distribution network of a low temperature district heating system is designed and optimized for a residential apartment complex under the local conditions of South Korea in the TRNSYS simulation environment. The residential apartment complex is a typical example of Korean residential...... °C, area of heat exchanger is increased by 68.2%, pumping power is also increased by 9.8% and heat loss is reduced by 15.6%. These results correspond to a temperature difference of 20 °C, the standard temperature difference in South Korea residential heating system. Economic assessment...

  7. Positron Emission Tomography Reveals Abnormal Topological Organization in Functional Brain Network in Diabetic Patients

    Directory of Open Access Journals (Sweden)

    Qiu eXiangzhe

    2016-05-01

    Full Text Available Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM. However, the DM-related changes in the topological properties in functional brain networks are almost unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs, followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized shortest path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing the functional evidence for the abnormalities of brain networks in DM.

  8. Suppression of anomalous synchronization and nonstationary behavior of neural network under small-world topology

    Science.gov (United States)

    Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.

    2018-05-01

    It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.

  9. Adaptive Sensing with Reliable Guarantee under White Gaussian Noise Channels of Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jun Long

    2015-01-01

    Full Text Available Quality of sensing is a fundamental research topic in sensor networks. In this paper, we propose an adaptive sensing technique to guarantee the end-to-end reliability while maximizing the lifetime of sensor networks under additive white Gaussian noise channels. First, we conduct theoretical analysis to obtain optimal node number N∗, node placement d∗, and node transmission structure P∗ under minimum total energy consumption and minimum unit data transmission energy consumption. Then, because sensor nodes closer to the sink consume more energy, nodes far from the sink have more residual energy. Based on this observation, we propose an adaptive sensing technique to achieve balanced network energy consumption. It adopts lower reliability requirement and shorter transmission distance for nodes near the sink and adopts higher reliability requirement and farther transmission distance for nodes far from the sink. Theoretical analysis and experimental results show that our design can improve the network lifetime by several times (1–5 times and network utility by 20% and the desired reliability level is also guaranteed.

  10. COST-EFFECTIVE BANDWIDTH PROVISIONING IN MICROWAVE WIRELESS NETWORKS UNDER UNRELIABLE CHANNEL CONDITIONS

    Directory of Open Access Journals (Sweden)

    Brigitte Jaumard

    Full Text Available ABSTRACT Cost-effective planning and dimensioning of backhaul microwave networks under unreliable channel conditions remains a relatively underexplored area in the literature. In particular, bandwidth assignment requires special attention as the transport capacity of microwave links is prone to variations due to, e.g., weather conditions. In this paper, we formulate an optimization model that determines the minimum cost bandwidth assignment of the links in the network for which traffic requirements can be fulfilled with high probability. This model also aims to increase network reliability by adjusting dynamically traffic routes in response to variations of link capacities induced by channel conditions. Experimental results show that 45% of the bandwidth cost can be saved compared to the case where a bandwidth over-provisioning policy is uniformly applied to all links in the network planning. Comparisons with previous work also show that our solution approach, based on column generation technique, is able to solve much larger instances in significantly shorter computing times (i.e., few minutes for medium-size networks, and up to 2 hours for very large networks, unsolved so far by previous models/algorithms, with a comparable level of reliability.

  11. A model of social network formation under the impact of structural balance

    Science.gov (United States)

    Li, Pei; Cheng, Jiajun; Chen, Yingwen; Wang, Hui

    2016-03-01

    Social networks have attracted remarkable attention from both academic and industrial societies and it is of great importance to understand the formation of social networks. However, most existing research cannot be applied directly to investigate social networks, where relationships are heterogeneous and structural balance is a common phenomenon. In this paper, we take both positive and negative relationships into consideration and propose a model to characterize the process of social network formation under the impact of structural balance. In this model, a new node first establishes a link with an existing node and then tries to connect to each of the newly connected node’s neighbors. If a new link is established, the type of this link is determined by structural balance. Then we analyze the degree distribution of the generated network theoretically, and estimate the fractions of positive and negative links. All analysis results are verified by simulations. These results are of importance to understand the formation of social networks, and the model can be easily extended to consider more realistic situations.

  12. Formal Models of the Network Co-occurrence Underlying Mental Operations.

    Directory of Open Access Journals (Sweden)

    Danilo Bzdok

    2016-06-01

    Full Text Available Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81 by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition.

  13. Awareness of evidence-based practices by organizations in a publicly funded smoking cessation network

    NARCIS (Netherlands)

    Provan, K.; Beagles, J.; Mercken, L.; Leischow, S.J.

    2013-01-01

    This research examines the awareness of evidence-based practices by the public organizations that fund services in the North American Quitline Consortium (NAQC). NAQC is a large, publicly funded, goal-directed “whole network,” spanning both Canada and the United States, working to get people to quit

  14. Monitoring Scientific Developments from a Dynamic Perspective: Self-Organized Structuring To Map Neural Network Research.

    Science.gov (United States)

    Noyons, E. C. M.; van Raan, A. F. J.

    1998-01-01

    Using bibliometric mapping techniques, authors developed a methodology of self-organized structuring of scientific fields which was applied to neural network research. Explores the evolution of a data generated field structure by monitoring the interrelationships between subfields, the internal structure of subfields, and the dynamic features of…

  15. Effects of the ISIS Recommender System for Navigation Support in Self-Organized Learning Networks

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Van den Berg, Bert; Eshuis, Jannes; Waterink, Wim; Nadolski, Rob; Berlanga, Adriana; Boers, Nanda; Koper, Rob

    2008-01-01

    Drachsler, H., Hummel, H. G. K., Van den Berg, B., Eshuis, J., Waterink, W., Nadolski, R., Berlanga, A., Boers, N., & Koper, R. (2008). Effects of the ISIS Recommender System for Navigation Support in Self-Organized Learning Networks. In M. Kalz, R. Koper, V. Hornung-Prähauser & M. Luckmann (Eds.).

  16. Multi-wall carbon nanotube networks as potential resistive gas sensors for organic vapor detection

    Czech Academy of Sciences Publication Activity Database

    Slobodian, P.; Říha, Pavel; Lengálová, A.; Svoboda, P.; Sáha, P.

    2011-01-01

    Roč. 49, č. 7 (2011), s. 2499-2507 ISSN 0008-6223 Institutional research plan: CEZ:AV0Z20600510 Keywords : carbon nanotube network * KMnO 4 oxidation * electrical resistance * organic vapor detection * adsorption/desorption cycles Subject RIV: JB - Sensors, Measurment, Regulation Impact factor: 5.378, year: 2011

  17. Challenges to the Learning Organization in the Context of Generational Diversity and Social Networks

    Science.gov (United States)

    Kaminska, Renata; Borzillo, Stefano

    2018-01-01

    Purpose: The purpose of this paper is to gain a better understanding of the challenges to the emergence of a learning organization (LO) posed by a context of generational diversity and an enterprise social networking system (ESNS). Design/methodology/approach: This study uses a qualitative methodology based on an analysis of 20 semi-structured…

  18. Regional and international integrated telemedicine network for organ transplant (HC 4028 & IN 4028 European Commission DGXIII).

    Science.gov (United States)

    Vari, S. G.; Brugal, G.; Godo, F.; Bercic, B.; Nagy, G.; Avar, G.; Adelh, D.; Lagouarde, P.

    2000-01-01

    A substantial portion of future medical practice will depend greatly on improved collaboration between the providers throughout the healthcare sector, and effective sharing of data and expertise by different healthcare professionals. In organ transplant it is a rule, donor organs are matched to recipients via national or multinational organ-sharing organizations. Only through close co-operation between transplant surgeons, immunologists, nephrologists, pathologists, radiologists and other physicians could one increase the efficiency of organ transplantation. Information technology (IT) has become an inevitable and inherent part of transplantation medicine. The RETRANSPLANT project interfaces and integrates IT from the European Union Fourth Framework projects to support the development of regional organ transplant information networks in Central Europe. PMID:11080009

  19. Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions

    Science.gov (United States)

    Cheminformatics-based software tools can predict the molecular structure of transformation products using a library of transformation reaction schemes. This paper presents the development of such a library for abiotic hydrolysis of organic chemicals under environmentally relevant...

  20. Ten years of the Immune Tolerance Network: an integrated clinical research organization.

    Science.gov (United States)

    Bluestone, Jeffrey A; Krensky, Alan M; Turka, Laurence A; Rotrosen, Daniel; Matthews, Jeffrey B

    2010-02-17

    The U.S. National Institutes of Health Roadmap and the U.S. Food and Drug Administration's Critical Path Initiative have endorsed the establishment of large academic clinical research networks as part of the solution to the growing divide between increased R&D spending and the lagging number of new drugs making it to market. Clearly, the role of these networks as translational science incubators that complement industry-sponsored programs is laudable and much-needed. However, the path to success for such organizations is less clear. Here, drawing on the experiences of the Immune Tolerance Network, a multidisciplinary clinical research network founded in 1999, we discuss some of the barriers inherent in developing such consortia and offer firsthand insight into the planning, resources, and organizational infrastructure required for a successful research program.

  1. Identification-based chaos control via backstepping design using self-organizing fuzzy neural networks

    International Nuclear Information System (INIS)

    Peng Yafu; Hsu, C.-F.

    2009-01-01

    This paper proposes an identification-based adaptive backstepping control (IABC) for the chaotic systems. The IABC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SOFNN identifier. The SOFNN identifier is used to online estimate the chaotic dynamic function with structure and parameter learning phases of fuzzy neural network. The structure learning phase consists of the growing and pruning of fuzzy rules; thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the neural structure of fuzzy neural network. The parameter learning phase adjusts the interconnection weights of neural network to achieve favorable approximation performance. Finally, simulation results verify that the proposed IABC can achieve favorable tracking performance.

  2. Cooperative integration and representation underlying bilateral network of fly motion-sensitive neurons.

    Directory of Open Access Journals (Sweden)

    Yoshinori Suzuki

    Full Text Available How is binocular motion information integrated in the bilateral network of wide-field motion-sensitive neurons, called lobula plate tangential cells (LPTCs, in the visual system of flies? It is possible to construct an accurate model of this network because a complete picture of synaptic interactions has been experimentally identified. We investigated the cooperative behavior of the network of horizontal LPTCs underlying the integration of binocular motion information and the information representation in the bilateral LPTC network through numerical simulations on the network model. First, we qualitatively reproduced rotational motion-sensitive response of the H2 cell previously reported in vivo experiments and ascertained that it could be accounted for by the cooperative behavior of the bilateral network mainly via interhemispheric electrical coupling. We demonstrated that the response properties of single H1 and Hu cells, unlike H2 cells, are not influenced by motion stimuli in the contralateral visual hemi-field, but that the correlations between these cell activities are enhanced by the rotational motion stimulus. We next examined the whole population activity by performing principal component analysis (PCA on the population activities of simulated LPTCs. We showed that the two orthogonal patterns of correlated population activities given by the first two principal components represent the rotational and translational motions, respectively, and similar to the H2 cell, rotational motion produces a stronger response in the network than does translational motion. Furthermore, we found that these population-coding properties are strongly influenced by the interhemispheric electrical coupling. Finally, to test the generality of our conclusions, we used a more simplified model and verified that the numerical results are not specific to the network model we constructed.

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

    Science.gov (United States)

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

    2015-12-01

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

  4. Network models of TEM β-lactamase mutations coevolving under antibiotic selection show modular structure and anticipate evolutionary trajectories.

    Science.gov (United States)

    Guthrie, Violeta Beleva; Allen, Jennifer; Camps, Manel; Karchin, Rachel

    2011-09-01

    Understanding how novel functions evolve (genetic adaptation) is a critical goal of evolutionary biology. Among asexual organisms, genetic adaptation involves multiple mutations that frequently interact in a non-linear fashion (epistasis). Non-linear interactions pose a formidable challenge for the computational prediction of mutation effects. Here we use the recent evolution of β-lactamase under antibiotic selection as a model for genetic adaptation. We build a network of coevolving residues (possible functional interactions), in which nodes are mutant residue positions and links represent two positions found mutated together in the same sequence. Most often these pairs occur in the setting of more complex mutants. Focusing on extended-spectrum resistant sequences, we use network-theoretical tools to identify triple mutant trajectories of likely special significance for adaptation. We extrapolate evolutionary paths (n = 3) that increase resistance and that are longer than the units used to build the network (n = 2). These paths consist of a limited number of residue positions and are enriched for known triple mutant combinations that increase cefotaxime resistance. We find that the pairs of residues used to build the network frequently decrease resistance compared to their corresponding singlets. This is a surprising result, given that their coevolution suggests a selective advantage. Thus, β-lactamase adaptation is highly epistatic. Our method can identify triplets that increase resistance despite the underlying rugged fitness landscape and has the unique ability to make predictions by placing each mutant residue position in its functional context. Our approach requires only sequence information, sufficient genetic diversity, and discrete selective pressures. Thus, it can be used to analyze recent evolutionary events, where coevolution analysis methods that use phylogeny or statistical coupling are not possible. Improving our ability to assess

  5. The Sub-Regional Functional Organization of Neocortical Irritative Epileptic Networks in Pediatric Epilepsy

    Directory of Open Access Journals (Sweden)

    Radek Janca

    2018-03-01

    Full Text Available Between seizures, irritative network generates frequent brief synchronous activity, which manifests on the EEG as interictal epileptiform discharges (IEDs. Recent insights into the mechanism of IEDs at the microscopic level have demonstrated a high variance in the recruitment of neuronal populations generating IEDs and a high variability in the trajectories through which IEDs propagate across the brain. These phenomena represent one of the major constraints for precise characterization of network organization and for the utilization of IEDs during presurgical evaluations. We have developed a new approach to dissect human neocortical irritative networks and quantify their properties. We have demonstrated that irritative network has modular nature and it is composed of multiple independent sub-regions, each with specific IED propagation trajectories and differing in the extent of IED activity generated. The global activity of the irritative network is determined by long-term and circadian fluctuations in sub-region spatiotemporal properties. Also, the most active sub-region co-localizes with the seizure onset zone in 12/14 cases. This study demonstrates that principles of recruitment variability and propagation are conserved at the macroscopic level and that they determine irritative network properties in humans. Functional stratification of the irritative network increases the diagnostic yield of intracranial investigations with the potential to improve the outcomes of surgical treatment of neocortical epilepsy.

  6. Report on investigation in fiscal 2000 of industrial technology exchange with international networking organizations; 2000 nendo kokusaitekina network gata soshiki tono sangyo gijutsu koryu chosa hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    With an objective to promote exchange of industrial technologies, investigations and analyses were made on identification of the current status of networking organizations in different countries working as windows for industrial technology exchange, and on the actual status of technology commercialization methods in overseas incubators. Activities were taken in the following three fields: 1) the current status of networking organizations and incubators in different countries, 2) typology of technology commercialization, technical fields, and success factors, and 3) possibility of the use of technology information in the networking organizations. In Item 1), investigations were performed on the current status and actual activity status of the networking organizations including research parks and individual incubators intended of information exchange, mainly in the United States, UK, and Finland. In Item 2), considerations are given on the points related to technology incubation based on the information about the networking organizations and incubators in each country, and the way the industry-academia cooperation should be. In Item 3), discussions were given on the roles of the networking organizations and the possibility of utilization of technological information in the networking organizations in Japan. (NEDO)

  7. Enhanced desorption of persistent organic pollutants from microplastics under simulated physiological conditions

    International Nuclear Information System (INIS)

    Bakir, Adil; Rowland, Steven J.; Thompson, Richard C.

    2014-01-01

    Microplastics have the potential to uptake and release persistent organic pollutants (POPs); however, subsequent transfer to marine organisms is poorly understood. Some models estimating transfer of sorbed contaminants to organisms neglect the role of gut surfactants under differing physiological conditions in the gut (varying pH and temperature), examined here. We investigated the potential for polyvinylchloride (PVC) and polyethylene (PE) to sorb and desorb 14 C-DDT, 14 C-phenanthrene (Phe), 14 C-perfluorooctanoic acid (PFOA) and 14 C-di-2-ethylhexyl phthalate (DEHP). Desorption rates of POPs were quantified in seawater and under simulated gut conditions. Influence of pH and temperature was examined in order to represent cold and warm blooded organisms. Desorption rates were faster with gut surfactant, with a further substantial increase under conditions simulating warm blooded organisms. Desorption under gut conditions could be up to 30 times greater than in seawater alone. Of the POP/plastic combinations examined Phe with PE gave the highest potential for transport to organisms. Highlights: • PVC and PE (200–250 μm) were able to sorb phenanthrene, DDT, PFOA and DEHP. • Desorption rates were faster using a gut surfactant compared to seawater alone. • Desorption rates were further enhanced at lower pH and higher temperature. • Plastic-POPs were ranked according to their potential to cause “harm”. -- Desorption rates of sorbed POPs from plastics were substantially enhanced under gut conditions specific of warm blooded organisms, suggesting potential transfer following ingestion

  8. Cytoskeletal actin networks in motile cells are critically self-organized systems synchronized by mechanical interactions

    Science.gov (United States)

    Cardamone, Luca; Laio, Alessandro; Torre, Vincent; Shahapure, Rajesh; DeSimone, Antonio

    2011-01-01

    Growing networks of actin fibers are able to organize into compact, stiff two-dimensional structures inside lamellipodia of crawling cells. We put forward the hypothesis that the growing actin network is a critically self-organized system, in which long-range mechanical stresses arising from the interaction with the plasma membrane provide the selective pressure leading to organization. We show that a simple model based only on this principle reproduces the stochastic nature of lamellipodia protrusion (growth periods alternating with fast retractions) and several of the features observed in experiments: a growth velocity initially insensitive to the external force; the capability of the network to organize its orientation; a load-history-dependent growth velocity. Our model predicts that the spectrum of the time series of the height of a growing lamellipodium decays with the inverse of the frequency. This behavior is a well-known signature of self-organized criticality and is confirmed by unique optical tweezer measurements performed in vivo on neuronal growth cones. PMID:21825142

  9. Evolution of organic molecules under Mars-like UV radiation conditions in space and laboratory

    Science.gov (United States)

    Rouquette, L.; Stalport, F.; Cottin, H.; Coll, P.; Szopa, C.; Saiagh, K.; Poch, O.; Khalaf, D.; Chaput, D.; Grira, K.; Dequaire, T.

    2017-09-01

    The detection and identification of organic molecules at Mars are of prime importance, as some of these molecules are life precursors and components. While in situ planetary missions are searching for them, it is essential to understand how organic molecules evolve and are preserved at the surface of Mars. Indeed the harsh conditions of the environment of Mars such as ultraviolet (UV) radiation or oxidative processes could explain the low abundance and diversity of organic molecules detected by now [1]. In order to get a better understanding of the evolution of organic matter at the surface of Mars, we exposed organic molecules under a Mars-like UV radiation environment. Similar organic samples were exposed to the Sun radiation, outside the International Space Station (ISS), and under a UV lamp (martian pressure and temperature conditions) in the laboratory. In both experiments, organic molecules tend to photodegrade under Mars-like UV radiation. Minerals, depending on their nature, can protect or accelerate the degradation of organic molecules. For some molecules, new products, possibly photoresistant, seem to be produced. Finally, experimenting in space allow us to get close to in situ conditions and to validate our laboratory experiment while the laboratory experiment is essential to study the evolution of a large amount and diversity of organic molecules.

  10. Interactive network configuration maintains bacterioplankton community structure under elevated CO2 in a eutrophic coastal mesocosm experiment

    Science.gov (United States)

    Lin, Xin; Huang, Ruiping; Li, Yan; Li, Futian; Wu, Yaping; Hutchins, David A.; Dai, Minhan; Gao, Kunshan

    2018-01-01

    There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO2 may influence bacterioplankton community structure.

  11. Interactive network configuration maintains bacterioplankton community structure under elevated CO2 in a eutrophic coastal mesocosm experiment

    Directory of Open Access Journals (Sweden)

    X. Lin

    2018-01-01

    Full Text Available There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO2 may influence bacterioplankton community structure.

  12. Dynamics of intracellular polymers in enhanced biological phosphorus removal processes under different organic carbon concentrations.

    Science.gov (United States)

    Xing, Lizhen; Ren, Li; Tang, Bo; Wu, Guangxue; Guan, Yuntao

    2013-01-01

    Enhanced biological phosphorus removal (EBPR) may deteriorate or fail during low organic carbon loading periods. Polyphosphate accumulating organisms (PAOs) in EBPR were acclimated under both high and low organic carbon conditions, and then dynamics of polymers in typical cycles, anaerobic conditions with excess organic carbons, and endogenous respiration conditions were examined. After long-term acclimation, it was found that organic loading rates did not affect the yield of PAOs and the applied low organic carbon concentrations were advantageous for the enrichment of PAOs. A low influent organic carbon concentration induced a high production of extracellular carbohydrate. During both anaerobic and aerobic endogenous respirations, when glycogen decreased to around 80 ± 10 mg C per gram of volatile suspended solids, PAOs began to utilize polyphosphate significantly. Regressed by the first-order reaction model, glycogen possessed the highest degradation rate and then was followed by polyphosphate, while biomass decay had the lowest degradation rate.

  13. Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization

    Science.gov (United States)

    2017-01-01

    Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity—a measure of network segregation—is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal

  14. Time Series Forecasting Energy-efficient Organization of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2007-09-01

    Full Text Available Due to their wide potential applications, wireless sensor networks have recentlyreceived tremendous attention. The strict energy constraints of sensor nodes result in thegreat challenges for energy efficiency. This paper investigates the energy efficiency problemand proposes an energy-efficient organization method with time series forecasting. Theorganization of wireless sensor networks is formulated for target tracking. Target model,multi-sensor model and energy model are defined accordingly. For the target trackingapplication, target localization is achieved by collaborative sensing with multi-sensor fusion.The historical localization results are utilized for adaptive target trajectory forecasting.Empirical mode decomposition is implemented to extract the inherent variation modes in thetime series of a target trajectory. Future target position is derived from autoregressivemoving average (ARMA models, which forecast the decomposition components,respectively. Moreover, the energy-efficient organization method is presented to enhance theenergy efficiency of wireless sensor networks. The sensor nodes implement sensing tasksaccording to the probability awakening in a distributed manner. When the sensor nodestransfer their observations to achieve data fusion, the routing scheme is obtained by antcolony optimization. Thus, both the operation and communication energy consumption canbe minimized. Experimental results verify that the combination of the ARMA model andempirical mode decomposition can estimate the target position efficiently and energy savingis achieved by the proposed organization method in wireless sensor networks.

  15. The development of an artificial organic networks toolkit for LabVIEW.

    Science.gov (United States)

    Ponce, Hiram; Ponce, Pedro; Molina, Arturo

    2015-03-15

    Two of the most challenging problems that scientists and researchers face when they want to experiment with new cutting-edge algorithms are the time-consuming for encoding and the difficulties for linking them with other technologies and devices. In that sense, this article introduces the artificial organic networks toolkit for LabVIEW™ (AON-TL) from the implementation point of view. The toolkit is based on the framework provided by the artificial organic networks technique, giving it the potential to add new algorithms in the future based on this technique. Moreover, the toolkit inherits both the rapid prototyping and the easy-to-use characteristics of the LabVIEW™ software (e.g., graphical programming, transparent usage of other softwares and devices, built-in programming event-driven for user interfaces), to make it simple for the end-user. In fact, the article describes the global architecture of the toolkit, with particular emphasis in the software implementation of the so-called artificial hydrocarbon networks algorithm. Lastly, the article includes two case studies for engineering purposes (i.e., sensor characterization) and chemistry applications (i.e., blood-brain barrier partitioning data model) to show the usage of the toolkit and the potential scalability of the artificial organic networks technique. © 2015 Wiley Periodicals, Inc.

  16. Reversible degradation in ITO-containing organic photovoltaics under concentrated sunlight

    NARCIS (Netherlands)

    Galagan, Y.O.; Mescheloff, A.; Veenstra, S.C.; Andriessen, H.A.J.M.; Katz, E.A.

    2015-01-01

    Stabilities of ITO-containing and ITO-free organic solar cells were investigated under simulated AM 1.5G illumination and under concentrated natural sunlight. In both cases ITO-free devices exhibit high stability, while devices containing ITO show degradation of their photovoltaic performance. The

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-05-17

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

  18. Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

    Science.gov (United States)

    Chen, Bor-Sen; Yeh, Chin-Hsun

    2017-12-01

    We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Automatic Matching of Multi-scale Road Networks under the Constraints of Smaller Scale Road Meshes

    Directory of Open Access Journals (Sweden)

    PEI Hongxing

    2017-06-01

    Full Text Available A new method is proposed to achieve automatic matching for multi-scale roads under the constraints of the smaller scale data. Firstly, meshes should be extracted from the two different scales road data. Secondly, several basic meshes in the larger scale road network will be merged as a composite one, which will be matched with one mesh from the smaller scale road network, so that the meshes with many-to-one and one-to-one matching relationships will be matched. Thirdly, meshes from the two different scale road data with many-to-many matching relationships will be matched. Finally, road will be classified into two categories under the constraints of meshes: mesh border roads and mesh internal roads, and then matching will be done in their own categories according to the matching relationships between the two scales meshes. The results showed that roads from different scale will be more precisely matched.

  20. Altered topological organization of white matter structural networks in patients with neuromyelitis optica.

    Directory of Open Access Journals (Sweden)

    Yaou Liu

    Full Text Available OBJECTIVE: To investigate the topological alterations of the whole-brain white-matter (WM structural networks in patients with neuromyelitis optica (NMO. METHODS: The present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups. RESULTS: The NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri. CONCLUSION: Although the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO.

  1. Inducing self-organized criticality in a network toy model by neighborhood assortativity.

    Science.gov (United States)

    Allen-Perkins, Alfonso; Galeano, Javier; Pastor, Juan Manuel

    2016-11-01

    Complex networks are a recent type of framework used to study complex systems with many interacting elements, such as self-organized criticality (SOC). The network nodes' tendency to link to other nodes of similar type is characterized by assortative mixing. Real networks exhibit assortative mixing by vertex degree, however, typical random network models, such as the Erdős-Rényi or the Barabási-Albert model, show no assortative arrangements. In this paper we introduce the notion of neighborhood assortativity as the tendency of a node to belong to a community (its neighborhood) showing an average property similar to its own. Imposing neighborhood assortative mixing by degree in a network toy model, SOC dynamics can be found. These dynamics are driven only by the network topology. The long-range correlations resulting from criticality have been characterized by means of fluctuation analysis and show an anticorrelation in the node's activity. The model contains only one parameter and its statistics plots for different values of the parameter can be collapsed into a single curve. The simplicity of the model allows us to perform numerical simulations and also to study analytically the statistics for a specific value of the parameter, making use of the Markov chains.

  2. Synchronization in material flow networks with biologically inspired self-organized control

    Energy Technology Data Exchange (ETDEWEB)

    Donner, Reik; Laemmer, Stefan [TU Dresden (Germany); Helbing, Dirk [ETH Zuerich (Switzerland)

    2009-07-01

    The efficient operation of material flows in traffic or production networks is a subject of broad economic interest. Traditional centralized as well as decentralized approaches to operating material flow networks are known to have severe disadvantages. As an alternative approach that may help to overcome these problems, we propose a simple self-organization mechanism of conflicting flows that is inspired by oscillatory phenomena of pedestrian or animal counter-flows at bottlenecks. As a result, one may observe a synchronization of the switching dynamics at different intersections in the network. For regular grid topologies, we find different synchronization regimes depending on the inertia of the switching from one service state to the next one. In order to test the robustness of our corresponding observations, we study how the detailed properties of the network as well as dynamic feedbacks between the relevant state variables affect the degree of achievable synchronization and the resulting performance of the network. Our results yield an improved understanding of the conditions that have to be present for efficiently operating material flow networks by a decentralized control, which is of paramount importance for future implementations in real-world traffic or production systems.

  3. Performance analysis of multi-radio routing protocol in cognitive radio ad hoc networks under different path failure rate

    International Nuclear Information System (INIS)

    Che-Aron, Z; Abdalla, A H; Abdullah, K; Hassan, W H

    2013-01-01

    In recent years, Cognitive Radio (CR) technology has largely attracted significant studies and research. Cognitive Radio Ad Hoc Network (CRAHN) is an emerging self-organized, multi-hop, wireless network which allows unlicensed users to opportunistically access available licensed spectrum bands for data communication under an intelligent and cautious manner. However, in CRAHNs, a lot of failures can easily occur during data transmission caused by PU (Primary User) activity, topology change, node fault, or link degradation. In this paper, an attempt has been made to evaluate the performance of the Multi-Radio Link-Quality Source Routing (MR-LQSR) protocol in CRAHNs under different path failure rate. In the MR-LQSR protocol, the Weighted Cumulative Expected Transmission Time (WCETT) is used as the routing metric. The simulations are carried out using the NS-2 simulator. The protocol performance is evaluated with respect to performance metrics like average throughput, packet loss, average end-to-end delay and average jitter. From the simulation results, it is observed that the number of path failures depends on the PUs number and mobility rate of SUs (Secondary Users). Moreover, the protocol performance is greatly affected when the path failure rate is high, leading to major service outages

  4. Soil aggregation and organic carbon of Oxisols under coffee in agroforestry systems

    Directory of Open Access Journals (Sweden)

    Gabriel Pinto Guimarães

    2014-02-01

    Full Text Available Intensive land use can lead to a loss of soil physical quality with negative impacts on soil aggregates, resistance to root penetration, porosity, and bulk density. Organic and agroforestry management systems can represent sustainable, well-balanced alternatives in the agroecosystem for promoting a greater input of organic matter than the conventional system. Based on the hypothesis that an increased input of organic matter improves soil physical quality, this study aimed to evaluate the impact of coffee production systems on soil physical properties in two Red-Yellow Oxisols (Latossolos Vermelho-Amarelos in the region of Caparaó, Espirito Santo, Brazil. On Farm 1, we evaluated the following systems: primary forest (Pf1, organic coffee (Org1 and conventional coffee (Con1. On Farm 2, we evaluated: secondary forest (Sf2, organic coffee intercropped with inga (Org/In2, organic coffee intercropped with leucaena and inga (Org/In/Le2, organic coffee intercropped with cedar (Org/Ced2 and unshaded conventional coffee (Con2. Soil samples were collected under the tree canopy from the 0-10, 10-20 and 20-40 cm soil layers. Under organic and agroforestry coffee management, soil aggregation was higher than under conventional coffee. In the agroforestry system, the degree of soil flocculation was 24 % higher, soil moisture was 80 % higher, and soil resistance to penetration was lower than in soil under conventional coffee management. The macroaggregates in the organic systems, Org/In2, Org/In/Le2, and Org/Ced2 contained, on average, 29.1, 40.1 and 34.7 g kg-1 organic carbon, respectively. These levels are higher than those found in the unshaded conventional system (Con2, with 20.2 g kg-1.

  5. Multi-scale parameterisation of a myocardial perfusion model using whole-organ arterial networks

    NARCIS (Netherlands)

    Hyde, Eoin R.; Cookson, Andrew N.; Lee, Jack; Michler, Christian; Goyal, Ayush; Sochi, Taha; Chabiniok, Radomir; Sinclair, Matthew; Nordsletten, David A.; Spaan, Jos; van den Wijngaard, Jeroen P. H. M.; Siebes, Maria; Smith, Nicolas P.

    2014-01-01

    A method to extract myocardial coronary permeabilities appropriate to parameterise a continuum porous perfusion model using the underlying anatomical vascular network is developed. Canine and porcine whole-heart discrete arterial models were extracted from high-resolution cryomicrotome vessel image

  6. Strategies for a better performance of RPL under mobility in wireless sensor networks

    Science.gov (United States)

    Latib, Z. A.; Jamil, A.; Alduais, N. A. M.; Abdullah, J.; Audah, L. H. M.; Alias, R.

    2017-09-01

    A Wireless Sensor Network (WSN) is usually stationary, which the network comprises of static nodes. The increase demand for mobility in various applications such as environmental monitoring, medical, home automation, and military, raises the question how IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) would perform under these mobility applications. This paper aims to understand performance of RPL and come out with strategies for a better performance of RPL in mobility scenarios. Because of this, this paper evaluates the performance of the RPL protocol under three different scenarios: sink and sensor nodes are static, static sink and mobile sensor nodes, and sink and sensor nodes are mobile. The network scenarios are implemented in Cooja simulator. A WSN consists of 25 sensor nodes and one sink node is configured in the simulation environment. The simulation is varied over different packet rates and ContikiMAC's Clear Channel Assessment (CCA) rate. As the performance metric, RPL is evaluated in term of packet delivery ratio (PDR), power consumption and packet rates. The simulation results show RPL provides a poor PDR in the mobility scenarios when compared to the static scenario. In addition, RPL consumes more power and increases duty-cycle rate to support mobility when compared to the static scenario. Based on the findings, we suggest three strategies for a better performance of RPL in mobility scenarios. First, RPL should operates at a lower packet rates when implemented in the mobility scenarios. Second, RPL should be implemented with a higher duty-cycle rate. Lastly, the sink node should be positioned as much as possible in the center of the mobile network.

  7. Fully transparent organic transistors with junction-free metallic network electrodes

    Energy Technology Data Exchange (ETDEWEB)

    Pei, Ke; Wang, Zongrong; Ren, Xiaochen; Zhang, Zhichao; Peng, Boyu; Chan, Paddy K. L., E-mail: pklc@hku.hk [Laboratory of Nanoscale Energy Conversion Devices and Physics, Department of Mechanical Engineering, The University of Hong Kong, Pokfulam (Hong Kong)

    2015-07-20

    We utilize highly transparent, junction-free metal network electrodes to fabricate fully transparent organic field effect transistors (OFETs). The patterned transparent Ag networks are developed by polymer crack template with adjustable line width and density. Sheet resistance of the network is 6.8 Ω/sq and optical transparency in the whole visible range is higher than 80%. The bottom contact OFETs with DNTT active layer and parylene-C dielectric insulator show a maximum field-effect mobility of 0.13 cm{sup 2}/V s (average mobility is 0.12 cm{sup 2}/V s) and on/off ratio is higher than 10{sup 7}. The current OFETs show great potential for applications in the next generation of transparent and flexible electronics.

  8. Fully transparent organic transistors with junction-free metallic network electrodes

    Science.gov (United States)

    Pei, Ke; Wang, Zongrong; Ren, Xiaochen; Zhang, Zhichao; Peng, Boyu; Chan, Paddy K. L.

    2015-07-01

    We utilize highly transparent, junction-free metal network electrodes to fabricate fully transparent organic field effect transistors (OFETs). The patterned transparent Ag networks are developed by polymer crack template with adjustable line width and density. Sheet resistance of the network is 6.8 Ω/sq and optical transparency in the whole visible range is higher than 80%. The bottom contact OFETs with DNTT active layer and parylene-C dielectric insulator show a maximum field-effect mobility of 0.13 cm2/V s (average mobility is 0.12 cm2/V s) and on/off ratio is higher than 107. The current OFETs show great potential for applications in the next generation of transparent and flexible electronics.

  9. RM-SORN: a reward-modulated self-organizing recurrent neural network.

    Science.gov (United States)

    Aswolinskiy, Witali; Pipa, Gordon

    2015-01-01

    Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

  10. Disrupted nodal and hub organization account for brain network abnormalities in Parkinson’s disease

    Directory of Open Access Journals (Sweden)

    Yuko Koshimori

    2016-11-01

    Full Text Available The recent application of graph theory to brain networks promises to shed light on complex diseases such as Parkinson’s disease. This study aimed to investigate functional changes in sensorimotor and cognitive networks in parkinsonian patients, with a focus on inter- and intra-connectivity organization in the disease-associated nodal and hub regions using the graph theoretical analyses. Resting-state functional MRI data of a total of 65 participants, including 23 healthy controls and 42 patients, were investigated in 120 nodes for local efficiency, betweenness centrality, and degree. Hub regions were identified in the healthy control and patient groups. We found nodal and hub changes in patients compared with healthy controls, including the right pre-supplementary motor area, left anterior insula, bilateral mid-insula, bilateral dorsolateral prefrontal cortex, and right caudate nucleus. In general, nodal regions within the sensorimotor network (i.e. right pre-supplementary motor area and right mid-insula displayed weakened connectivity, with the former node associated with more severe bradykinesia, and impaired integration with default mode network regions. The left mid-insula also lost its hub properties in patients. Within the executive networks, the left anterior insular cortex lost its hub properties in patients, while a new hub region was identified in the right caudate nucleus, paralleled by an increased level of inter- and intra-connectivity in the bilateral dorsolateral prefrontal cortex possibly representing compensatory mechanisms. These findings highlight the diffuse changes in nodal organization and regional hub disruption accounting for the distributed abnormalities across brain networks and the clinical manifestations of Parkinson’s disease.

  11. Microscopic mechanism for self-organized quasiperiodicity in random networks of nonlinear oscillators.

    Science.gov (United States)

    Burioni, Raffaella; di Santo, Serena; di Volo, Matteo; Vezzani, Alessandro

    2014-10-01

    Self-organized quasiperiodicity is one of the most puzzling dynamical phases observed in systems of nonlinear coupled oscillators. The single dynamical units are not locked to the periodic mean field they produce, but they still feature a coherent behavior, through an unexplained complex form of correlation. We consider a class of leaky integrate-and-fire oscillators on random sparse and massive networks with dynamical synapses, featuring self-organized quasiperiodicity, and we show how complex collective oscillations arise from constructive interference of microscopic dynamics. In particular, we find a simple quantitative relationship between two relevant microscopic dynamical time scales and the macroscopic time scale of the global signal. We show that the proposed relation is a general property of collective oscillations, common to all the partially synchronous dynamical phases analyzed. We argue that an analogous mechanism could be at the origin of similar network dynamics.

  12. Characterizing Design Process Interfaces as Organization Networks: Insights for Engineering Systems Management

    DEFF Research Database (Denmark)

    Ruiz, Pedro Parraguez; Eppinger, Steven; Maier, Anja

    2016-01-01

    and interpret the effect of those characteristics on interface problems. As a result, we show how structural and compositional aspects of the organization networks between information-dependent activities provide valuable insights to better manage complex engineering design processes. The proposed approach......The engineering design literature has provided guidance on how to identify and analyze design activities and their information dependencies. However, a systematic characterization of process interfaces between engineering design activities is missing, and the impact of structural and compositional...... aspects of interfaces on process performance is unclear. To fill these gaps, we propose a new approach that characterizes process interfaces as organization networks consisting of people and their interactions when performing interfacing activities. Furthermore, we provide guidance on how to test...

  13. Synchronization unveils the organization of ecological networks with positive and negative interactions.

    Science.gov (United States)

    Girón, Andrea; Saiz, Hugo; Bacelar, Flora S; Andrade, Roberto F S; Gómez-Gardeñes, Jesús

    2016-06-01

    Network science has helped to understand the organization principles of the interactions among the constituents of large complex systems. However, recently, the high resolution of the data sets collected has allowed to capture the different types of interactions coexisting within the same system. A particularly important example is that of systems with positive and negative interactions, a usual feature appearing in social, neural, and ecological systems. The interplay of links of opposite sign presents natural difficulties for generalizing typical concepts and tools applied to unsigned networks and, moreover, poses some questions intrinsic to the signed nature of the network, such as how are negative interactions balanced by positive ones so to allow the coexistence and survival of competitors/foes within the same system? Here, we show that synchronization phenomenon is an ideal benchmark for uncovering such balance and, as a byproduct, to assess which nodes play a critical role in the overall organization of the system. We illustrate our findings with the analysis of synthetic and real ecological networks in which facilitation and competitive interactions coexist.

  14. Studies of network organization and dynamics of e-beam crosslinked PVPs: From macro to nano

    International Nuclear Information System (INIS)

    Dispenza, C.; Grimaldi, N.; Sabatino, M.-A.; Todaro, S.; Bulone, D.; Giacomazza, D.; Przybytniak, G.; Alessi, S.; Spadaro, G.

    2012-01-01

    In this work the influence of poly(N-vinyl pyrrolidone) (PVP) concentration in water on the organization and dynamics of the corresponding macro-/nanogel networks has been systematically investigated. Irradiation has been performed at the same irradiation dose (within the sterilization dose range) and dose rate. In the selected irradiation conditions, the transition between macroscopic gelation and micro-/nanogels formation is observed just below the critical overlap concentration (∼1 wt%), whereas the net prevalence of intra-molecular over inter-molecular crosslinking occurs at a lower polymer concentration (below 0.25 wt%). Dynamic–mechanical spectroscopy has been applied as a classical methodology to estimate the network mesh size for macrogels in their swollen state, while 13 C NMR spin–lattice relaxation spectroscopy has been applied on both the macrogel and nanogel freeze dried residues to withdraw interesting information of the network spatial organization in the passage of scale from macro to nano. - Highlights: ► Aqueous solutions of commercial PVP were irradiated using linear electron accelerator. ► By varying polymer concentration it is possible to obtain information from macro to nano networks. ► Spin–lattice relaxation times are associated to the mobility of molecular segments. ► 1 H– 13 C-NMR proton relaxation time represents a junction between macro/nano world.

  15. CLUSTERISATION AND INFORMATION TECHNOLOGY IN ADVANCED TRAINING OF THE HEADS OF NETWORK EDUCATIONAL ORGANIZATIONS

    Directory of Open Access Journals (Sweden)

    Victoriia Stoikova

    2017-04-01

    Full Text Available The creation of strong basic schools with the network of branches and other networked educational organizations in the Ukrainian education system requires from leading cadres the possession of the basics of network management. The article deals with the questions of the process of forming professional competencies of heads of networked educational entities in conditions of postgraduate pedagogical education. The features of learning model which based on the active use of information and communication technologies are revealed have been disclosed; components of the open educational environment (cognitive, social and educational and their influence on the process of training leading cadres; advantages of using Internet technologies for educational purposes. The article describes the experience of organizing a continuous educational process by using the funds of information and communication technologies: websites, distance learning courses, social communities, and other Internet services. At the same time, heads of educational institutions are united in cluster formations by type of educational institutions, the level of providing educational services, the direction of professional interests, preferences, and also for the joint development of managerial algorithms in certain typical situations and for solving typical professional problems. In such a model of learning, knowledge is produced by participants independently during active activity by joint search, processing, and analysis of information, solving problem situations, discussions, debates, etc.

  16. Cooperative Networks: Altruism, Group Solidarity, Reciprocity, and Sanctioning in Ugandan Producer Organizations.

    Science.gov (United States)

    Baldassarri, Delia

    2015-09-01

    Repeated interaction and social networks are commonly considered viable solutions to collective action problems. This article identifies and systematically measures four general mechanisms--that is, generalized altruism, group solidarity, reciprocity, and the threat of sanctioning--and tests which of them brings about cooperation in the context of Ugandan producer organizations. Using an innovative methodological framework that combines "lab-in-the-field" experiments with survey interviews and complete social networks data, the article goes beyond the assessment of a relationship between social networks and collective outcomes to study the mechanisms that favor cooperative behavior. The article first establishes a positive relationship between position in the network structure and propensity to cooperate in the producer organization and then uses farmers' behavior in dictator and public goods games to test different mechanisms that may account for such a relationship. Results show that cooperation is induced by patterns of reciprocity that emerge through repeated interaction rather than other-regarding preferences like altruism or group solidarity.

  17. Using the Weighted Rich-Club Coefficient to Explore Traffic Organization in Mobility Networks

    Science.gov (United States)

    Ramasco, José J.; Colizza, Vittoria; Panzarasa, Pietro

    The aim of a transportation system is to enable the movement of goods or persons between any two locations with the highest possible efficiency. This simple principle inspires highly complex structures in a number of real-world mobility networks of different kind that often exhibit a hierarchical organization. In this paper, we rely on a framework that has been recently introduced for the study of the management and distribution of resources in different real-world systems. This framework offers a new method for exploring the tendency of the top elements to form clubs with exclusive control over the system’s resources. Such tendency is known as the weighted rich-club effect. We apply the method to three cases of mobility networks at different scales of resolution: the US air transportation network, the US counties daily commuting, and the Italian municipalities commuting datasets. In all cases, a strong weighted rich-club effect is found. We also show that a very simple model can account for part of the intrinsic features of mobility networks, while deviations found between the theoretical predictions and the empirical observations point to the presence of higher levels of organization.

  18. Synaptic Noise Facilitates the Emergence of Self-Organized Criticality in the Caenorhabditis elegans Neuronal Network

    OpenAIRE

    Çiftçi, Koray

    2017-01-01

    Avalanches with power-law distributed size parameters have been observed in neuronal networks. This observation might be a manifestation of the self-organized criticality (SOC). Yet, the physiological mechanicsm of this behavior is currently unknown. Describing synaptic noise as transmission failures mainly originating from the probabilistic nature of neurotransmitter release, this study investigates the potential of this noise as a mechanism for driving the functional architecture of the neu...

  19. Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

    International Nuclear Information System (INIS)

    Correa, R.; Chesta, M.A.; Morales, J.R.; Dinator, M.I.; Requena, I.; Vila, I.

    2006-01-01

    An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses

  20. Feature discovery on segmented objects in SAR imagery using self-organizing neural networks

    Science.gov (United States)

    Fogler, Robert J.; Koch, Mark W.; Moya, Mary M.; Hush, Donald R.

    In this paper we investigate the applicability of the feature extraction mechanisms found in the neurophysiology of mammals to the problem of object recognition in synthetic aperture radar imagery. Our approach presents multiple views of target objects to a two-stage-organizing neural network architecture. The first stage, a Neocognitron, performs two layers of feature extraction. The resulting feature vectors are presented to the second stage, an ART-2A classifier self-organizing neural network which clusters the features into multiple object categories. In our first experiments reported in a previous paper, the Neocognitron was trained on raw SAR imagery. The architecture was able to recognize a simulated vehicle at arbitrary azimuthal orientations at a single depression angle while rejecting clutter as well as other vehicles. Feature extraction on raw imagery yielded features that were robust but difficult to interpret. We have performed new experiments in which the self-organization process is used to discover features separately in shadow and bright returns from objects to be recognized. feature extraction on shadow returns yields oriented contrast edge operators suggestive of bipartite simple cells observed in the striate cortex of mammals. Feature extraction on the specularity patterns in bright returns yield a mixture of orientation-independent operators similar to those found in the retina, and a collection of symmetric oriented contrast edge operators. These operators are formed at multiple positions within the receptive fields during the self-organization process and collectively resemble a two-dimensional Haar basis set. we merge the feature operators discovered separately in shadow and bright returns into a combined feature extractor front end. This front end is designed to extract the desired features from raw imagery. We compare the performance of the earlier two-stage neural network with a modified network using the new feature set.

  1. Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

    Energy Technology Data Exchange (ETDEWEB)

    Correa, R. [Universidad Tecnologica Metropolitana, Departamento de Fisica, Av. Jose Pedro Alessandri 1242, Nunoa, Santiago (Chile)]. E-mail: rcorrea@utem.cl; Chesta, M.A. [Universidad Nacional de Cordoba, Facultad de Matematica, Astronomia y Fisica, Medina Allende s/n Ciudad Universitaria, 5000 Cordoba (Argentina)]. E-mail: chesta@famaf.unc.edu.ar; Morales, J.R. [Universidad de Chile, Facultad de Ciencias, Departamento de Fisica, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: rmorales@uchile.cl; Dinator, M.I. [Universidad de Chile, Facultad de Ciencias, Departamento de Fisica, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: mdinator@uchile.cl; Requena, I. [Universidad de Granada, Departamento de Ciencias de la Computacion e Inteligencia Artificial, Daniel Saucedo Aranda s/n, 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Vila, I. [Universidad de Chile, Facultad de Ciencias, Departamento de Ecologia, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: limnolog@uchile.cl

    2006-08-15

    An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses.

  2. Neural network model for evaluation of seedling vigour under clinostated conditions

    Science.gov (United States)

    Zaidi, M.; Murase, H.

    A hierarchical neural net can be applied to simulate nonlinear phenomena found in biological systems. The learning process of the hierarchical neural net can be used as an algorithm for nonlinear multivariate analysis. The non- invasive technique for monitoring the plant's growth stage is one part of the required technology of the bio-response feedback control system. The stage of a plant's growth can be identified or quantified by measuring physical indices. Automated monitoring is also necessary in the clinostat experiment and neural networks are used for the calibration of lettuce plant growth. A back propagation neural network was trained to evaluate the plant growth in terms of plant growth characteristics, with a network consisting of 4, 8 and 1 processing units in the input, hidden and output layers, respectively. Sixteen sets of training data were used. The training was terminated after 800 times of iterative calculations at the RMS error value equal to 3.35x10-3 . Four sets of validation data were used to calculate the prediction error. The ability of the neural network models to predict the required information is very accurate. As a result, there is potential for the present technique to be applied to seedling vigour evaluating system under the clinostated conditions.

  3. Determinants of investment under incentive regulation: The case of the Norwegian electricity distribution networks

    International Nuclear Information System (INIS)

    Poudineh, Rahmatallah; Jamasb, Tooraj

    2016-01-01

    Investment in electricity networks, as regulated natural monopolies, is among the highest regulatory and energy policy priorities. The electricity sector regulators adopt different incentive mechanisms to ensure that the firms undertake sufficient investment to maintain and modernise the grid. Thus, an effective regulatory treatment of investment requires understanding the response of companies to the regulatory incentives. This study analyses the determinants of investment in electricity distribution networks using a panel dataset of 129 Norwegian companies observed from 2004 to 2010. A Bayesian Model Averaging approach is used to provide a robust statistical inference by taking into account the uncertainties around model selection and estimation. The results show that three factors drive nearly all network investments: investment rate in previous period, socio-economic costs of energy not supplied and finally useful life of assets. The results indicate that Norwegian companies have, to some degree, responded to the investment incentives provided by the regulatory framework. However, some of the incentives do not appear to be effective in driving the investments. - Highlights: • This paper investigates determinants of investment under incentive regulation. • We apply a Bayesian model averaging technique to deal with model uncertainty. • Dataset comprises 129 Norwegian electricity network companies from 2004 to 2010. • The results show that firms have generally responded to investment incentives. • However, some of the incentives do not appear to have been effective.

  4. A multi-period distribution network design model under demand uncertainty

    Science.gov (United States)

    Tabrizi, Babak H.; Razmi, Jafar

    2013-05-01

    Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

  5. Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome

    Science.gov (United States)

    Haimovici, Ariel; Tagliazucchi, Enzo; Balenzuela, Pablo; Chialvo, Dante R.

    2013-04-01

    The relation between large-scale brain structure and function is an outstanding open problem in neuroscience. We approach this problem by studying the dynamical regime under which realistic spatiotemporal patterns of brain activity emerge from the empirically derived network of human brain neuroanatomical connections. The results show that critical dynamics unfolding on the structural connectivity of the human brain allow the recovery of many key experimental findings obtained from functional magnetic resonance imaging, such as divergence of the correlation length, the anomalous scaling of correlation fluctuations, and the emergence of large-scale resting state networks.

  6. Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution

    Science.gov (United States)

    Tse, Amanda; Verkhivker, Gennady M.

    2015-01-01

    Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib) and promiscuous (Bosutinib, Dasatinib) kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations of key mediating

  7. Online network organization of Barcelona en Comú, an emergent movement-party.

    Science.gov (United States)

    Aragón, Pablo; Gallego, Helena; Laniado, David; Volkovich, Yana; Kaltenbrunner, Andreas

    2017-01-01

    The emerging grassroots party Barcelona en Comú won the 2015 Barcelona City Council election. This candidacy was devised by activists involved in the Spanish 15M movement to transform citizen outrage into political change. On the one hand, the 15M movement was based on a decentralized structure. On the other hand, political science literature postulates that parties develop oligarchical leadership structures. This tension motivates to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. In this study we develop a computational methodology to characterize the online network organization of every party in the election campaign on Twitter. Results on the network of retweets reveal that, while traditional parties are organized in a single cluster, for Barcelona en Comú two well-defined groups co-exist: a centralized cluster led by the candidate and party accounts, and a decentralized cluster with the movement activists. Furthermore, results on the network of replies also shows a dual structure: a cluster around the candidate receiving the largest attention from other parties, and another with the movement activists exhibiting a higher predisposition to dialogue with other parties.

  8. Reporting Organ Trafficking Networks: A Survey-Based Plea to Breach the Secrecy Oath.

    Science.gov (United States)

    Ambagtsheer, F; Van Balen, L J; Duijst-Heesters, W L J M; Massey, E K; Weimar, W

    2015-07-01

    Patients travel worldwide to purchase kidneys. Transplant professionals can play a role in identifying kidney purchase. However, due to the tension between their rights and obligations, a lack of understanding and knowledge exists on how to prevent and report purchase. We present the results of a national survey that describes transplant professionals' experiences, attitudes, behaviors, conflicts of duties, legal knowledge and needs for guidelines toward patients who purchase kidneys abroad. Second, we clarify professionals' rights and obligations regarding organ purchase and propose actions that they can take to report purchase. Of the 100/241 (42%) professionals who treated patients who traveled to a country outside the European Union for a kidney transplant, 31 (31%) were certain that patients purchased kidneys. Sixty-five (65%) had suspicions that patients had bought kidneys. The majority reported a conflict of duties. Eighty percent reported a need for guidelines. Professionals can help prevent organ purchase by disclosing information about organ trafficking networks to law enforcement. Such disclosure can support the investigation and prosecution of networks. We offer key components for guidelines on disclosure of these networks. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons.

  9. HEMATOLOGICAL INDICES OF RAT ORGANISMS UNDER CONDITIONS OF OXIDATIVE STRESS AND LIPOSOMAL PREPARATION ACTION

    OpenAIRE

    M. Khariv; B. V. Gutyj; V. Butsyak; І. Khariv

    2016-01-01

    The article deals with the results of search of the influence of developed complex liposomal drug on dynamics of hematological parameters of rat organisms under conditions of simulated oxidative stress caused by the use of carbon tetrachloride. Intramuscular injection of 50% tetrachloromethane to rats at a dose of 0.25 ml per 100 g of body weight causes antigenic load on the body and leads to disruption of physiologic level of hematological indices of experimental animal organisms. This indic...

  10. Modeling and simulating command and control for organizations under extreme situations

    CERN Document Server

    Moon, Il-Chul; Kim, Tag Gon

    2013-01-01

    Commanding and controlling organizations in extreme situations is a challenging task in military, intelligence, and disaster management. Such command and control must be quick, effective, and considerate when dealing with the changing, complex, and risky conditions of the situation. To enable optimal command and control under extremes, robust structures and efficient operations are required of organizations. This work discusses how to design and conduct virtual experiments on resilient organizational structures and operational practices using modeling and simulation. The work illustrates key a

  11. Gene Profiling of Aortic Valve Interstitial Cells under Elevated Pressure Conditions: Modulation of Inflammatory Gene Networks

    Directory of Open Access Journals (Sweden)

    James N. Warnock

    2011-01-01

    Full Text Available The study aimed to identify mechanosensitive pathways and gene networks that are stimulated by elevated cyclic pressure in aortic valve interstitial cells (VICs and lead to detrimental tissue remodeling and/or pathogenesis. Porcine aortic valve leaflets were exposed to cyclic pressures of 80 or 120 mmHg, corresponding to diastolic transvalvular pressure in normal and hypertensive conditions, respectively. Linear, two-cycle amplification of total RNA, followed by microarray was performed for transcriptome analysis (with qRT-PCR validation. A combination of systems biology modeling and pathway analysis identified novel genes and molecular mechanisms underlying the biological response of VICs to elevated pressure. 56 gene transcripts related to inflammatory response mechanisms were differentially expressed. TNF-α, IL-1α, and IL-1β were key cytokines identified from the gene network model. Also of interest was the discovery that pentraxin 3 (PTX3 was significantly upregulated under elevated pressure conditions (41-fold change. In conclusion, a gene network model showing differentially expressed inflammatory genes and their interactions in VICs exposed to elevated pressure has been developed. This system overview has detected key molecules that could be targeted for pharmacotherapy of aortic stenosis in hypertensive patients.

  12. Disrupted topological organization of brain structural network associated with prior overt hepatic encephalopathy in cirrhotic patients

    International Nuclear Information System (INIS)

    Chen, Hua-Jun; Shi, Hai-Bin; Jiang, Long-Feng; Li, Lan; Chen, Rong

    2018-01-01

    To investigate structural brain connectome alterations in cirrhotic patients with prior overt hepatic encephalopathy (OHE). Seventeen cirrhotic patients with prior OHE (prior-OHE), 18 cirrhotic patients without prior OHE (non-prior-OHE) and 18 healthy controls (HC) underwent diffusion tensor imaging. Neurocognitive functioning was assessed with Psychometric Hepatic Encephalopathy Score (PHES). Using a probabilistic fibre tracking approach, we depicted the whole-brain structural network as a connectivity matrix of 90 regions (derived from the Automated Anatomic Labeling atlas). Graph theory-based analyses were performed to analyse topological properties of the brain network. The analysis of variance showed significant group effects on several topological properties, including network strength, global efficiency and local efficiency. A progressive decrease trend for these metrics was found from non-prior-OHE to prior-OHE, compared with HC. Among the three groups, the regions with altered nodal efficiency were mainly distributed in the frontal and occipital cortices, paralimbic system and subcortical regions. The topological metrics, such as network strength and global efficiency, were correlated with PHES among cirrhotic patients. The cirrhotic patients developed structural brain connectome alterations; this is aggravated by prior OHE episode. Disrupted topological organization of the brain structural network may account for cognitive impairments related to prior OHE. (orig.)

  13. Disrupted topological organization of brain structural network associated with prior overt hepatic encephalopathy in cirrhotic patients

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hua-Jun [Fujian Medical University Union Hospital, Department of Radiology, Fuzhou (China); The First Affiliated Hospital of Nanjing Medical University, Department of Radiology, Nanjing (China); Shi, Hai-Bin [The First Affiliated Hospital of Nanjing Medical University, Department of Radiology, Nanjing (China); Jiang, Long-Feng [The First Affiliated Hospital of Nanjing Medical University, Department of Infectious Diseases, Nanjing (China); Li, Lan [Fujian Medical University Union Hospital, Department of Radiology, Fuzhou (China); Chen, Rong [University of Maryland School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Baltimore, MD (United States); Beijing Institute of Technology, Advanced Innovation Center for Intelligent Robots and Systems, Beijing (China)

    2018-01-15

    To investigate structural brain connectome alterations in cirrhotic patients with prior overt hepatic encephalopathy (OHE). Seventeen cirrhotic patients with prior OHE (prior-OHE), 18 cirrhotic patients without prior OHE (non-prior-OHE) and 18 healthy controls (HC) underwent diffusion tensor imaging. Neurocognitive functioning was assessed with Psychometric Hepatic Encephalopathy Score (PHES). Using a probabilistic fibre tracking approach, we depicted the whole-brain structural network as a connectivity matrix of 90 regions (derived from the Automated Anatomic Labeling atlas). Graph theory-based analyses were performed to analyse topological properties of the brain network. The analysis of variance showed significant group effects on several topological properties, including network strength, global efficiency and local efficiency. A progressive decrease trend for these metrics was found from non-prior-OHE to prior-OHE, compared with HC. Among the three groups, the regions with altered nodal efficiency were mainly distributed in the frontal and occipital cortices, paralimbic system and subcortical regions. The topological metrics, such as network strength and global efficiency, were correlated with PHES among cirrhotic patients. The cirrhotic patients developed structural brain connectome alterations; this is aggravated by prior OHE episode. Disrupted topological organization of the brain structural network may account for cognitive impairments related to prior OHE. (orig.)

  14. Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles

    Directory of Open Access Journals (Sweden)

    Marie-Josée Fleury

    2017-03-01

    Full Text Available Introduction: This study evaluates implementation of the Quebec Mental Health Reform (2005–2015, which promoted the development of integrated service networks, in 11 local service networks organized into four territorial groups according to socio-demographic characteristics and mental health services offered. Methods: Data were collected from documents concerning networks; structured questionnaires completed by 90 managers and by 16 respondent-psychiatrists; and semi-structured interviews with 102 network stakeholders. Factors associated with implementation and integration were organized according to: 1 reform characteristics; 2 implementation context; 3 organizational characteristics; and 4 integration strategies. Results: While local networks were in a process of development and expansion, none were fully integrated at the time of the study. Facilitators and barriers to implementation and integration were primarily associated with organizational characteristics. Integration was best achieved in larger networks including a general hospital with a psychiatric department, followed by networks with a psychiatric hospital. Formalized integration strategies such as service agreements, liaison officers, and joint training reduced some barriers to implementation in networks experiencing less favourable conditions. Conclusion: Strategies for the implementation of healthcare reform and integrated service networks should include sustained support and training in best-practices, adequate performance indicators and resources, formalized integration strategies to improve network coordination and suitable initiatives to promote staff retention.

  15. Processes leading to increased soil organic carbon in a Mojave Desert ecosystem under elevated CO2

    Science.gov (United States)

    Koyama, A.; Evans, R. D.

    2011-12-01

    We observed increased soil organic carbon (SOC) following ten years of elevated atmospheric CO2 treatment at the Nevada Desert FACE Facility in the Mojave Desert. Physical and chemical fractions of surface soils collected under the dominant shrub, Larrea tridentata (Larrea), and plant interspace were analyzed for particle size, plant-derived n-alkanes, microbial phospholipid fatty acids (PLFA) and neutral lipid fatty acids (NLFA) to explore potential mechanisms causing the observed increase in SOC. SOC concentrations under Larrea in bulk soils, coarse particulate organic matter (POM), fine POM and mineral-bound soil organic matter (SOM) under elevated CO2 were greater than those under ambient CO2 by 34%, 45%, 26% and 20%, respectively. Under Larrea, n-alkane concentrations were 52% greater under elevated compared to ambient CO2. Such increases in coarse POM and n-alkane concentrations suggest litter input from Larrea was at least one source for increased SOC under elevated CO2. While there was no significant difference in PLFA abundance between the CO2 treatments, elevated CO2 significantly increased the fungi to bacterial PLFA ratio. In addition, fungal and bacterial NLFA and NLFA 16:1ω5, a biomarker of arbuscular mycorrhizal fungi, were significantly higher under elevated than ambient CO2. These observations plus others suggest that Larrea allocated more photosynthate belowground to increased root exudation rather than increased fine root growth under elevated CO2. Thus, increased root exudates and microbial residues as well as episodic increases in litter input from Larrea are mechanisms behind the increased SOC under elevated CO2. Elevated CO2 did not increase SOC in surface soils in plant interspace despite incorporation of CO2 labeled with 13C under elevated CO2.

  16. Modelling soil organic carbon stocks along topographic transects under climate change scenarios using CarboSOIL

    Science.gov (United States)

    Kotb Abd-Elmabod, Sameh; Muñoz-Rojas, Miriam; Jordán, Antonio; Anaya-Romero, María; de la Rosa, Diego

    2014-05-01

    CarboSOIL is a land evaluation model for soil organic carbon (SOC) accounting under global change scenarios (Muñoz-Rojas et al., 2013a; 2013b) and is a new component of the MicroLEIS Decision Support System. MicroLEIS is a tool for decision-makers dealing with specific agro-ecological problems as, for example, soil contamination risks (Abd-Elmabod et al., 2010; Abd-Elmabod et al., 2012)which has been designed as a knowledge-based approach incorporating a set of interlinked data bases. Global change and land use changes in recent decades have caused relevant impacts in vegetation carbon stocks (Muñoz-Rojas et al., 2011) and soil organic carbon stocks, especially in sensible areas as the Mediterranean region (Muñoz-Rojas et al., 2012a; 2012b). This study aims to investigate the influence of topography, climate, land use and soil factors on SOC stocks by the application of CarboSOIL in a representative area of the Mediterranean region (Seville, Spain). Two topographic transects (S-N and W-E oriented) were considered, including 63 points separated 4 km each. These points are associated to 41 soil profiles extracted from the SDBm soil data base (De la Rosa et al., 2001) and climatic information (average minimum temperature, average maximum temperature and average rainfall per month) extracted from raster data bases (Andalusian Environmental Information Network, REDIAM). CarboSOIL has been applied along topographic transects at different soil depths and under different climate change scenarios. Climate scenarios have been calculated according to the global climate model (CNRMCM3) by extracting spatial climate data under IPCC A1B scenario for the current period (average data from 1960-2000), 2040, 2070 and 2100. In the current scenario, results show that the highest SOC stock values located on Typic Haploxeralfs under olive groves for soil sections 0-25 cm and for 25-50 cm, but the highest values were determined on fruit-cropped Rendolic Xerothent in the 50-75cm

  17. Complex network analysis of phase dynamics underlying oil-water two-phase flows

    Science.gov (United States)

    Gao, Zhong-Ke; Zhang, Shan-Shan; Cai, Qing; Yang, Yu-Xuan; Jin, Ning-De

    2016-01-01

    Characterizing the complicated flow behaviors arising from high water cut and low velocity oil-water flows is an important problem of significant challenge. We design a high-speed cycle motivation conductance sensor and carry out experiments for measuring the local flow information from different oil-in-water flow patterns. We first use multivariate time-frequency analysis to probe the typical features of three flow patterns from the perspective of energy and frequency. Then we infer complex networks from multi-channel measurements in terms of phase lag index, aiming to uncovering the phase dynamics governing the transition and evolution of different oil-in-water flow patterns. In particular, we employ spectral radius and weighted clustering coefficient entropy to characterize the derived unweighted and weighted networks and the results indicate that our approach yields quantitative insights into the phase dynamics underlying the high water cut and low velocity oil-water flows. PMID:27306101

  18. Topological Control on the Structural Relaxation of Atomic Networks under Stress

    Science.gov (United States)

    Bauchy, Mathieu; Wang, Mengyi; Yu, Yingtian; Wang, Bu; Krishnan, N. M. Anoop; Masoero, Enrico; Ulm, Franz-Joseph; Pellenq, Roland

    2017-07-01

    Upon loading, atomic networks can feature delayed irreversible relaxation. However, the effect of composition and structure on relaxation remains poorly understood. Herein, relying on accelerated molecular dynamics simulations and topological constraint theory, we investigate the relationship between atomic topology and stress-induced structural relaxation, by taking the example of creep deformations in calcium silicate hydrates (C - S - H ), the binding phase of concrete. Under constant shear stress, C - S - H is found to feature delayed logarithmic shear deformations. We demonstrate that the propensity for relaxation is minimum for isostatic atomic networks, which are characterized by the simultaneous absence of floppy internal modes of relaxation and eigenstress. This suggests that topological nanoengineering could lead to the discovery of nonaging materials.

  19. Under-Frequency Load Shedding Technique Considering Event-Based for an Islanded Distribution Network

    Directory of Open Access Journals (Sweden)

    Hasmaini Mohamad

    2016-06-01

    Full Text Available One of the biggest challenge for an islanding operation is to sustain the frequency stability. A large power imbalance following islanding would cause under-frequency, hence an appropriate control is required to shed certain amount of load. The main objective of this research is to develop an adaptive under-frequency load shedding (UFLS technique for an islanding system. The technique is designed considering an event-based which includes the moment system is islanded and a tripping of any DG unit during islanding operation. A disturbance magnitude is calculated to determine the amount of load to be shed. The technique is modeled by using PSCAD simulation tool. A simulation studies on a distribution network with mini hydro generation is carried out to evaluate the UFLS model. It is performed under different load condition: peak and base load. Results show that the load shedding technique have successfully shed certain amount of load and stabilized the system frequency.

  20. Distinct soil microbial diversity under long-term organic and conventional farming

    Science.gov (United States)

    Hartmann, Martin; Frey, Beat; Mayer, Jochen; Mäder, Paul; Widmer, Franco

    2015-01-01

    Low-input agricultural systems aim at reducing the use of synthetic fertilizers and pesticides in order to improve sustainable production and ecosystem health. Despite the integral role of the soil microbiome in agricultural production, we still have a limited understanding of the complex response of microbial diversity to organic and conventional farming. Here we report on the structural response of the soil microbiome to more than two decades of different agricultural management in a long-term field experiment using a high-throughput pyrosequencing approach of bacterial and fungal ribosomal markers. Organic farming increased richness, decreased evenness, reduced dispersion and shifted the structure of the soil microbiota when compared with conventionally managed soils under exclusively mineral fertilization. This effect was largely attributed to the use and quality of organic fertilizers, as differences became smaller when conventionally managed soils under an integrated fertilization scheme were examined. The impact of the plant protection regime, characterized by moderate and targeted application of pesticides, was of subordinate importance. Systems not receiving manure harboured a dispersed and functionally versatile community characterized by presumably oligotrophic organisms adapted to nutrient-limited environments. Systems receiving organic fertilizer were characterized by specific microbial guilds known to be involved in degradation of complex organic compounds such as manure and compost. The throughput and resolution of the sequencing approach permitted to detect specific structural shifts at the level of individual microbial taxa that harbours a novel potential for managing the soil environment by means of promoting beneficial and suppressing detrimental organisms. PMID:25350160

  1. Distinct soil microbial diversity under long-term organic and conventional farming.

    Science.gov (United States)

    Hartmann, Martin; Frey, Beat; Mayer, Jochen; Mäder, Paul; Widmer, Franco

    2015-05-01

    Low-input agricultural systems aim at reducing the use of synthetic fertilizers and pesticides in order to improve sustainable production and ecosystem health. Despite the integral role of the soil microbiome in agricultural production, we still have a limited understanding of the complex response of microbial diversity to organic and conventional farming. Here we report on the structural response of the soil microbiome to more than two decades of different agricultural management in a long-term field experiment using a high-throughput pyrosequencing approach of bacterial and fungal ribosomal markers. Organic farming increased richness, decreased evenness, reduced dispersion and shifted the structure of the soil microbiota when compared with conventionally managed soils under exclusively mineral fertilization. This effect was largely attributed to the use and quality of organic fertilizers, as differences became smaller when conventionally managed soils under an integrated fertilization scheme were examined. The impact of the plant protection regime, characterized by moderate and targeted application of pesticides, was of subordinate importance. Systems not receiving manure harboured a dispersed and functionally versatile community characterized by presumably oligotrophic organisms adapted to nutrient-limited environments. Systems receiving organic fertilizer were characterized by specific microbial guilds known to be involved in degradation of complex organic compounds such as manure and compost. The throughput and resolution of the sequencing approach permitted to detect specific structural shifts at the level of individual microbial taxa that harbours a novel potential for managing the soil environment by means of promoting beneficial and suppressing detrimental organisms.

  2. Organic vs. organic - soil arthropods as bioindicators of ecological sustainability in greenhouse system experiment under Mediterranean conditions.

    Science.gov (United States)

    Madzaric, Suzana; Ceglie, F G; Depalo, L; Al Bitar, L; Mimiola, G; Tittarelli, F; Burgio, G

    2017-11-23

    Organic greenhouse (OGH) production is characterized by different systems and agricultural practices with diverse environmental impact. Soil arthropods are widely used as bioindicators of ecological sustainability in open field studies, while there is a lack of research on organic production for protected systems. This study assessed the soil arthropod abundance and diversity over a 2-year crop rotation in three systems of OGH production in the Mediterranean. The systems under assessment differed in soil fertility management: SUBST - a simplified system of organic production, based on an input substitution approach (use of guano and organic liquid fertilizers), AGROCOM - soil fertility mainly based on compost application and agroecological services crops (ASC) cultivation (tailored use of cover crops) as part of crop rotation, and AGROMAN - animal manure and ASC cultivation as part of crop rotation. Monitoring of soil fauna was performed by using pitfall traps and seven taxa were considered: Carabidae, Staphylinidae, Araneae, Opiliones, Isopoda, Myriapoda, and Collembola. Results demonstrated high potential of ASC cultivation as a technique for beneficial soil arthropod conservation in OGH conditions. SUBST system was dominated by Collembola in all crops, while AGROMAN and AGROCOM had more balanced relative abundance of Isopoda, Staphylinidae, and Aranea. Opiliones and Myriapoda were more affected by season, while Carabidae were poorly represented in the whole monitoring period. Despite the fact that all three production systems are in accordance with the European Union regulation on organic farming, findings of this study displayed significant differences among them and confirmed the suitability of soil arthropods as bioindicators in protected systems of organic farming.

  3. Network structure underlying resolution of conflicting non-verbal and verbal social information.

    Science.gov (United States)

    Watanabe, Takamitsu; Yahata, Noriaki; Kawakubo, Yuki; Inoue, Hideyuki; Takano, Yosuke; Iwashiro, Norichika; Natsubori, Tatsunobu; Takao, Hidemasa; Sasaki, Hiroki; Gonoi, Wataru; Murakami, Mizuho; Katsura, Masaki; Kunimatsu, Akira; Abe, Osamu; Kasai, Kiyoto; Yamasue, Hidenori

    2014-06-01

    Social judgments often require resolution of incongruity in communication contents. Although previous studies revealed that such conflict resolution recruits brain regions including the medial prefrontal cortex (mPFC) and posterior inferior frontal gyrus (pIFG), functional relationships and networks among these regions remain unclear. In this functional magnetic resonance imaging study, we investigated the functional dissociation and networks by measuring human brain activity during resolving incongruity between verbal and non-verbal emotional contents. First, we found that the conflict resolutions biased by the non-verbal contents activated the posterior dorsal mPFC (post-dmPFC), bilateral anterior insula (AI) and right dorsal pIFG, whereas the resolutions biased by the verbal contents activated the bilateral ventral pIFG. In contrast, the anterior dmPFC (ant-dmPFC), bilateral superior temporal sulcus and fusiform gyrus were commonly involved in both of the resolutions. Second, we found that the post-dmPFC and right ventral pIFG were hub regions in networks underlying the non-verbal- and verbal-content-biased resolutions, respectively. Finally, we revealed that these resolution-type-specific networks were bridged by the ant-dmPFC, which was recruited for the conflict resolutions earlier than the two hub regions. These findings suggest that, in social conflict resolutions, the ant-dmPFC selectively recruits one of the resolution-type-specific networks through its interaction with resolution-type-specific hub regions. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  4. Common modulation of limbic network activation underlies musical emotions as they unfold.

    Science.gov (United States)

    Singer, Neomi; Jacoby, Nori; Lin, Tamar; Raz, Gal; Shpigelman, Lavi; Gilam, Gadi; Granot, Roni Y; Hendler, Talma

    2016-11-01

    Music is a powerful means for communicating emotions among individuals. Here we reveal that this continuous stream of affective information is commonly represented in the brains of different listeners and that particular musical attributes mediate this link. We examined participants' brain responses to two naturalistic musical pieces using functional Magnetic Resonance imaging (fMRI). Following scanning, as participants listened to the musical pieces for a second time, they continuously indicated their emotional experience on scales of valence and arousal. These continuous reports were used along with a detailed annotation of the musical features, to predict a novel index of Dynamic Common Activation (DCA) derived from ten large-scale data-driven functional networks. We found an association between the unfolding music-induced emotionality and the DCA modulation within a vast network of limbic regions. The limbic-DCA modulation further corresponded with continuous changes in two temporal musical features: beat-strength and tempo. Remarkably, this "collective limbic sensitivity" to temporal features was found to mediate the link between limbic-DCA and the reported emotionality. An additional association with the emotional experience was found in a left fronto-parietal network, but only among a sub-group of participants with a high level of musical experience (>5years). These findings may indicate two processing-levels underlying the unfolding of common music emotionality; (1) a widely shared core-affective process that is confined to a limbic network and mediated by temporal regularities in music and (2) an experience based process that is rooted in a left fronto-parietal network that may involve functioning of the 'mirror-neuron system'. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study

    Directory of Open Access Journals (Sweden)

    Soha Saleh

    2017-01-01

    Full Text Available Mirror visual feedback (MVF is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical or opposite (mirror hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with

  6. Physiological mechanisms contributing to increased water-use efficiency in winter wheat under organic fertilization.

    Science.gov (United States)

    Wang, Linlin; Wang, Shiwen; Chen, Wei; Li, Hongbing; Deng, Xiping

    2017-01-01

    Improving the efficiency of resource utilization has received increasing research attention in recent years. In this study, we explored the potential physiological mechanisms underlying improved grain yield and water-use efficiency of winter wheat (Triticum aestivum L.) following organic fertilizer application. Two wheat cultivars, ChangHan58 (CH58) and XiNong9871 (XN9871), were grown under the same nitrogen (N) fertilizer rate (urea-N, CK; and manure plus urea-N, M) and under two watering regimes (WW, well-watered; and WS, water stress) imposed after anthesis. The M fertilizer treatment had a higher Pn and lower gs and Tr than CK under both water conditions, in particular, it significantly increased WRC and Ψw, and decreased EWLR and MDA under WS. Also, the M treatment increased post-anthesis N uptake by 81.4 and 16.4% under WS and WW, thus increasing post-anthesis photosynthetic capacity and delaying leaf senescence. Consequently, the M treatment increased post-anthesis DM accumulation under WS and WW by 51.5 and 29.6%, WUEB by 44.5 and 50.9%, grain number per plant by 11.5 and 12.2% and 1000-grain weight by 7.3 and 3.6%, respectively, compared with CK. The grain yield under M treatment increased by 23 and 15%, and water use efficiency (WUEg) by 25 and 23%, respectively. The increased WUE under organic fertilizer treatment was due to elevated photosynthesis and decreased Tr and gs. Our results suggest that the organic fertilizer treatment enabled plants to use water more efficiently under drought stress.

  7. Abnormal organization of white matter network in patients with no dementia after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Lin Shi

    Full Text Available Structural changes after ischemic stroke could affect information communication extensively in the brain network. It is likely that the defects in the white matter (WM network play a key role in information interchange. In this study, we used graph theoretical analysis to examine potential organization alteration in the WM network architecture derived from diffusion tensor images from subjects with no dementia and experienced stroke in the past 5.4-14.8 months (N = 47, Mini-Mental Screening Examination, MMSE range 18-30, compared with a normal control group with 44 age and gender-matched healthy volunteers (MMSE range 26-30. Region-wise connectivity was derived from fiber connection density of 90 different cortical and subcortical parcellations across the whole brain. Both normal controls and patients with chronic stroke exhibited efficient small-world properties in their WM structural networks. Compared with normal controls, topological efficiency was basically unaltered in the patients with chronic stroke, as reflected by unchanged local and global clustering coefficient, characteristic path length, and regional efficiency. No significant difference in hub distribution was found between normal control and patient groups. Patients with chronic stroke, however, were found to have reduced betweenness centrality and predominantly located in the orbitofrontal cortex, whereas increased betweenness centrality and vulnerability were observed in parietal-occipital cortex. The National Institutes of Health Stroke Scale (NIHSS score of patient is correlated with the betweenness centrality of right pallidum and local clustering coefficient of left superior occipital gyrus. Our findings suggest that patients with chronic stroke still exhibit efficient small-world organization and unaltered topological efficiency, with altered topology at orbitofrontal cortex and parietal-occipital cortex in the overall structural network. Findings from this study could

  8. Growth, Yield and Fruit Quality of Grapevines under Organic and Biodynamic Management.

    Directory of Open Access Journals (Sweden)

    Johanna Döring

    Full Text Available The main objective of this study was to determine growth, yield and fruit quality of grapevines under organic and biodynamic management in relation to integrated viticultural practices. Furthermore, the mechanisms for the observed changes in growth, yield and fruit quality were investigated by determining nutrient status, physiological performance of the plants and disease incidence on bunches in three consecutive growing seasons. A field trial (Vitis vinifera L. cv. Riesling was set up at Hochschule Geisenheim University, Germany. The integrated treatment was managed according to the code of good practice. Organic and biodynamic plots were managed according to Regulation (EC No 834/2007 and Regulation (EC No 889/2008 and according to ECOVIN- and Demeter-Standards, respectively. The growth and yield of the grapevines differed strongly among the different management systems, whereas fruit quality was not affected by the management system. The organic and the biodynamic treatments showed significantly lower growth and yield in comparison to the integrated treatment. The physiological performance was significantly lower in the organic and the biodynamic systems, which may account for differences in growth and cluster weight and might therefore induce lower yields of the respective treatments. Soil management and fertilization strategy could be responsible factors for these changes. Yields of the organic and the biodynamic treatments partially decreased due to higher disease incidence of downy mildew. The organic and the biodynamic plant protection strategies that exclude the use of synthetic fungicides are likely to induce higher disease incidence and might partially account for differences in the nutrient status of vines under organic and biodynamic management. Use of the biodynamic preparations had little influence on vine growth and yield. Due to the investigation of important parameters that induce changes especially in growth and yield of

  9. Serviceability Assessment for Cascading Failures in Water Distribution Network under Seismic Scenario

    Directory of Open Access Journals (Sweden)

    Qing Shuang

    2016-01-01

    Full Text Available The stability of water service is a hot point in industrial production, public safety, and academic research. The paper establishes a service evaluation model for the water distribution network (WDN. The serviceability is measured in three aspects: (1 the functionality of structural components under disaster environment; (2 the recognition of cascading failure process; and (3 the calculation of system reliability. The node and edge failures in WDN are interrelated under seismic excitations. The cascading failure process is provided with the balance of water supply and demand. The matrix-based system reliability (MSR method is used to represent the system events and calculate the nonfailure probability. An example is used to illustrate the proposed method. The cascading failure processes with different node failures are simulated. The serviceability is analyzed. The critical node can be identified. The result shows that the aged network has a greater influence on the system service under seismic scenario. The maintenance could improve the antidisaster ability of WDN. Priority should be given to controlling the time between the initial failure and the first secondary failure, for taking postdisaster emergency measures within this time period can largely cut down the spread of cascade effect in the whole WDN.

  10. Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization.

    Science.gov (United States)

    Westphal, Andrew J; Wang, Siliang; Rissman, Jesse

    2017-03-29

    Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity-a measure of network segregation-is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control

  11. [Seasonal dynamics of soil organic carbon and active organic carbon fractions in Calamagrostis angustifolia wetlands topsoil under different water conditions].

    Science.gov (United States)

    Hou, Cui-Cui; Song, Chang-Chun; Li, Ying-Chen; Guo, Yue-Dong

    2011-01-01

    The experiment was carried in Sanjiang Plain in the northeast of China during the growing season in 2009. Soil organic carbon (SOC), as well as the soil active organic carbon fractions in the 0-20 cm soil layer of Calamagrostis angustifolia wetland under different water conditions were on monthly observation. Based on the research and indoor analysis, the seasonal dynamics of light fractions of soil organic carbon (LFOC) and microbial biomass carbon (MBC) were analyzed. The results indicated that the SOC contents had significantly seasonal dynamics, and the hydrological circle had apparently driving effect on LFOC and MBC during the growing season, especially under the seasonal flooded condition. The freeze-thaw process reduced the SOC, LFOC, MBC contents, with the decreases of 74.53%, 80.93%, 83.09%, while both carbon contents of light and heavy fractions were reduced at the same time. The result also showed that the seasonal flooding condition increased the proportion of LFOC in topsoil, which was larger in marsh meadow (13.58%) than in wet meadow (11.96%), whilst the MBC in marsh meadow (1 397.21 mg x kg(-1)) was less than the latter (1 603.65 mg x kg(-1)), proving that the inundated environment inhibited the mineralization and decomposition of organic matter. But the microbial activity could be adaptive to the flooding condition. During the growing season the MBC soared to 1 829.21 mg x kg(-1) from 337.56 mg x kg(-1) in July, and the microbial quotient was 1.51 times higher than that in June, indicating the high microbial efficacy of soil organic matter. Meanwhile, there was a significant correlation between the contents of LFOC and SOC (r = 0.816), suggesting that higher LFOC content was favorable to the soil carbon accumulation. Moreover, in the seasonal flooded Calamagrostis angustifolia wetland the soil LFOC content was significantly correlated with MBC (r = 0.95), implying that the available carbon source had more severe restriction on the microbial

  12. Origin and evolution of the self-organizing cytoskeleton in the network of eukaryotic organelles.

    Science.gov (United States)

    Jékely, Gáspár

    2014-09-02

    The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing "active gel," the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

  13. Entomofauna associated to horticultural crops under organic and conventional practices in Cordoba, Argentina

    International Nuclear Information System (INIS)

    Zalazar, Laura; Salvo, Adriana

    2007-01-01

    Farming practices and the addition of chemical synthetic substances in conventional agroecosystems are detrimental mainly to natural enemies of phytophagous insects, diminishing the natural regulation of pest insects. On the other hand, in organic agriculture, biological processes and care of the environment are favoured, hence an increase in insect biodiversity is predicted in this type of systems. In this work, abundance, richness of insects and proportion of functional groups were compared through a single quantitative sampling of insects in horticultural crop fields, three under organic and three under conventional management practices. Insect species richness, total and for guilds (phytophagous and entomophagous insects) were significantly higher in organic orchards, and also was the abundance of entomophagous insects. Richness and abundance of all insect orders (with exception of Homoptera abundance), were higher in orchards under organic management, being significant the differences for richness of Coleoptera and richness and abundance of Hymenoptera. Similar tendencies were observed in data obtained through sweep net in weeds. These results suggest that organic practices increase the diversity of species, particularly that of natural enemies. (author)

  14. COMPONENT SUPPLY MODEL FOR REPAIR ACTIVITIES NETWORK UNDER CONDITIONS OF PROBABILISTIC INDEFINITENESS.

    Directory of Open Access Journals (Sweden)

    Victor Yurievich Stroganov

    2017-02-01

    Full Text Available This article contains the systematization of the major production functions of repair activities network and the list of planning and control functions, which are described in the form of business processes (BP. Simulation model for analysis of the delivery effectiveness of components under conditions of probabilistic uncertainty was proposed. It has been shown that a significant portion of the total number of business processes is represented by the management and planning of the parts and components movement. Questions of construction of experimental design techniques on the simulation model in the conditions of non-stationarity were considered.

  15. Investigating risk and robustness measures for supply chain network design under demand uncertainty

    DEFF Research Database (Denmark)

    Govindan, Kannan; Fattahi, Mohammad

    2017-01-01

    This paper addresses a multi-stage and multi-period supply chain network design problem in which multiple commodities should be produced through different subsequent levels of manufacturing processes. The problem is formulated as a two-stage stochastic program under stochastic and highly time......-variable demands. To deal with the stochastic demands, a Latin Hypercube Sampling method is applied to generate a fan of scenarios and then, a backward scenario reduction technique reduces the number of scenarios. Weighted mean-risk objectives by using different risk measures and minimax objective are examined...

  16. Seasonal Dynamics of Enzymatic Activities and Functional Diversity in Soils under Different Organic Management

    Science.gov (United States)

    Soil microbial activity and diversity fluctuate seasonally under annual organic amendment for improving soil quality. We investigated the effects of municipal compost (MC), poultry litter (PL), and cover crops of spring oats and red clover (RC) on soil enzyme activities, and soil bacterial community...

  17. Long-term changes in soil organic carbon and nitrogen under semiarid tillage and cropping practices

    Science.gov (United States)

    Understanding long-term changes in soil organic carbon (SOC) and total soil nitrogen (TSN) is important for evaluating C fluxes and optimizing N management. We evaluated long-term SOC and TSN changes under dryland rotations for historical stubble-mulch (HSM) and graded terrace (GT) plots on a clay l...

  18. Identifying gene coexpression networks underlying the dynamic regulation of wood-forming tissues in Populus under diverse environmental conditions.

    Science.gov (United States)

    Zinkgraf, Matthew; Liu, Lijun; Groover, Andrew; Filkov, Vladimir

    2017-06-01

    Trees modify wood formation through integration of environmental and developmental signals in complex but poorly defined transcriptional networks, allowing trees to produce woody tissues appropriate to diverse environmental conditions. In order to identify relationships among genes expressed during wood formation, we integrated data from new and publically available datasets in Populus. These datasets were generated from woody tissue and include transcriptome profiling, transcription factor binding, DNA accessibility and genome-wide association mapping experiments. Coexpression modules were calculated, each of which contains genes showing similar expression patterns across experimental conditions, genotypes and treatments. Conserved gene coexpression modules (four modules totaling 8398 genes) were identified that were highly preserved across diverse environmental conditions and genetic backgrounds. Functional annotations as well as correlations with specific experimental treatments associated individual conserved modules with distinct biological processes underlying wood formation, such as cell-wall biosynthesis, meristem development and epigenetic pathways. Module genes were also enriched for DNase I hypersensitivity footprints and binding from four transcription factors associated with wood formation. The conserved modules are excellent candidates for modeling core developmental pathways common to wood formation in diverse environments and genotypes, and serve as testbeds for hypothesis generation and testing for future studies. No claim to original US government works. New Phytologist © 2017 New Phytologist Trust.

  19. Organic carbon sequestration under selected land use in Padang city, West Sumatra, Indonesia

    Science.gov (United States)

    Yulnafatmawita; Yasin, S.

    2018-03-01

    Organic carbon is a potential element to build biomass as well as emitting CO2 to the atmosphere and promotes global warming. This research was aimed to calculate the sequestered Carbon (C) within a 1-m soil depth under selected land use from 6 different sites in Padang city, Indonesia. Disturbed and undisturbed soil samples were taken from several horizons until 100 cm depth at each location. Soil parameters observed were organic carbon (OC), bulk density (BD), and soil texture. The result showed that soil OC content tended to decrease by the depth at all land use types, except under rice field in Kurao-Nanggalo which extremely increased at >65 cm soil depth with the highest carbon stock. The soil organic carbon sequestration from the highest to the lowest according to land use and the location is in the following order mix garden- Kayu Aro > mix garden- Aie Pacah > Rangeland- Parak Laweh >seasonal farming- Teluk Sirih > rice field- Kampuang Jua.

  20. The role of bridging organizations in environmental management: examining social networks in working groups

    Directory of Open Access Journals (Sweden)

    Adam A. Kowalski

    2015-06-01

    Full Text Available The linkage of diverse sets of actors and knowledge systems across management levels and institutional boundaries often poses one of the greatest challenges in adaptive management of natural resources. Bridging organizations can facilitate interactions among actors in management settings by lowering the transaction costs of collaboration. The Center for Ocean Solutions (COS is an example of a bridging organization that is focused on linking actors within the ocean sciences and governance arena through the use of working groups. This research examines how network connections between group members affect working group functionality and, more specifically, whether cohesive network structures allow groups to more effectively achieve their goals and objectives. A mixed-methods approach, incorporating both qualitative and quantitative data collection and analysis methods, is employed to understand the structural characteristics of COS working groups. The study finds that cohesive network structures are not associated with increased working group functionality. Strong, centralized leadership is a better predictor of working group success in achieving goals and objectives.

  1. Emergence of small-world anatomical networks in self-organizing clustered neuronal cultures.

    Directory of Open Access Journals (Sweden)

    Daniel de Santos-Sierra

    Full Text Available In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations.

  2. The Ubiquitin Ligase CBLC Maintains the Network Organization of the Golgi Apparatus.

    Directory of Open Access Journals (Sweden)

    Wan Yin Lee

    Full Text Available The Golgi apparatus plays a pivotal role in the sorting and post-translational modifications of secreted and membrane proteins. In mammalian cells, the Golgi is organized in stacks of cisternae linked together to form a network with a ribbon shape. Regulation of Golgi ribbon formation is poorly understood. Here we find in an image-based RNAi screen that depletion of the ubiquitin-ligase CBLC induces Golgi fragmentation. Depletions of the close homologues CBL and CBLB do not induce any visible defects. In CBLC-depleted cells, Golgi stacks appear relatively unperturbed at both the light and electron microscopy levels, suggesting that CBLC controls mostly network organization. CBLC partially localizes on Golgi membranes and this localization is enhanced after activation of the SRC kinase. Inhibition of SRC reverts CBLC depletion effects, suggesting interplay between the two. CBLC's regulation of Golgi network requires its ubiquitin ligase activity. However, SRC levels are not significantly affected by CBLC, and CBLC knockdown does not phenocopy SRC activation, suggesting that CBLC's action at the Golgi is not direct downregulation of SRC. Altogether, our results demonstrate a role of CBLC in regulating Golgi ribbon by antagonizing the SRC tyrosine kinase.

  3. Lifelong learning of human actions with deep neural network self-organization.

    Science.gov (United States)

    Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

    2017-12-01

    Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  4. Phase transitions and self-organized criticality in networks of stochastic spiking neurons

    Science.gov (United States)

    Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C.; Stolfi, Jorge; Kinouchi, Osame

    2016-11-01

    Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

  5. Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

    Science.gov (United States)

    Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C; Stolfi, Jorge; Kinouchi, Osame

    2016-11-07

    Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

  6. Hypothalamus-Related Resting Brain Network Underlying Short-Term Acupuncture Treatment in Primary Hypertension

    Directory of Open Access Journals (Sweden)

    Hongyan Chen

    2013-01-01

    Full Text Available The present study attempted to explore modulated hypothalamus-seeded resting brain network underlying the cardiovascular system in primary hypertensive patients after short-term acupuncture treatment. Thirty right-handed patients (14 male were divided randomly into acupuncture and control groups. The acupuncture group received a continuous five-day acupuncture treatment and undertook three resting-state fMRI scans and 24-hour ambulatory blood pressure monitoring (ABPM as well as SF-36 questionnaires before, after, and one month after acupuncture treatment. The control group undertook fMRI scans and 24-hour ABPM. For verum acupuncture, average blood pressure (BP and heart rate (HR decreased after treatment but showed no statistical differences. There were no significant differences in BP and HR between the acupuncture and control groups. Notably, SF-36 indicated that bodily pain (P = 0.005 decreased and vitality (P = 0.036 increased after acupuncture compared to the baseline. The hypothalamus-related brain network showed increased functional connectivity with the medulla, brainstem, cerebellum, limbic system, thalamus, and frontal lobes. In conclusion, short-term acupuncture did not decrease BP significantly but appeared to improve body pain and vitality. Acupuncture may regulate the cardiovascular system through a complicated brain network from the cortical level, the hypothalamus, and the brainstem.

  7. Converging models of schizophrenia - Network alterations of prefrontal cortex underlying cognitive impairments

    Science.gov (United States)

    Sakurai, Takeshi; Gamo, Nao J; Hikida, Takatoshi; Kim, Sun-Hong; Murai, Toshiya; Tomoda, Toshifumi; Sawa, Akira

    2015-01-01

    The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal. PMID:26408506

  8. Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

    Directory of Open Access Journals (Sweden)

    Pei-Chen Lo

    2013-01-01

    Full Text Available This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph. Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y, the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording, in Chan meditation (stage M, and the unique Chakra-focusing practice (stage C. Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group.

  9. CytoViz: an artistic mapping of network measurements as living organisms in a VR application

    Science.gov (United States)

    López Silva, Brenda A.; Renambot, Luc

    2007-02-01

    CytoViz is an artistic, real-time information visualization driven by statistical information gathered during gigabit network transfers to the Scalable Adaptive Graphical Environment (SAGE) at various events. Data streams are mapped to cellular organisms defining their structure and behavior as autonomous agents. Network bandwidth drives the growth of each entity and the latency defines its physics-based independent movements. The collection of entity is bound within the 3D representation of the local venue. This visual and animated metaphor allows the public to experience the complexity of high-speed network streams that are used in the scientific community. Moreover, CytoViz displays the presence of discoverable Bluetooth devices carried by nearby persons. The concept is to generate an event-specific, real-time visualization that creates informational 3D patterns based on actual local presence. The observed Bluetooth traffic is put in opposition of the wide-area networking traffic by overlaying 2D animations on top of the 3D world. Each device is mapped to an animation fading over time while displaying the name of the detected device and its unique physical address. CytoViz was publicly presented at two major international conferences in 2005 (iGrid2005 in San Diego, CA and SC05 in Seattle, WA).

  10. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

  11. Emergent inequality and self-organized social classes in a network of power and frustration

    Science.gov (United States)

    Mahault, Benoit; Saxena, Avadh

    2017-01-01

    We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes. PMID:28212440

  12. Emergent inequality and self-organized social classes in a network of power and frustration.

    Science.gov (United States)

    Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano

    2017-01-01

    We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.

  13. A Self-Organizing Incremental Neural Network based on local distribution learning.

    Science.gov (United States)

    Xing, Youlu; Shi, Xiaofeng; Shen, Furao; Zhou, Ke; Zhao, Jinxi

    2016-12-01

    In this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines the advantages of incremental learning and matrix learning. It can automatically discover suitable nodes to fit the learning data in an incremental way without a priori knowledge such as the structure of the network. The nodes of the network store rich local information regarding the learning data. The adaptive vigilance parameter guarantees that LD-SOINN is able to add new nodes for new knowledge automatically and the number of nodes will not grow unlimitedly. While the learning process continues, nodes that are close to each other and have similar principal components are merged to obtain a concise local representation, which we call a relaxation data representation. A denoising process based on density is designed to reduce the influence of noise. Experiments show that the LD-SOINN performs well on both artificial and real-word data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Connecting Social Networks with Ecosystem Services for Watershed Governance: a Social-Ecological Network Perspective Highlights the Critical Role of Bridging Organizations

    Directory of Open Access Journals (Sweden)

    Kaitlyn J. Rathwell

    2012-06-01

    Full Text Available In many densely settled agricultural watersheds, water quality is a point of conflict between amenity and agricultural activities because of the varied demands and impacts on shared water resources. Successful governance of these watersheds requires coordination among different activities. Recent research has highlighted the role that social networks between management entities can play to facilitate cross-scale interaction in watershed governance. For example, bridging organizations can be positioned in social networks to bridge local initiatives done by single municipalities across whole watersheds. To better understand the role of social networks in social-ecological system dynamics, we combine a social network analysis of the water quality management networks held by local governments with a social-ecological analysis of variation in water management and ecosystem services across the Montérégie, an agricultural landscape near Montréal, Québec, Canada. We analyze municipal water management networks by using one-mode networks to represent direct collaboration between municipalities, and two-mode networks to capture how bridging organizations indirectly connect municipalities. We find that municipalities do not collaborate directly with one another but instead are connected via bridging organizations that span the water quality management network. We also discovered that more connected municipalities engaged in more water management activities. However, bridging organizations preferentially connected with municipalities that used more tourism related ecosystem services rather than those that used more agricultural ecosystem services. Many agricultural municipalities were relatively isolated, despite being the main producers of water quality problems. In combination, these findings suggest that further strengthening the water management network in the Montérégie will contribute to improving water quality in the region. However, such

  15. Alkaline degradation of organic materials contained in TRU wastes under repository conditions

    International Nuclear Information System (INIS)

    Otsuka, Yoshiki; Banba, Tsunetaka

    2007-09-01

    Alkaline degradation tests for 9 organic materials were conducted under the conditions of TRU waste disposal: anaerobic alkaline conditions. The tests were carried out at 90degC for 91 days. The sample materials for the tests were selected from the standpoint of constituent organic materials of TRU wastes. It has been found that cellulose and plastic solidified products are degraded relatively easily and that rubbers are difficult to degrade. It could be presumed that the alkaline degradation of organic materials occurs starting from the functional group in the material. Therefore, the degree of degradation difficulty is expected to be dependent on the kinds of functional group contained in the organic material. (author)

  16. From the Social to the Economic and Beyond? A Relational Approach to the Historical Development of Danish Organic Food Networks

    DEFF Research Database (Denmark)

    Kjeldsen, Chris; Ingemann, Jan Holm

    2009-01-01

    , using the historical development of organic food in Denmark as an example. From the 1970s and onwards, organic food networks in Denmark have evolved from being primarily a marginal social movement to becoming included in the market mainstream. The social and spatial settings for organic food networks...... in Denmark have thus been significantly altered. Using debates on the conventionalisation of organic food systems as the starting point, it is argued in this article that this development in Denmark can be interpreted from a relational perspective as an ongoing process of establishing organizational...

  17. Application of Set Covering Location Problem for Organizing the Public Postal Network

    Directory of Open Access Journals (Sweden)

    Dragana Šarac

    2016-08-01

    Full Text Available Most countries of the European Union ensure certain obligations (criteria which universal service providers must meet to ensure the realization of the universal service. These criteria vary from country to country, giving their own choice of an optimal model for the density of the postal network. Such postal network of the operator providing universal postal service must be organized so that post offices are accessible at the optimal distance from the user. This paper presents two different approaches. The first one is based on the population criteria determined in the previous study. The second one is new, a general method created to determine the minimum number of postal unit applications of Set Covering Location Problem. The authors apply both methods on real data collected from the Serbian municipalities and finally, compare the obtained results.

  18. Neural network system and methods for analysis of organic materials and structures using spectral data

    Science.gov (United States)

    Meyer, Bernd J.; Sellers, Jeffrey P.; Thomsen, Jan U.

    1993-01-01

    Apparatus and processes for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

  19. Laser fluorimetry of mixtures of polyatomic organic compounds using artificial neural networks

    International Nuclear Information System (INIS)

    Dolenko, S A; Gerdova, I V; Dolenko, T A; Fadeev, V V

    2001-01-01

    New possibilities of laser fluorimetry offered by the use of algorithms for solving inverse problems based on artificial neural networks are demonstrated. A two-component mixture of polyatomic organic compounds is analysed by three methods of laser fluorimetry: a direct analysis of the fluorescence band, the kinetic fluorimetry (when durations of the laser pulse and the detector gate pulse are comparable with the fluorescence lifetimes or exceed them), and the saturation fluorimetry. The numerical experiments showed that the use of artificial neural networks in these methods provides a high practical stability of the solution of inverse problems and ensures a high sensitivity and a high accuracy of determining the contribution of components to fluorescence and of measuring molecular photophysical parameters, which can be used for the identification of components. (laser applications and other topics in quantum electronics)

  20. Comparison between genetic algorithm and self organizing map to detect botnet network traffic

    Science.gov (United States)

    Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

    2017-11-01

    In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

  1. Implementation of self-organizing neural networks for visuo-motor control of an industrial robot.

    Science.gov (United States)

    Walter, J A; Schulten, K I

    1993-01-01

    The implementation of two neural network algorithms for visuo-motor control of an industrial robot (Puma 562) is reported. The first algorithm uses a vector quantization technique, the ;neural-gas' network, together with an error correction scheme based on a Widrow-Hoff-type learning rule. The second algorithm employs an extended self-organizing feature map algorithm. Based on visual information provided by two cameras, the robot learns to position its end effector without an external teacher. Within only 3000 training steps, the robot-camera system is capable of reducing the positioning error of the robot's end effector to approximately 0.1% of the linear dimension of the work space. By employing adaptive feedback the robot succeeds in compensating not only slow calibration drifts, but also sudden changes in its geometry. Hardware aspects of the robot-camera system are discussed.

  2. Coexistence of Stochastic Oscillations and Self-Organized Criticality in a Neuronal Network: Sandpile Model Application.

    Science.gov (United States)

    Saeedi, Alireza; Jannesari, Mostafa; Gharibzadeh, Shahriar; Bakouie, Fatemeh

    2018-04-01

    Self-organized criticality (SOC) and stochastic oscillations (SOs) are two theoretically contradictory phenomena that are suggested to coexist in the brain. Recently it has been shown that an accumulation-release process like sandpile dynamics can generate SOC and SOs simultaneously. We considered the effect of the network structure on this coexistence and showed that the sandpile dynamics on a small-world network can produce two power law regimes along with two groups of SOs-two peaks in the power spectrum of the generated signal simultaneously. We also showed that external stimuli in the sandpile dynamics do not affect the coexistence of SOC and SOs but increase the frequency of SOs, which is consistent with our knowledge of the brain.

  3. Neural network system and methods for analysis of organic materials and structures using spectral data

    Science.gov (United States)

    Meyer, B.J.; Sellers, J.P.; Thomsen, J.U.

    1993-06-08

    Apparatus and processes are described for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

  4. City leadership for health and sustainable development: the World Health Organization European Healthy Cities Network.

    Science.gov (United States)

    Tsouros, Agis

    2009-11-01

    This paper provides an overview of European Healthy Cities Network (EHCN) organized by the WHO Regional Office Europe. The focus is on the third of five phases covering the period 1998-2002. Fifty-six cities were members of the WHO-EHCN and over 1000 European cities were members of national networks. Association with WHO has given municipalities legitimacy to move into a domain often associated with health service. Equity and community participation are core values. City mayors provide political leadership. Intersectoral cooperation underpins a Healthy Cities approach. The WHO Regional Office for Europe supports WHO-EHCN, providing guidance and technical leadership. Cities' processes and structures are prerequisits for improvements in health and are central to the evaluation of Phase III of the WHO-EHCN.

  5. Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty.

    Science.gov (United States)

    Teng, Chih-Ching; Lu, Chi-Heng

    2016-10-01

    Despite the progressive development of the organic food sector in Taiwan, little is known about how consumers' consumption motives will influence organic food decision through various degrees of involvement and whether or not consumers with various degrees of uncertainty will vary in their intention to buy organic foods. The current study aims to examine the effect of consumption motives on behavioral intention related to organic food consumption under the mediating role of involvement as well as the moderating role of uncertainty. Research data were collected from organic food consumers in Taiwan via a questionnaire survey, eventually obtaining 457 valid questionnaires for analysis. This study tested the overall model fit and hypotheses through structural equation modeling method (SEM). The results show that consumer involvement significantly mediates the effects of health consciousness and ecological motives on organic food purchase intention, but not applied to food safety concern. Moreover, the moderating effect of uncertainty is statistical significance, indicating that the relationship between involvement and purchase intention becomes weaker in the condition of consumers with higher degree of uncertainty. Several implications and suggestions are also discussed for organic food providers and marketers. Copyright © 2016. Published by Elsevier Ltd.

  6. Basic Substances under EU Pesticide Regulation: An Opportunity for Organic Production?

    Directory of Open Access Journals (Sweden)

    Patrice A. Marchand

    2017-02-01

    Full Text Available Some of the active substances allowed in organic production are now approved as basic sub- stances under the EU plant protection products regulation. Previously, all organic farming permitted active substances were approved as conventional plant protection products. In accordance with the criteria of Article 23 of the EU regulation (EC No 1107/2009, basic substances are granted without maximum residue limits and have a good prospect for being included in Annex II of organic farming Regulation (EC 889/2008. In fact, most of them are already permitted in organic farming. At this stage, it seems desirable to organize applications in order to avoid duplications and to clarify strategy across Europe. This organization should be planned in order to identify corresponding knowledge and data from field experiments, and to further constitute the most crucial issues related to organic production. A work of this nature was initially supported by IFOAM-EU for lecithin, calcium hydroxide and Quassia extract. The Institut Technique de l’Agriculture Biologique (ITAB was previously engaged in a large-scale approval plan motivated by the continuous demand for the regularization of compounds/substances already in use and has a mandate for testing and approving new compatible substances. Thus, the horsetail extract (Equisetum arvense was the first approved basic substance and ITAB has obtained 11 of the 15 basic substances approved at the EU level.

  7. Greed and Fear in Network Reciprocity: Implications for Cooperation among Organizations

    Science.gov (United States)

    Kitts, James A.; Leal, Diego F.; Felps, Will; Jones, Thomas M.; Berman, Shawn L.

    2016-01-01

    Extensive interdisciplinary literatures have built on the seminal spatial dilemmas model, which depicts the evolution of cooperation on regular lattices, with strategies propagating locally by relative fitness. In this model agents may cooperate with neighbors, paying an individual cost to enhance their collective welfare, or they may exploit cooperative neighbors and diminish collective welfare. Recent research has extended the model in numerous ways, incorporating behavioral noise, implementing other network topologies or adaptive networks, and employing alternative dynamics of replication. Although the underlying dilemma arises from two distinct dimensions—the gains for exploiting cooperative partners (Greed) and the cost of cooperating with exploitative partners (Fear)–most work following from the spatial dilemmas model has argued or assumed that the dilemma can be represented with a single parameter: This research has typically examined Greed or Fear in isolation, or a composite such as the K-index of Cooperation or the ratio of the benefit to cost of cooperation. We challenge this claim on theoretical grounds—showing that embedding interaction in networks generally leads Greed and Fear to have divergent, interactive, and highly nonlinear effects on cooperation at the macro level, even when individuals respond identically to Greed and Fear. Using computational experiments, we characterize both dynamic local behavior and long run outcomes across regions of this space. We also simulate interventions to investigate changes of Greed and Fear over time, showing how model behavior changes asymmetrically as boundaries in payoff space are crossed, leading some interventions to have irreversible effects on cooperation. We then replicate our experiments on inter-organizational network data derived from links through shared directors among 2,400 large US corporations, thus demonstrating our findings for Greed and Fear on a naturally-occurring network. In closing

  8. Learning teams and networks: using information technology as a means of managing work process development in healthcare organizations.

    Science.gov (United States)

    Korhonen, Vesa; Paavilainen, Eija

    2002-01-01

    This article focuses on the introduction of team learning and shared knowledge creation using computer-based learning environments and teams as networks in the development of healthcare organizations. Using computer technology, care units can be considered learning teams and the hospital a network of those learning teams. Team learning requires that the healthcare workers' intellectual capital and personal competence be viewed as an important resource in developing the quality of action of the entire healthcare organization.

  9. Prospective estimation of organ dose in CT under tube current modulation

    International Nuclear Information System (INIS)

    Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Frush, Donald P.; Samei, Ehsan

    2015-01-01

    Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT exams under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI vol -normalized-organ dose coefficients (h organ ) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to

  10. Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

    Science.gov (United States)

    Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

    2009-01-01

    We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

  11. [ANMCO/SIC Consensus document: The heart failure network: organization of outpatient care].

    Science.gov (United States)

    Aspromonte, Nadia; Gulizia, Michele Massimo; Di Lenarda, Andrea; Mortara, Andrea; Battistoni, Ilaria; De Maria, Renata; Gabriele, Michele; Iacoviello, Massimo; Navazio, Alessandro; Pini, Daniela; Di Tano, Giuseppe; Marini, Marco; Ricci, Renato Pietro; Alunni, Gianfranco; Radini, Donatella; Metra, Marco; Romeo, Francesco

    2016-01-01

    Changing demographics and an increasing burden of multiple chronic comorbidities in western countries dictate refocusing of heart failure (HF) services from acute in-hospital care to better support the long inter-critical out-of-hospital phases of HF. The needs of the HF population are not adequately addressed by current HF outpatient services, as documented by differences in age, gender, comorbidities and recommended therapies between patients discharged for hospitalized HF and those followed up at HF clinics.The Working Group on Heart Failure of the Italian Association of Hospital Cardiologists (ANMCO) has drafted a consensus document for the organization of a national HF care network. The aims of this document are to describe tasks and requirements of the different health system points of contact for HF patients, and to define how diagnosis, management and care processes should be documented and shared among healthcare professionals. In this document, HF clinics are classified into three groups: 1) community HF clinics, devoted to the management of stable patients in strict liaison with primary care, regular re-evaluation of emerging clinical needs and prompt treatment of impending destabilizations, 2) hospital HF clinics, that target both new-onset and chronic HF patients for diagnostic assessment, treatment planning and early post-discharge follow-up. They act as main referral for medicine units and community clinics; 3) advanced HF clinics, directed at patients with severe disease or persistent clinical instability, candidates to advanced treatment options such as heart transplant or mechanical circulatory support. These different types of HF clinics are integrated in a dedicated network for the management of HF patients on a regional basis, according to geographic features. By sharing predefined protocols and communication systems, these HF networks integrate multiprofessional providers to ensure continuity of care. This consensus document is expected to

  12. Systems-level organization of non-alcoholic fatty liver disease progression network

    Directory of Open Access Journals (Sweden)

    K. Shubham

    2017-10-01

    Full Text Available Non-Alcoholic Fatty Liver Disease (NAFLD is a hepatic metabolic disorder that is commonly associated with sedentary lifestyle and high fat diets. NAFLD is prevalent in individuals with obesity, insulin resistance and Type 2 Diabetes (T2D. The clinical spectrum of NAFLD ranges from simple steatosis to Non-Alcoholic Steatohepatitis (NASH with fibrosis, which can progress to cirrhosis and hepatocellular carcinoma.The pathogenesis of NAFLD is complex, involving crosstalk between multiple organs, cell-types, and environmental and genetic factors. Dysfunction of White Adipose Tissue (WAT plays a central role in the development of NAFLD and other metabolic disorders. WAT is an active endocrine organ that regulates whole-body energy homeostasis, lipid metabolism, insulin sensitivity and food intake by secreting biologically active molecules (lipokines, adipokines and cytokines. WAT dynamically reacts to nutrient excess or deprivation by remodelling the number (called hyperplasia and/or size (called hypertrophy of adipocytes to store fat or supply nutrients to other tissues by lipolysis, respectively. Adipose tissue remodelling is also accompanied by changes in the composition or function of stromal vascular cells and ECM. The major objective of our study was to identify and characterize the metabolic and signaling modules associated with the progression of NAFLD in the VAT. We performed Weighted Gene Co-expression Network Analysis (WGCNA to organize microarray data obtained from the VAT of patients at different stages of NAFLD into functional modules. In order to obtain insights into the metabolism and its regulation at the genome scale, a co-expression network of metabolic genes in the Human Metabolic Network (HMR2 was constructed and compared with the co-expression network constructed based on all the varying genes. We also used the prior network information on adipocyte metabolism (GEM to verify and extract reporter metabolites. Our analysis revealed

  13. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Re-conceptualization of Knowledge Organization: Imperatives of Networked Resources and Digitization

    Directory of Open Access Journals (Sweden)

    Abdus Sattar Chaudhry

    2016-12-01

    Full Text Available Rethinking and re-conceptualization of knowledge organization has become necessary as a result of recent changes brought by digitization, networked resources, and interdisciplinary shifts. This paper calls for a review of curriculum and changes in teaching approaches to respond to these changes. The paper suggests expanding the scope of knowledge organization by adding new topics, and recommends placement of these topics in different courses (introductory or foundation courses, core or required courses, and electives or specialized courses for a balanced approach. The paper also proposes a change in the mindset about the target of these courses and recommends knowledge organization work be extended from institutions to individuals. It is also suggested that knowledge organization work responsibilities are broadened to involve authors, knowledge workers, and information users rather than restricting it only to trained information professionals. The paper highlights that the digital environment makes it necessary to change the context for teaching KO courses and goes beyond the collection of information resources and addresses personal information management needs as well. The paper concludes that fundamental changes tantamount to re-conceptualization of the area of knowledge organization, which is expected to open up new opportunities for information graduates aspiring to work in information environment beyond libraries.

  15. Structural Organization of the Laryngeal Motor Cortical Network and Its Implication for Evolution of Speech Production.

    Science.gov (United States)

    Kumar, Veena; Croxson, Paula L; Simonyan, Kristina

    2016-04-13

    The laryngeal motor cortex (LMC) is essential for the production of learned vocal behaviors because bilateral damage to this area renders humans unable to speak but has no apparent effect on innate vocalizations such as human laughing and crying or monkey calls. Several hypotheses have been put forward attempting to explain the evolutionary changes from monkeys to humans that potentially led to enhanced LMC functionality for finer motor control of speech production. These views, however, remain limited to the position of the larynx area within the motor cortex, as well as its connections with the phonatory brainstem regions responsible for the direct control of laryngeal muscles. Using probabilistic diffusion tractography in healthy humans and rhesus monkeys, we show that, whereas the LMC structural network is largely comparable in both species, the LMC establishes nearly 7-fold stronger connectivity with the somatosensory and inferior parietal cortices in humans than in macaques. These findings suggest that important "hard-wired" components of the human LMC network controlling the laryngeal component of speech motor output evolved from an already existing, similar network in nonhuman primates. However, the evolution of enhanced LMC-parietal connections likely allowed for more complex synchrony of higher-order sensorimotor coordination, proprioceptive and tactile feedback, and modulation of learned voice for speech production. The role of the primary motor cortex in the formation of a comprehensive network controlling speech and language has been long underestimated and poorly studied. Here, we provide comparative and quantitative evidence for the significance of this region in the control of a highly learned and uniquely human behavior: speech production. From the viewpoint of structural network organization, we discuss potential evolutionary advances of enhanced temporoparietal cortical connections with the laryngeal motor cortex in humans compared with nonhuman

  16. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

    Science.gov (United States)

    Moya, José M; Araujo, Alvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

    2009-01-01

    The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  17. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Javier Blesa

    2009-11-01

    Full Text Available The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps, in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  18. Self-organized emergence of multilayer structure and chimera states in dynamical networks with adaptive couplings

    Science.gov (United States)

    Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.

    2017-12-01

    We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.

  19. Investigation on chlorine-based sanitization under stabilized conditions in the presence of organic load.

    Science.gov (United States)

    Teng, Zi; Luo, Yaguang; Alborzi, Solmaz; Zhou, Bin; Chen, Lin; Zhang, Jinglin; Zhang, Boce; Millner, Patricia; Wang, Qin

    2018-02-02

    Chlorine, the most commonly used sanitizer for fresh produce washing, has constantly shown inferior sanitizing efficacy in the presence of organic load. Conventionally this is attributed indirectly to the rapid chlorine depletion by organics leading to fluctuating free chlorine (FC) contents. However, little is known on whether organic load affects the sanitization process directly at well-maintained FC levels. Hereby, a sustained chlorine decay approach was employed to study the inactivation of Escherichia coli O157:H7 under stabilized washing conditions. Chlorine solution was first incubated with organic load for up to 4h, modeling the chlorination in produce washing lines. The FC level was then stabilized at five targeted values for sanitization study. Our study showed decreased sanitizing efficacy as the organic load increased. At 5s residence time and pH6.5, a minimum of 0.5 and 7.5mg/L FC were needed to achieve a 5 log reduction at 0 and 900mg/L chemical oxygen demand (COD), respectively. The decrease was more pronounced at lower FC, higher COD, higher pH, and shorter residence time values. The organics-associated interference with FC measurement and disruption of chlorine/bacteria interaction, together with the chlorine demand of concentrated inoculum per se, collectively resulted in inadequate sanitization. Finally, our results were compared with existing studies conducted under dynamic conditions in the context of different experimental settings. This study provided a feasible method for studying the bacteria/sanitizer interaction while ruling out the confounding effect from fluctuating FC levels, and it indicated the direct, negative impact of organic load. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

    Science.gov (United States)

    Zhang, Guomei; Sun, Hao

    2016-12-16

    We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

  1. Physical attributes of ultisol of Brazil's northeastern semiarid under organic farming of wine grapes

    Directory of Open Access Journals (Sweden)

    Jardenia R. Feitosa

    2015-03-01

    Full Text Available The purpose of this study was to evaluate the effects of organic farming of wine grapes under physical and chemical characteristics of Ultisol Brazil's northeastern semiarid region. The samples of soil were collected from the row and interrow of the farming and from the fallow area, at the depths of 0.0-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.60 m. The samples were collected at six and twelve months after the culture implementation to evaluate the state of aggregation, bulk density and total soil porosity, flocculation index and organic matter contents, calcium, magnesium, and sodium. The results were submitted to statistical analysis. The adoption of organic farming contributed to the soil aggregation process. The bulk density and total soil porosity did not differ significantly between the evaluations, but were within the critical limits for sandy soils. The index flocculation did not have a great influence on the aggregates formation, being this process influenced by organic matter. The period of one year was considered short to obtain conclusive results in improving the soil quality by organic farming, since there are difficulties in tropical soils in promoting significant increases in organic matter content in short time.

  2. Physical attributes of Ultisol of Brazil's northeastern semiarid under organic farming of wine grapes.

    Science.gov (United States)

    Feitosa, Jardenia R; Mendes, Alessandra M S; Olszevski, Nelci; Cunha, Tony J F; Cortez, Jorge W; Giongo, Vanderlise

    2015-03-01

    The purpose of this study was to evaluate the effects of organic farming of wine grapes under physical and chemical characteristics of Ultisol Brazil's northeastern semiarid region. The samples of soil were collected from the row and interrow of the farming and from the fallow area, at the depths of 0.0-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.60 m. The samples were collected at six and twelve months after the culture implementation to evaluate the state of aggregation, bulk density and total soil porosity, flocculation index and organic matter contents, calcium, magnesium, and sodium. The results were submitted to statistical analysis. The adoption of organic farming contributed to the soil aggregation process. The bulk density and total soil porosity did not differ significantly between the evaluations, but were within the critical limits for sandy soils. The index flocculation did not have a great influence on the aggregates formation, being this process influenced by organic matter. The period of one year was considered short to obtain conclusive results in improving the soil quality by organic farming, since there are difficulties in tropical soils in promoting significant increases in organic matter content in short time.

  3. Cropland versus Gariga schrubland on soil organic carbon storage under Mediterranen climatic condition of Sicily

    Science.gov (United States)

    Novara, A.; Gristina, L.; Santoro, A.; Poma, I.

    2009-04-01

    Soil organic carbon (SOC) pool is the largest among the terrestrial pool and it plays a key role to mitigate climate change. The restoration of SOC pool represents a potential sink for atmospheric CO2. Land use is one of the most important factors controlling organic carbon content. The main land uses throughout the Mediterranean are croplands (olive, wheat and vineyards) and scrublands. The land abandonment or the reclamation of land is changing the cover of scrubland and cropland. This will change the carbon cycle. The aim of this work is determining the direction and magnitude of soil organic change associated with land use change under Mediterranean Climatic Conditions. Using both historic record and land cover crop maps we estimated the effect of land cover change on the stock carbon from 1972 to 2008 in Sicily. A system of paired plots was established on Mollic Gypsiric cambisol and Gypsiric cambisol on agriculture and rangeland land uses. The study sites were selected at the natural reserve "Grotta di S. Ninfa", in the West of Sicily. Soil samples (24) were taken at 20 and 40 cm depth, air dried and sieved at 2 mm. Dry aggregate size fractions selected were >1000 µm, 1000-500 µm, 500-250 µm, 250-63 µm, 63-25 µm and <25 µm. The results show that gariga increase the organic matter in soil, mainly on the organic horizon. Key worlds: Land use change, Soil organic Carbon , Mediterranean, aggregates, gariga, cropland.

  4. Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

    Energy Technology Data Exchange (ETDEWEB)

    Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders; Blankinship, Joseph; Bond-Lamberty, Benjamin; Lawrence, Corey; Loisel, Julie; Malhotra, Avni; Jackson, Robert B.; Ogle, S. M.; Phillips, Claire; Ryals, Rebecca; Todd-Brown, Katherine EO; Vargas, Rodrigo; Vergara, Sintana; Cotrufo, Francesca; Keiluweit, M.; Heckman, Katherine; Crow, Susan; Silver, Whendee; Delonge, Marcia; Nave, Lucas

    2017-10-05

    Over 75% of soil organic carbon (C) in the upper meter of earth’s terrestrial surface has been subjected to cropping, grazing, forestry, or urbanization. As a result, terrestrial C cycling cannot be studied out of land use context. Meanwhile, amendments by soil organic matter demonstrate reliable methodologies to restore and improve soils to a more productive state, therefore soil health and productivity cannot be understood without reference to soil C. Measurements for detecting changes in soil C are needed to constrain and monitor best practices and must reflect processes of C stabilization and destabilization over various timescales, soil types, and spatial scales in order to quantify C sequestration at regional to global scales. We have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil carbon and its management for sustained production and climate regulation.

  5. Networks and spatial patterns of extremist organizations in North and West Africa

    DEFF Research Database (Denmark)

    Walther, Olivier; Leuprecht, Christian; Skillicorn, David

    2018-01-01

    and stability” (MaliActu 2016). The much-debated letter, which arrived one month before Ansar Dine attacked a UN convoy in the north of the country (RFI 2016), is the latest development in a tortuous military career for ag Ghaly, who, since the 1990s, has been a foreign fighter for the late Colonel Gaddafi...... of quantitative studies conducted across the world have shown that internal fragmentation, conflicts and alliances between armed groups played a crucial role in explaining the onset and diffusion of internecine violence (Bakke et al. 2012; Cunningham et al. 2012) and the often elusive quest for peace settlements...... of ensuring border integrity through border patrols and law enforcement. The chapter proceeds as follows. The second section reviews the literature on the social and spatial organization of state and non-state organizations, paying particular attention to the role of networks and national borders. The third...

  6. Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

    Energy Technology Data Exchange (ETDEWEB)

    Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders; Blankinship, Joseph; Bond-Lamberty, Benjamin; Lawrence, Corey; Loisel, Julie; Malhotra, Avni; Jackson, Robert B.; Ogle, S.M.; Phillips, Claire; Ryals, Rebecca; Todd-Brown, Katherine EO; Vargas, Rodrigo; Vergara, Sintana; Cotrufo, Francesca; Keiluweit, M.; Heckman, Katherine; Crow, Susan; Silver, Whendee; Delonge, Marcia; Nave, Lucas

    2018-02-01

    Over 75% of soil organic carbon (C) in the upper meter of earth’s terrestrial surface has been subjected to cropping, grazing, forestry, or urbanization. As a result, terrestrial C cycling cannot be studied out of land use context. Meanwhile, amendments by soil organic matter demonstrate reliable methodologies to restore and improve soils to a more productive state, therefore soil health and productivity cannot be understood without reference to soil C. Measurements for detecting changes in soil C are needed to constrain and monitor best practices and must reflect processes of C stabilization and destabilization over various timescales, soil types, and spatial scales in order to quantify C sequestration at regional to global scales. We have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil carbon and its management for sustained production and climate regulation.

  7. Neurobiologically Realistic Determinants of Self-Organized Criticality in Networks of Spiking Neurons

    Science.gov (United States)

    Rubinov, Mikail; Sporns, Olaf; Thivierge, Jean-Philippe; Breakspear, Michael

    2011-01-01

    Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches) and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect their importance for

  8. Immune Organs and Haemopoietic System Under Modelling of the Mission Factors

    Science.gov (United States)

    Sapin, M. R.; Grigoriev, A. I.; Erofeeva, L. M.; Grigorenko, D. E.; Fedorenko, B. S.

    1997-07-01

    Literary and experimental data on the character of changes in immune organs and lymphoid tissue of respiratory system and digestive system in laboratory animals during the mission factors model are given. Inhibition of reproductive function in bone marrow, thymus and spleen under irradiation of gamma-rays and accelerated carbon ions, tensity of immune response in the lymphoid structures of larynx, trachea and bronchi under the influence of acetaldehyde vapors and decrease of lymphoid tissue square on histological series in spleen and small intestine with an increase of concentration of microbial bodies in the drinking water were estimated.

  9. Evaluating the connectivity of a protected areas' network under the prism of global change: the efficiency of the European Natura 2000 network for four birds of prey.

    Science.gov (United States)

    Mazaris, Antonios D; Papanikolaou, Alexandra D; Barbet-Massin, Morgane; Kallimanis, Athanasios S; Jiguet, Frédéric; Schmeller, Dirk S; Pantis, John D

    2013-01-01

    Climate and land use changes are major threats to biodiversity. To preserve biodiversity, networks of protected areas have been established worldwide, like the Natura 2000 network across the European Union (EU). Currently, this reserve network consists of more than 26000 sites covering more than 17% of EU terrestrial territory. Its efficiency to mitigate the detrimental effects of land use and climate change remains an open research question. Here, we examined the potential current and future geographical ranges of four birds of prey under scenarios of both land use and climate changes. By using graph theory, we examined how the current Natura 2000 network will perform in regard to the conservation of these species. This approach determines the importance of a site in regard to the total network and its connectivity. We found that sites becoming unsuitable due to climate change are not a random sample of the network, but are less connected and contribute less to the overall connectivity than the average site and thus their loss does not disrupt the full network. Hence, the connectivity of the remaining network changed only slightly from present day conditions. Our findings highlight the need to establish species-specific management plans with flexible conservation strategies ensuring protection under potential future range expansions. Aquila pomarina is predicted to disappear from the southern part of its range and to become restricted to northeastern Europe. Gyps fulvus, Aquila chrysaetos, and Neophron percnopterus are predicted to locally lose some suitable sites; hence, some isolated small populations may become extinct. However, their geographical range and metapopulation structure will remain relatively unaffected throughout Europe. These species would benefit more from an improved habitat quality and management of the existing network of protected areas than from increased connectivity or assisted migration.

  10. Microbial diversity and organic matter fractions under two arid soils in Algerian Sahara

    Science.gov (United States)

    Karabi, Mokhtar; Hamdi, Aissa Baelhadj; Zenkhri, Salah

    2016-07-01

    The Algerian Sahara is characterized by a heterogeneity of edaphic conditions and climatic dissimilarities; however, information on biological indicators of arid soils is weakly documented in this area. The researchers who have studied the biological activities of the soils of the arid regions have underlined their low organic matter content, particularly their very low rates of organic nitrogen; a low humification because seriously inhibited by a significant mineralization. The objective of the current work is to study the microbial biomass densities and organic matter fractions for different types of soil, under two arid soil in Algerian Sahara. The experiment was conducted in an alluvial soil in traditional palm grove of Guerrara, and in a saline soil in experimental field of university of Ouargla. Composite soil samples (10 subsamples each) were collected aseptically at 0-20 cm depth on two diagonal transects drawn over an area of 12 ha. The following germs densities were determined: Bacteria, Fungi and Actinomycetes. The soil organic matter fractions, the textural fractions, chemical attributes (organic C, total N, total limestone and gypsum) were also determined. The microbial groups count on both soils reveals that the bacterianmicroflora present a numerical superiority followed by the actinomycetes and finally fungi. The micro-organisms densities except fungal density, showed a prevalence of the bacterianmicroflora, and actinomycetes in alluvial soil compared to saline soil. Fractionation of soil organic matter show that all fractions are better represented in alluvial soil except non-extractable organic carbon (NEOC) which are better represented in saline soil. This confirms that alluvial soil has a relatively large biological activity than saline soil and that humification process is relatively pronounced by comparing it with the saline soil, which tends to contain little polycondenseshumic compounds.

  11. Soil Water Content Sensor Response to Organic Matter Content under Laboratory Conditions

    Science.gov (United States)

    Fares, Ali; Awal, Ripendra; Bayabil, Haimanote K.

    2016-01-01

    Studies show that the performance of soil water content monitoring (SWCM) sensors is affected by soil physical and chemical properties. However, the effect of organic matter on SWCM sensor responses remains less understood. Therefore, the objectives of this study are to (i) assess the effect of organic matter on the accuracy and precision of SWCM sensors using a commercially available soil water content monitoring sensor; and (ii) account for the organic matter effect on the sensor’s accuracy. Sand columns with seven rates of oven-dried sawdust (2%, 4%, 6%, 8%, 10%, 12% and 18% v/v, used as an organic matter amendment), thoroughly mixed with quartz sand, and a control without sawdust were prepared by packing quartz sand in two-liter glass containers. Sand was purposely chosen because of the absence of any organic matter or salinity, and also because sand has a relatively low cation exchange capacity that will not interfere with the treatment effect of the current work. Sensor readings (raw counts) were monitored at seven water content levels (0, 0.02, 0.04, 0.08, 0.12, 0.18, 0.24, and 0.30 cm3 cm−3) by uniformly adding the corresponding volumes of deionized water in addition to the oven-dry one. Sensor readings were significantly (p Sensor readings were strongly correlated with the organic matter level (R2 = 0.92). In addition, the default calibration equation underestimated the water content readings at the lower water content range (0.05 cm3 cm−3). A new polynomial calibration equation that uses raw count and organic matter content as covariates improved the accuracy of the sensor (RMSE = 0.01 cm3 cm−3). Overall, findings of this study highlight the need to account for the effect of soil organic matter content to improve the accuracy and precision of the tested sensor under different soils and environmental conditions. PMID:27527185

  12. Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks.

    Science.gov (United States)

    Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Hwang, I-Shyan

    2017-12-19

    The K -coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K -covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K -coverage Group Scheduling (PSKGS) and Self-Organized K -coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.

  13. Sustainability of Constructed Wetland under the Impact of Aquatic Organisms Overloading

    Directory of Open Access Journals (Sweden)

    Shih-Chieh Chen

    2017-05-01

    Full Text Available Environmental impacts, such as earthquakes, chemical pollution and anthropogenic factors can affect the stability and sustainability of an ecosystem. In this study, a long-term (3.7 years investigation experiment was conducted to estimate the sustainability of a constructed wetland (CW under the impact of aquatic organisms overloading. The situation of aquatic organisms overloading in this study meant that around 27,000 kg of fishes had to be moved and accommodated in a 4 ha water area of wetland for six months. Experimental results indicated that the pH value of CW water was slightly acidic and the Dissolved Oxygen (DO level decreased under the impact. On the other hand, the levels of Electrical Conductivity (EC, Suspended Solids (SS, Chemical Oxygen Demand (COD, and Total Kjeldahl Nitrogen (TKN of CW water were increased under the impact. The pathogen analysis revealed that total coliforms, Salmonella spp., Enterococcus spp., and Escherichia coli, in the wetland water increased under the impact. The analyzed factors of water quality and amount of pathogens were all returned to their original statuses soon after the impact ended. Eventually, the results of microbial community structure analysis showed that overloading of aquatic organisms slightly increased the specific richness (R of wetland bacteria, whereas higher structural biodiversity (H of CW could stabilize the whole microbial community and prevent the pathogens or other bacteria from increasing to become the dominant strains. These results were novel and could be possible to conclude that a CW environment could not only stabilize the water quality and amount of pathogens resulting from the impact of aquatic organisms overloading, but also they could stabilize the microbial community structures, allowing the biogeochemical cycles of the CW to function. They could provide the useful information for wetland sustainability.

  14. Clay mineral formation under oxidized conditions and implications for paleoenvironments and organic preservation on Mars

    Energy Technology Data Exchange (ETDEWEB)

    Gainey, Seth R.; Hausrath, Elisabeth M.; Adcock, Christopher T.; Tschauner, Oliver; Hurowitz, Joel A.; Ehlmann, Bethany L.; Xiao, Yuming; Bartlett, Courtney L. (CIW); (UNLV); (CIT); (SBU)

    2017-11-01

    Clay mineral-bearing locations have been targeted for martian exploration as potentially habitable environments and as possible repositories for the preservation of organic matter. Although organic matter has been detected at Gale Crater, Mars, its concentrations are lower than expected from meteoritic and indigenous igneous and hydrothermal reduced carbon. We conducted synthesis experiments motivated by the hypothesis that some clay mineral formation may have occurred under oxidized conditions conducive to the destruction of organics. Previous work has suggested that anoxic and/or reducing conditions are needed to synthesize the Fe-rich clay mineral nontronite at low temperatures. In contrast, our experiments demonstrated the rapid formation of Fe-rich clay minerals of variable crystallinity from aqueous Fe3+ with small amounts of aqueous Mg2+. Our results suggest that Fe-rich clay minerals such as nontronite can form rapidly under oxidized conditions, which could help explain low concentrations of organics within some smectite-containing rocks or sediments on Mars.

  15. Abiotic synthesis of organic compounds from carbon disulfide under hydrothermal conditions.

    Science.gov (United States)

    Rushdi, Ahmed I; Simoneit, Bernd R T

    2005-12-01

    Abiotic formation of organic compounds under hydrothermal conditions is of interest to bio, geo-, and cosmochemists. Oceanic sulfur-rich hydrothermal systems have been proposed as settings for the abiotic synthesis of organic compounds. Carbon disulfide is a common component of magmatic and hot spring gases, and is present in marine and terrestrial hydrothermal systems. Thus, its reactivity should be considered as another carbon source in addition to carbon dioxide in reductive aqueous thermosynthesis. We have examined the formation of organic compounds in aqueous solutions of carbon disulfide and oxalic acid at 175 degrees C for 5 and 72 h. The synthesis products from carbon disulfide in acidic aqueous solutions yielded a series of organic sulfur compounds. The major compounds after 5 h of reaction included dimethyl polysulfides (54.5%), methyl perthioacetate (27.6%), dimethyl trithiocarbonate (6.8%), trithianes (2.7%), hexathiepane (1.4%), trithiolanes (0.8%), and trithiacycloheptanes (0.3%). The main compounds after 72 h of reaction consisted of trithiacycloheptanes (39.4%), pentathiepane (11.6%), tetrathiocyclooctanes (11.5%), trithiolanes (10.6%), tetrathianes (4.4%), trithianes (1.2%), dimethyl trisulfide (1.1%), and numerous minor compounds. It is concluded that the abiotic formation of aliphatic straight-chain and cyclic polysulfides is possible under hydrothermal conditions and warrants further studies.

  16. Breast cancer publication network: profile of co-authorship and co-organization.

    Science.gov (United States)

    Biglu, Mohammad-Hossein; Abotalebi, Parvaneh; Ghavami, Mostafa

    2016-01-01

    Introduction: Breast cancer is one of the highest reasons of deaths for people in the world. The objective of current study is to analyze and visualize the trend of global scientific activities in the field of breast cancer during a period of 10 years through 2006-2015. Methods: The current study was performed by utilizing the scientometrics analysis and mapping the co-authorship and co-organization networks. The Web of Science Core Collection (WoS-CC)database was used to extract all papers indexed as a topic of breast cancer through 2006 to 2015. Research productivity was measured through analysis several parameters, including: the number and time course of publications, the journal and language of publications, the frequency and type of publications, as well as top 20 active sub-categories together with country contribution. The extracted data were transferred into the Excel charts and plotted as diagrams. The Science of Science (Sci2) and CiteSpace softwares were used as tools for mapping the co-authorship and co-organization networks of the published papers. Results: Analysis of data indicated that the number of publications in the field of breast cancer has linearly increased and correlated with the time-course of the study. The number of publication indexed in WoS-CC in 2015 was two times greater than that of 2006, which reached from 15 229 documents in 2006 to 30 667 documents in 2015. English Language accounted for 98% of total publications as the most dominant language. The vast majority of publications' type was in the form of original journal articles (64.7%). Based on Bradford scatterings law, the journal of "Cancer Research" was the most productive journal among the core journals, while the USA, China, and England were the most prolific countries in the field. The co-organization network indicated the dominant role of Harvard University in the field. Conclusion: The integrity of network indicated that scientists in the field of breast cancer

  17. Crystal chemistry of uranyl carboxylate coordination networks obtained in the presence of organic amine molecules

    Energy Technology Data Exchange (ETDEWEB)

    Mihalcea, Ionut; Henry, Natacha; Loiseau, Thierry [Unite de Catalyse et Chimie du Solide (UCCS) - UMR CNRS 8181, Universite de Lille Nord de France, USTL-ENSCL, Villeneuve d' Ascq (France)

    2014-03-15

    Three uranyl isophthalates (1,3-bdc) and two uranyl pyromellitates (btec) of coordination-polymer type were hydrothermally synthesized (200 C for 24 h) in the presence of different amine-based molecules [1,3-diaminopropane (dap) or dimethylamine (dma) originating from the in situ decomposition of N,N-dimethylformamide]. (UO{sub 2}){sub 2}(OH){sub 2}(H{sub 2}O)(1,3-bdc).H{sub 2}O (1) is composed of inorganic tetranuclear cores, which are linked to each other through the isophthalato ligand to generate infinite neutral ribbons, which are intercalated by free H{sub 2}O molecules. The compounds (UO{sub 2}){sub 1.5}(H{sub 2}O)(1,3-bdc){sub 2}.0.5H{sub 2}dap.1.5H{sub 2}O (2) and UO{sub 2}(1,3-bdc){sub 1.5}.0.5H{sub 2}dap.2H{sub 2}O (3) consist of discrete uranyl-centered hexagonal bipyramids connected to each other by a ditopic linker to form a single-layer network for 2 or a double-layer network for 3. The protonated diamine molecules are located between the uranyl-organic sheets and balance the negative charge of the layered sub-networks. The phase (UO{sub 2}){sub 2}O(btec).2Hdma.H{sub 2}O (4) presents a 2D structure built up from tetranuclear units, which consist of two central sevenfold coordinated uranium centers and two peripheral eightfold coordinated uranium centers. The connection of the resulting tetramers through the pyromellitate molecules generates an anionic layerlike structure, in which the protonated dimethylammonium species are inserted. The compound UO{sub 2}(btec).2Hdma (5) is also a lamellar coordination polymer, which contains isolated eightfold coordinated uranium cations linked through pyromellitate molecules and intercalated by protonated dimethylammonium species. In both phases 4 and 5, the btec linker has non-bonded carboxyl oxygen atoms, which preferentially interact with the protonated amine molecules through a hydrogen-bond network. The different illustrations show the structural diversity of uranyl-organic coordination polymers with organic

  18. Mineral Nutritional Yield and Nutrient Density of Locally Adapted Wheat Genotypes under Organic Production

    Directory of Open Access Journals (Sweden)

    Sergio Daniel Moreira-Ascarrunz

    2016-12-01

    Full Text Available The aim of the present investigation was to investigate the nutritional yield, nutrient density, stability, and adaptability of organically produced wheat for sustainable and nutritional high value food production. This study evaluated the nutritional yield of four minerals (Fe, Zn, Cu, and Mg in 19 wheat genotypes, selected as being locally adapted under organic agriculture conditions. The new metric of nutritional yield was calculated for each genotype and they were evaluated for stability using the Additive Main effects and Multiplicative Interaction (AMMI stability analysis and for genotypic value, stability, and adaptability using the Best Linear Unbiased Prediction (BLUP procedure. The results indicated that there were genotypes suitable for production under organic agriculture conditions with satisfactory yields (>4000 kg·ha−1. Furthermore, these genotypes showed high nutritional yield and nutrient density for the four minerals studied. Additionally, since these genotypes were stable and adaptable over three environmentally different years, they were designated “balanced genotypes” for the four minerals and for the aforementioned characteristics. Selection and breeding of such “balanced genotypes” may offer an alternative to producing nutritious food under low-input agriculture conditions. Furthermore, the type of evaluation presented here may also be of interest for implementation in research conducted in developing countries, following the objectives of producing enough nutrients for a growing population.

  19. ASSESSMENT OF REQUIREMENT OF THE POPULATION IN THE ORGAN TRANSPLANTATION, THE DONOR RESOURCE AND PLANNING OF THE EFFECTIVE NETWORK OF THE MEDICAL ORGANIZATIONS (THE CENTERS OF TRANSPLANTATION

    Directory of Open Access Journals (Sweden)

    S. V. Gautier

    2013-01-01

    Full Text Available Aim. To estimate the requirement of the population of the Russian Federation for an organ transplantation and donor resource, to offer approach to planning of an effective network of the medical organizations (the centers of transplantation. Materials and methods. The analysis and comparison of statistical data on population, number of the patients receiving a dialysis, data about medical care on an organ transplantation in Russia and foreign countries is made. Results. On the basis of what the assessment of requirement of the population of the Russian Federation in an organ transplantation and donor resource is carried out, approach to planning of an effective network of the medical organizations (the centers of transplantation and scenarios of development of organ do- nation and transplantation in Russia is offered. Conclusion. To provide the population of the Russian Federation with medical care on an organ transplantation according to real requirement and donor resource, in each region of the Russian Federation have to be organized deceased organ donation and transplantation of a cadaveric kidney. But the transplantation of extrarenal organs is better to develop in the federal centers of hi-tech medical care with donor providing from territories of adjacent regions. 

  20. Computational modeling of neural plasticity for self-organization of neural networks.

    Science.gov (United States)

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.