WorldWideScience

Sample records for underlying network organization

  1. Dopamine D1 signaling organizes network dynamics underlying working memory.

    Science.gov (United States)

    Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

    2016-06-01

    Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

  2. Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network

    Science.gov (United States)

    Tian, Wenliang; Meng, Fandi; Liu, Li; Li, Ying; Wang, Fuhui

    2017-01-01

    A concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus |Z|) are utilized as the parameters of the network. The average accuracies of the predicted service property and immersion time by the established network are 98.6% and 84.8%, respectively. The combination of accelerated test and prediction method by BP-ANN is promising to evaluate and predict coating property used in deep sea. PMID:28094340

  3. Virtual Organizations: Beyond Network Organization

    Directory of Open Access Journals (Sweden)

    Liviu Gabriel CRETU

    2006-01-01

    Full Text Available One of the most used buzz-words in (e-business literature of the last decade is virtual organization. The term "virtual" can be identified in all sorts of combinations regarding the business world. From virtual products to virtual processes or virtual teams, everything that is “touched” by the computer’s processing power instantly becomes virtual. Moreover, most of the literature treats virtual and network organizations as being synonyms. This paper aims to draw a much more distinctive line between the two concepts. Providing a more coherent description of what virtual organization might be is also one of our intentions.

  4. 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.

  5. 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

  6. Exploring network organization in practice

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    Constructing a network organization for global R&D is presented as a common sense practice in existing literature. However, there are still queries about the network organization, such as the persistence of hierarchies which make a network organization merely a “bureaucracy-lite” organization....... Furthermore, in practice, we rarely see radical organizational change towards a network organization that adopts an internal market. The co-existence of market, hierarchy and network triggered research interest. A multiple case study of three transnational corporations’ global R&D organization shows...... 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...

  7. Revisiting Network Organization in Practice

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    of networks in a network organization, which are internal market, IT networks, informal and social networks, global R&D project networks, global R&D specialists’ network, and alliances with external partners. Though the case TNCs are network-based, hierarchies remain to be an important part...... 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...

  8. 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, the r...

  9. Organization of complex networks

    Science.gov (United States)

    Kitsak, Maksim

    Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how

  10. Organ trade using social networks

    OpenAIRE

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

    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 Febru...

  11. Artificial neural network modelling for organic and total nitrogen removal of aerobic granulation under steady-state condition.

    Science.gov (United States)

    Gong, H; Pishgar, R; Tay, J H

    2018-04-27

    Aerobic granulation is a recent technology with high level of complexity and sensitivity to environmental and operational conditions. Artificial neural networks (ANNs), computational tools capable of describing complex non-linear systems, are the best fit to simulate aerobic granular bioreactors. In this study, two feedforward backpropagation ANN models were developed to predict chemical oxygen demand (Model I) and total nitrogen removal efficiencies (Model II) of aerobic granulation technology under steady-state condition. Fundamentals of ANN models and the steps to create them were briefly reviewed. The models were respectively fed with 205 and 136 data points collected from laboratory-, pilot-, and full-scale studies on aerobic granulation technology reported in the literature. Initially, 60%, 20%, and 20%, and 80%, 10%, and 10% of the points in the corresponding datasets were randomly chosen and used for training, testing, and validation of Model I, and Model II, respectively. Overall coefficient of determination (R 2 ) value and mean squared error (MSE) of the two models were initially 0.49 and 15.5, and 0.37 and 408, respectively. To improve the model performance, two data division methods were used. While one method is generic and potentially applicable to other fields, the other can only be applied to modelling the performance of aerobic granular reactors. R 2 value and MSE were improved to 0.90 and 2.54, and 0.81 and 121.56, respectively, after applying the new data division methods. The results demonstrated that ANN-based models were capable simulation approach to predict a complicated process like aerobic granulation.

  12. 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.

  13. 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. PMID:26555073

  14. Interspecific Competition Underlying Mutualistic Networks

    Science.gov (United States)

    Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

    2012-03-01

    Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

  15. Self-organization, Networks, Future

    Directory of Open Access Journals (Sweden)

    T. S. Akhromeyeva

    2013-01-01

    Full Text Available This paper presents an analytical review of a conference on the great scientist, a brilliant professor, an outstanding educator Sergei Kapitsa, held in November 2012. In the focus of this forum were problems of self-organization and a paradigm of network structures. The use of networks in the context of national defense, economics, management of mass consciousness was discussed. The analysis of neural networks in technical systems, the structure of the brain, as well as in the space of knowledge, information, and behavioral strategies plays an important role. One of the conference purposes was to an online organize community in Russia and to identify the most promising directions in this field. Some of them are presented in this paper.

  16. 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.

  17. 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.

  18. Simulations of biopolymer networks under shear

    NARCIS (Netherlands)

    Huisman, Elisabeth Margaretha

    2011-01-01

    In this thesis we present a new method to simulate realistic three-dimensional networks of biopolymers under shear. These biopolymer networks are important for the structural functions of cells and tissues. We use the method to analyze these networks under shear, and consider the elastic modulus,

  19. 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...

  20. 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.

  1. 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 ...

  2. Credal Networks under Maximum Entropy

    OpenAIRE

    Lukasiewicz, Thomas

    2013-01-01

    We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. ...

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

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    -tech industry. Besides interfirm networks, some organizational researchers are interested in the internal network organizational design. Prospector firms putting innovation on top of the agenda usually has a network organization which is more flexible. This paper analyzes how an SME from a traditional industry...

  4. Asymptotic stability of a genetic network under impulsive control

    International Nuclear Information System (INIS)

    Li Fangfei; Sun Jitao

    2010-01-01

    The study of the stability of genetic network is an important motif for the understanding of the living organism at both molecular and cellular levels. In this Letter, we provide a theoretical method for analyzing the asymptotic stability of a genetic network under impulsive control. And the sufficient conditions of its asymptotic stability under impulsive control are obtained. Finally, an example is given to illustrate the effectiveness of the obtained method.

  5. 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 ...

  6. 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

  7. 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)

  8. STRUCTURE AND COOPTATION IN ORGANIZATION NETWORK

    Directory of Open Access Journals (Sweden)

    Valéria Riscarolli

    2007-10-01

    Full Text Available Business executive are rethinking business concept, based on horizontalization principles. As so, most organizational functions are outsourced, leading the enterprise to build business through a network of organizations. Here we study the case of Cia Hering’s network of organizations, a leader in knit apparel segment in Latin America (IEMI, 2004, looking at the network’s structure and levels of cooptation. A theoretical model was used using Quinn et al. (2001 “sun ray” network structure as basis to analyze the case study. Main results indicate higher degree of structural conformity, but incipient degree of coopetation in the network.

  9. United Network for Organ Sharing

    Science.gov (United States)

    ... donor families & recipients Organ donation facts Policy Policy development Policy brochures Membership Data Transplant trends Data resources Technology Get Involved EDUCATE Become a UNOS Ambassador Promote organ donation Share through social media VISIT Attend a UNOS event Tour the National ...

  10. Organization of growing random networks

    International Nuclear Information System (INIS)

    Krapivsky, P. L.; Redner, S.

    2001-01-01

    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 k . When A k grows more slowly than linearly with k, the number of nodes with k links, N k (t), decays faster than a power law in k, while for A k growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A k is asymptotically linear, N k (t)∼tk -ν , with ν dependent on details of the attachment probability, but in the range 2 -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

  11. Computing chemical organizations in biological networks.

    Science.gov (United States)

    Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

    2008-07-15

    Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

  12. 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.

  13. 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...

  14. 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

    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...... manner under different failure scenarios. This work evaluates two rerouting strategies and proposes four policies for failure handling in a connection-oriented optical transport network, under generalized multiprotocol label switching control plane. The performance of the strategies and the policies......, 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...

  15. Exploring the networking behaviors of hospital organizations.

    Science.gov (United States)

    Di Vincenzo, Fausto

    2018-05-08

    Despite an extensive body of knowledge exists on network outcomes and on how hospital network structures may contribute to the creation of outcomes at different levels of analysis, less attention has been paid to understanding how and why hospital organizational networks evolve and change. The aim of this paper is to study the dynamics of networking behaviors of hospital organizations. Stochastic actor-based model for network dynamics was used to quantitatively examine data covering six-years of patient transfer relations among 35 hospital organizations. Specifically, the study investigated about determinants of patient transfer evolution modeling partner selection choice as a combination of multiple organizational attributes and endogenous network-based processes. The results indicate that having overlapping specialties and treating patients with the same case-mix decrease the likelihood of observing network ties between hospitals. Also, results revealed as geographical proximity and membership of the same LHA have a positive impact on the networking behavior of hospitals organizations, there is a propensity in the network to choose larger hospitals as partners, and to transfer patients between hospitals facing similar levels of operational uncertainty. Organizational attributes (overlapping specialties and case-mix), institutional factors (LHA), and geographical proximity matter in the formation and shaping of hospital networks over time. Managers can benefit from the use of these findings by clearly identifying the role and strategic positioning of their hospital with respect to the entire network. Social network analysis can yield novel information and also aid policy makers in the formation of interventions, encouraging alliances among providers as well as planning health system restructuring.

  16. 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.

  17. 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.

  18. Self-organization of complex networks as a dynamical system.

    Science.gov (United States)

    Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

    2015-01-01

    To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

  19. 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...

  20. 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-...

  1. CDMA coverage under mobile heterogeneous network load

    NARCIS (Netherlands)

    Saban, D.; van den Berg, Hans Leo; Boucherie, Richardus J.; Endrayanto, A.I.

    2002-01-01

    We analytically investigate coverage (determined by the uplink) under non-homogeneous and moving traffic load of third generation UMTS mobile networks. In particular, for different call assignment policies, we investigate cell breathing and the movement of the coverage gap occurring between cells

  2. Reliability of lifeline networks under seismic hazard

    International Nuclear Information System (INIS)

    Selcuk, A. Sevtap; Yuecemen, M. Semih

    1999-01-01

    Lifelines, such as pipelines, transportation, communication and power transmission systems, are networks which extend spatially over large geographical regions. The quantification of the reliability (survival probability) of a lifeline under seismic threat requires attention, as the proper functioning of these systems during or after a destructive earthquake is vital. In this study, a lifeline is idealized as an equivalent network with the capacity of its elements being random and spatially correlated and a comprehensive probabilistic model for the assessment of the reliability of lifelines under earthquake loads is developed. The seismic hazard that the network is exposed to is described by a probability distribution derived by using the past earthquake occurrence data. The seismic hazard analysis is based on the 'classical' seismic hazard analysis model with some modifications. An efficient algorithm developed by Yoo and Deo (Yoo YB, Deo N. A comparison of algorithms for terminal pair reliability. IEEE Transactions on Reliability 1988; 37: 210-215) is utilized for the evaluation of the network reliability. This algorithm eliminates the CPU time and memory capacity problems for large networks. A comprehensive computer program, called LIFEPACK is coded in Fortran language in order to carry out the numerical computations. Two detailed case studies are presented to show the implementation of the proposed model

  3. 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.

  4. 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.

  5. 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.

  6. The Multiplex Network of EU Lobby Organizations.

    Science.gov (United States)

    Zeng, An; Battiston, Stefano

    2016-01-01

    The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register with information about shareholding and interlocking directorates of firms. We find that the network centrality of lobby organizations has no simple relation with their lobbying budget. Moreover, different layers of the multiplex network provide complementary information to characterize organizations' potential influence. At the aggregate level, it appears that while the domains of finance and climate are separated on the layer of affiliation relations, they become intertwined when economic relations are considered. Because groups of interest differ not only in their budget and network centrality but also in terms of their internal cohesiveness, drawing a map of both connections across and within groups is a precondition to better understand the dynamics of influence on policy making and the forces at play.

  7. 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.

  8. 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...

  9. Network Formation under the Threat of Disruption

    NARCIS (Netherlands)

    Hoyer, B.

    2013-01-01

    The studies in this thesis are focused on the impact the presence of a network disruptor has on network formation models. In particular, we build two theoretical models to study the effect of network disruption on network formation and test the effect network disruption has on equilibrium selection

  10. Artificial neural network study on organ-targeting peptides

    Science.gov (United States)

    Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

    2010-01-01

    We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

  11. 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....

  12. Organization of excitable dynamics in hierarchical biological networks.

    Directory of Open Access Journals (Sweden)

    Mark Müller-Linow

    Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

  13. 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).

  14. 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

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

    Science.gov (United States)

    Fair, Damien A; Cohen, Alexander L; Power, Jonathan D; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Schlaggar, Bradley L; Petersen, Steven E

    2009-05-01

    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 both have

  16. 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

  17. 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.

  18. 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

  19. Prediction of pelvic organ prolapse using an artificial neural network.

    Science.gov (United States)

    Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

    2008-08-01

    The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

  20. 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.

  1. 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....

  2. 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.

  3. Hierarchical spatial organization of geographical networks

    International Nuclear Information System (INIS)

    Travencolo, Bruno A N; Costa, Luciano da F

    2008-01-01

    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

  4. Governing the transnational organic cotton network from Benin

    NARCIS (Netherlands)

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

    2012-01-01

    In this article, we attempt to conceptualize the historical development and the governance structure of the transnational organic cotton network from Benin. We aim to discover how the organic cotton production-consumption network is governed locally and internationally. Existing bodies of literature

  5. 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.)

  6. 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.

  7. 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

  8. 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...

  9. Network conditioning under conflicting goals: Accident causation

    International Nuclear Information System (INIS)

    Jouse, W.C.

    1992-01-01

    Networks based on the Barto-Sutton architecture (BSA) of neural-like elements have an information-processing structure that is analogous to the cognitive structure of a human. Given a set of explicitly stated rules of conduct, such networks develop a set of skills that is capable of satisfying the rules. In this sense, the network acts as a translator of rules into skill-based behavior. The BSA acquires its skills through casual, correlation-based scheduling. Stated briefly, it first constructs an internal representation, or model, of the rules of conduct, and then uses the model to correct deficiencies in its skill. It learns in a manner that closely resembles classical conditioning, shifting the onset of signals associated with unconditioned stimuli forward in time to coincide with the onset of conditioning stimuli. The low-level positive reinforcement the network receives from enhancing its operational efficiency is immediate and direct. In the absence of countervailing influences, this continuous pressure is sufficient to discount the recollection of past failures and leads to accidents with a predictable regularity

  10. 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.

  11. GOAT MILK PRODUCTION UNDER ORGANIC FARMING STANDARS

    Directory of Open Access Journals (Sweden)

    Gerold Hartmut Rahmann

    2009-02-01

    Full Text Available Organic farming has emerged from its niche. This holds true for organic goat milk, yoghurt and cheese as well. Particularly in the EU many dairy goat farms have converted or want to convert towards organic farming to profit from the positive image and the good prices for milk (+100% in Western Europe and Alpine regions. High performance dairy goats demand excellent feedstuffs, a sound environment and top management. It was not clear how organic farming can fulfil these demands. The restrictive factors influencing the productivity of the animals in organic farming are as follows: limited concentrate feeding (

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Robustness analysis of interdependent networks under multiple-attacking strategies

    Science.gov (United States)

    Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

    2018-04-01

    The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

  18. 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.

  19. 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.

  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.

    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.

  3. 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.

  4. Grower Communication Networks: Information Sources for Organic Farmers

    Science.gov (United States)

    Crawford, Chelsi; Grossman, Julie; Warren, Sarah T.; Cubbage, Fred

    2015-01-01

    This article reports on a study to determine which information sources organic growers use to inform farming practices by conducting in-depth semi-structured interviews with 23 organic farmers across 17 North Carolina counties. Effective information sources included: networking, agricultural organizations, universities, conferences, Extension, Web…

  5. Line and lattice networks under deterministic interference models

    NARCIS (Netherlands)

    Goseling, Jasper; Gastpar, Michael; Weber, Jos H.

    Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of

  6. 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

  7. Transnational organizing: Issue professionals in environmental sustainability networks.

    Science.gov (United States)

    Henriksen, Lasse Folke; Seabrooke, Leonard

    2016-09-01

    An ongoing question for institutional theory is how organizing occurs transnationally, where institution building occurs in a highly ambiguous environment. This article suggests that at the core of transnational organizing is competition and coordination within professional and organizational networks over who controls issues. Transnational issues are commonly organized through professional battles over how issues are treated and what tasks are involved. These professional struggles are often more important than what organization has a formal mandate over an issue. We highlight how 'issue professionals' operate in two-level professional and organizational networks to control issues. This two-level network provides the context for action in which professionals do their institutional work. The two-level network carries information about professional incentives and also norms about how issues should be treated and governed by organizations. Using network and career sequences methods, we provide a case of transnational organizing through professionals who attempt issue control and network management on transnational environmental sustainability certification. The article questions how transnational organizing happens, and how we can best identify attempts at issue control.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. Vulnerability of complex networks under intentional attack with incomplete information

    International Nuclear Information System (INIS)

    Wu, J; Deng, H Z; Tan, Y J; Zhu, D Z

    2007-01-01

    We study the vulnerability of complex networks under intentional attack with incomplete information, which means that one can only preferentially attack the most important nodes among a local region of a network. The known random failure and the intentional attack are two extreme cases of our study. Using the generating function method, we derive the exact value of the critical removal fraction f c of nodes for the disintegration of networks and the size of the giant component. To validate our model and method, we perform simulations of intentional attack with incomplete information in scale-free networks. We show that the attack information has an important effect on the vulnerability of scale-free networks. We also demonstrate that hiding a fraction of the nodes information is a cost-efficient strategy for enhancing the robustness of complex networks

  13. Multistage Logistic Network Optimization under Disruption Risk

    OpenAIRE

    Rusman, Muhammad

    2013-01-01

    Getting over disruptions risk has been a challenging issue for many companies under the globalization that will link to potential external source such as demand uncertainties, natural disasters, and terrorist attacks. The disruption is an unexpected event that disturbs normal flows of products and materials within a supply chain. The disruption at one members of supply chain will propagate the offers and finally affect significant impacts on the entire chain. If we look back...

  14. Self-organized criticality in a network of interacting neurons

    NARCIS (Netherlands)

    Cowan, J.D.; Neuman, J.; Kiewiet, B.; van Drongelen, W.

    2013-01-01

    This paper contains an analysis of a simple neural network that exhibits self-organized criticality. Such criticality follows from the combination of a simple neural network with an excitatory feedback loop that generates bistability, in combination with an anti-Hebbian synapse in its input pathway.

  15. Comparative Analysis of Human Communication Networks in Selected Formal Organizations.

    Science.gov (United States)

    Farace, Richard V.; Johnson, Jerome David

    This paper briefly describes the organization of a "data bank" containing research on communication networks, specifies the kinds of information compiled about various network properties, discusses some specific results of the work done to date, and presents some general conclusions about the overall project and its potential advantages to…

  16. Problems in the Deployment of Learning Networks In Small Organizations

    NARCIS (Netherlands)

    Shankle, Dean E.; Shankle, Jeremy P.

    2006-01-01

    Please, cite this publication as: Shankle, D.E., & Shankle, J.P. (2006). Problems in the Deployment of Learning Networks In Small Organizations. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria:

  17. How women organize social networks different from men.

    Science.gov (United States)

    Szell, Michael; Thurner, Stefan

    2013-01-01

    Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks. Here we study gender-specific differences of a multiplex network from a complete behavioral dataset of an online-game society of about 300,000 players. On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females. On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males. These results confirm quantitatively that females and males manage their social networks in substantially different ways.

  18. 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

  19. 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.

  20. 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...... 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...... 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...

  1. Informal Networks in Organizations - A Literature Review

    DEFF Research Database (Denmark)

    Waldstrøm, Christian

    2001-01-01

    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...

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

    Indian Academy of Sciences (India)

    Most of the complex systems seen in real life also have associated dynamics [10], and the ... another example, this time a hierarchical structure, viz., the Cayley tree with b ..... natural constraints operating on networks in real life, such as the ...

  3. Self-Organization in Communication Networks

    NARCIS (Netherlands)

    V. Bala; S. Goyal (Sanjeev)

    1997-01-01

    textabstractWe develop a dynamic model to study the formation of communication networks. In this model, individuals periodically make decisions concerning the continuation of existing information links and the formation of new information links, with their cohorts. These decisions trade off the

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, 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 (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. 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 sensitivity of critical states and the predictability and timing of oscillations for efficient information

  9. Energy network dispatch optimization under emergency of local energy shortage

    International Nuclear Information System (INIS)

    Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang

    2012-01-01

    The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.

  10. 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.

  11. 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.

  12. 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.

  13. Switching performance of OBS network model under prefetched real traffic

    Science.gov (United States)

    Huang, Zhenhua; Xu, Du; Lei, Wen

    2005-11-01

    Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

  14. Self-organized criticality in neural networks

    Science.gov (United States)

    Makarenkov, Vladimir I.; Kirillov, A. B.

    1991-08-01

    Possible mechanisms of creating different types of persistent states for informational processing are regarded. It is presented two origins of criticalities - self-organized and phase transition. A comparative analyses of their behavior is given. It is demonstrated that despite a likeness there are important differences. These differences can play a significant role to explain the physical issue of such highest functions of the brain as a short-term memory and attention. 1.

  15. Performance and energy efficiency in wireless self-organized networks

    Energy Technology Data Exchange (ETDEWEB)

    Gao, C.

    2009-07-01

    Self-organized packet radio networks (ad-hoc networks) and wireless sensor networks have got massive attention recently. One of critical problems in such networks is the energy efficiency, because wireless nodes are usually powered by battery. Energy efficiency design can dramatically increase the survivability and stability of wireless ad-hoc/sensor networks. In this thesis the energy efficiency has been considered at different protocol layers for wireless ad-hoc/sensor networks. The energy consumption of wireless nodes is inspected at the physical layer and MAC layer. At the network layer, some current routing protocols are compared and special attention has been paid to reactive routing protocols. A minimum hop analysis is given and according to the analysis result, a modification of AODV routing is proposed. A variation of transmit power can be also applied to clustering algorithm, which is believed to be able to control the scalability of network. Clustering a network can also improve the energy efficiency. We offer a clustering scheme based on the link state measurement and variation of transmit power of intra-cluster and inter-cluster transmission. Simulation shows that it can achieve both targets. In association with the clustering algorithm, a global synchronization scheme is proposed to increase the efficiency of clustering algorithm. The research attention has been also paid to self-organization for multi-hop cellular networks. A 2-hop 2-slot uplink proposal to infrastructure-based cellular networks. The proposed solution can significantly increase the throughput of uplink communication and reduce the energy consumption of wireless terminals. (orig.)

  16. 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.

  17. 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 ...

  18. 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.

  19. Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

    Science.gov (United States)

    Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

    2017-01-01

    Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

  20. The puzzling resilience of transnational organized criminal networks

    DEFF Research Database (Denmark)

    Leuprecht, Christian; Aulthouse, Andrew; Walther, Olivier

    2016-01-01

    international organized crime syndicate based in Jamaica, whose resilience proves particularly puzzling. We were curious to know whether there is any evidence that international borders have an effect on the structure of illicit networks that cross them. It turns out that transnational drug distribution......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...... networks such as the Shower Posse rely on a small number of brokers whose role is to connect otherwise distinct domestic markets. Due to the high transaction costs associated with developing and maintaining transnational movement, the role of such brokers appears particularly important in facilitating...

  1. Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.

    Science.gov (United States)

    Parras, Juan; Zazo, Santiago

    2018-01-30

    We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

  2. Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

    Directory of Open Access Journals (Sweden)

    Juan Parras

    2018-01-01

    Full Text Available We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

  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. SORN: a self-organizing recurrent neural network

    Directory of Open Access Journals (Sweden)

    Andreea Lazar

    2009-10-01

    Full Text Available Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success.

  5. Organizing product innovation: hierarchy, market or triple-helix networks?

    Science.gov (United States)

    Fitjar, Rune Dahl; Gjelsvik, Martin; Rodríguez-Pose, Andrés

    This paper assesses the extent to which the organization of the innovation effort in firms, as well as the geographical scale at which this effort is pursued, affects the capacity to benefit from product innovations. Three alternative modes of organization are studied: hierarchy, market and triple-helix-type networks. Furthermore, we consider triple-helix networks at three geographical scales: local, national and international. These relationships are tested on a random sample of 763 firms located in five urban regions of Norway which reported having introduced new products or services during the preceding 3 years. The analysis shows that firms exploiting internal hierarchy or triple-helix networks with a wide range of partners managed to derive a significantly higher share of their income from new products, compared to those that mainly relied on outsourcing within the market. In addition, the analysis shows that the geographical scale of cooperation in networks, as well as the type of partner used, matters for the capacity of firms to benefit from product innovation. In particular, firms that collaborate in international triple-helix-type networks involving suppliers, customers and R&D institutions extract a higher share of their income from product innovations, regardless of whether they organize the processes internally or through the network.

  6. Hierarchical organization of brain functional networks during visual tasks.

    Science.gov (United States)

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

    2011-09-01

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

  7. Stochastic Online Learning in Dynamic Networks under Unknown Models

    Science.gov (United States)

    2016-08-02

    The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for

  8. 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

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

    Directory of Open Access Journals (Sweden)

    Olav Østerbø

    2012-01-01

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

  10. Phrenic motoneurons: output elements of a highly organized intraspinal network.

    Science.gov (United States)

    Ghali, Michael George Zaki

    2018-03-01

    pontomedullary respiratory network generates the respiratory pattern and relays it to bulbar and spinal respiratory motor outputs. The phrenic motor system controlling diaphragm contraction receives and processes descending commands to produce orderly, synchronous, and cycle-to-cycle-reproducible spatiotemporal firing. Multiple investigators have studied phrenic motoneurons (PhMNs) in an attempt to shed light on local mechanisms underlying phrenic pattern formation. I and colleagues (Marchenko V, Ghali MG, Rogers RF. Am J Physiol Regul Integr Comp Physiol 308: R916-R926, 2015.) recorded PhMNs in unanesthetized, decerebrate rats and related their activity to simultaneous phrenic nerve (PhN) activity by creating a time-frequency representation of PhMN-PhN power and coherence. On the basis of their temporal firing patterns and relationship to PhN activity, we categorized PhMNs into three classes, each of which emerges as a result of intrinsic biophysical and network properties and organizes the orderly contraction of diaphragm motor fibers. For example, early inspiratory diaphragmatic activation by the early coherent burst generated by high-frequency PhMNs may be necessary to prime it to overcome its initial inertia. We have also demonstrated the existence of a prominent role for local intraspinal inhibitory mechanisms in shaping phrenic pattern formation. The objective of this review is to relate and synthesize recent findings with those of previous studies with the aim of demonstrating that the phrenic nucleus is a region of active local processing, rather than a passive relay of descending inputs.

  11. 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 ...

  12. 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.

  13. 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.

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

    DEFF Research Database (Denmark)

    Winther, Christian Dahl

    This paper studies the introduction of a new and incompatible technology in a spatial market with network externalities. In competition with an established network, the entrant chooses how long to do research and a level of product differentiation, which determine the adoption patterns of consumers...... level of product differentiation that should be chosen by the sponsor of the new technology in equilibrium. Third, the formal relationship between these variables are derived under compatibility.  Fourth, the entering firm's problem is solved by numerical methods to gain insight into the optimal linkage...... between research time and product design....

  15. 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.

  16. 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

  17. Mining E-mail to Leverage Knowledge Networks in Organizations

    NARCIS (Netherlands)

    van Reijsen, J.; Helms, R.W.; Jackson, T.W.

    2009-01-01

    There is nothing new about the notion that in today‟s knowledge driven economy, knowledge is the key strategic asset for competitive advantage in an organization. Also, we have learned that knowledge is residing in the organization‟s informal network. Hence, to leverage business performance from a

  18. 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

  19. 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…

  20. Knowledge Sharing via Social Networking Platforms in Organizations

    Science.gov (United States)

    Kettles, Degan

    2012-01-01

    Knowledge Management Systems have been actively promoted for decades within organizations but have frequently failed to be used. Recently, deployments of enterprise social networking platforms used for knowledge management have become commonplace. These platforms help harness the knowledge of workers by serving as repositories of knowledge as well…

  1. 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

  2. Organizing smart networks and humans into augmented teams

    NARCIS (Netherlands)

    Neef, R.M.; Rijn, M. van; Keus, D.; Marck, J.W.

    2009-01-01

    This paper discusses the challenge of turning networks of sensors, computers, agents and humans into hybrid teams that are capable, effective and adaptive. We propose a functional model and illustrate how such a model can be put into practice, and augment the capabilities of the human organization.

  3. Analyzing Human Communication Networks in Organizations: Applications to Management Problems.

    Science.gov (United States)

    Farace, Richard V.; Danowski, James A.

    Investigating the networks of communication in organizations leads to an understanding of efficient and inefficient information dissemination as practiced in large systems. Most important in organizational communication is the role of the "liaison person"--the coordinator of intercommunication. When functioning efficiently, coordinators maintain…

  4. Communication Network Integration and Group Uniformity in a Complex Organization.

    Science.gov (United States)

    Danowski, James A.; Farace, Richard V.

    This paper contains a discussion of the limitations of research on group processes in complex organizations and the manner in which a procedure for network analysis in on-going systems can reduce problems. The research literature on group uniformity processes and on theoretical models of these processes from an information processing perspective…

  5. Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

    Science.gov (United States)

    Li, Dong; Zhou, Changsong

    2011-01-01

    Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

  6. Functional brain networks underlying detection and integration of disconfirmatory evidence.

    Science.gov (United States)

    Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

    2015-05-15

    .g., 17s after trial onset) the hemodynamic responses associated with all three networks were simultaneously active. These findings highlight distinct cognitive processes and corresponding functional brain networks underlying stages of disconfirmatory evidence integration, and demonstrate the power of multivariate and multi-experiment methodology in cognitive neuroscience. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. How women organize social networks different from men

    Science.gov (United States)

    Szell, Michael; Thurner, Stefan

    2013-01-01

    Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks. Here we study gender-specific differences of a multiplex network from a complete behavioral dataset of an online-game society of about 300,000 players. On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females. On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males. These results confirm quantitatively that females and males manage their social networks in substantially different ways. PMID:23393616

  8. 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%.

  9. Mixed Transportation Network Design under a Sustainable Development Perspective

    Science.gov (United States)

    Qin, Jin; Ni, Ling-lin; Shi, Feng

    2013-01-01

    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%. PMID:23476142

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

    KAUST Repository

    Alfadly, Modar

    2018-01-01

    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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. In Search of a Network Organization for Innovation: A Multilevel Analysis on Transnational Corporations' Global Innovation

    DEFF Research Database (Denmark)

    Hu, Yimei

    2013-01-01

    4 explores how transnational corporations perceive and design an internal network organization to facilitate global innovation. Based on a multiple case study of three Danish transnational corporations’ global R&D organization, this paper shows three types of network organization design...... explores how an SME develops a network organization consisting of both interfirm innovation networks and an internal network organization to facilitate its global innovation strategy. Regarding the intraorganizational network organization, market mechanism is adopted to optimize internal resource...... corporations perceive/design a network organization to facilitate their global innovation? • To what extent and how can we manage a network organization? Research focus of the dissertation is on transnational corporations’ network organization for innovation. The first research question aims to clarify...

  16. Organization of managed clinical networking for home parenteral nutrition.

    Science.gov (United States)

    Baxter, Janet P; McKee, Ruth F

    2006-05-01

    Home parenteral nutrition (HPN) is an established treatment for intestinal failure, and organization of HPN is variable throughout the UK and Europe. Managed clinical networking is the single most important feature of the UK National Health Service strategy for acute services in Scotland and has the potential to improve the management of HPN patients. This review addresses the role of managed clinical networking in HPN and compares outcome data between centres. The Scottish HPN Managed Clinical Network has published the main body of the current literature supporting the concept of managed clinical networking in this context. The Network is responsible for the organization and quality assurance of HPN provision in Scotland, and has been established for 5 years. It has captured significant patient data for the purpose of clinical audit and illustrates that this is an effective model for the management of this patient population. This review provides advice for other areas wishing to improve equity of access, and to smooth the patient journey between primary, secondary and tertiary health care in the context of artificial nutrition support.

  17. 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.

  18. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    Science.gov (United States)

    Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R; Scherer, Norbert F

    2012-01-01

    Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS).

  19. Optimal Intermittent Operation of Water Distribution Networks under Water Shortage

    Directory of Open Access Journals (Sweden)

    mohamad Solgi

    2017-07-01

    Full Text Available Under water shortage conditions, it is necessary to exercise water consumption management practices in water distribution networks (WDN. Intermittent supply of water is one such practice that makes it possible to supply consumption nodal demands with the required pressure via water cutoff to some consumers during certain hours of the day. One of the most important issues that must be observed in this management practice is the equitable and uniform water distribution among the consumers. In the present study, uniformity in water distribution and minimum supply of water to all consumers are defined as justice and equity, respectively. Also, an optimization model has been developed to find an optimal intermittent supply schedule that ensures maximum number of demand nodes are supplied with water while the constraints on the operation of water distribution networks are also observed. To show the efficiency of the proposed model, it has been used in the Two-Loop distribution network under several different scenarios of water shortage. The optimization model has been solved using the honey bee mating optimization algorithm (HBMO linked to the hydraulic simulator EPANET. The results obtained confirm the efficiency of the proposed model in achieving an optimal intermittent supply schedule. Moreover, the model is found capable of distributing the available water in an equitable and just manner among all the consumers even under severe water shoratges.

  20. Phylogenetically informed logic relationships improve detection of biological network organization

    Science.gov (United States)

    2011-01-01

    Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

  1. 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

  2. Self-organized criticality in developing neuronal networks.

    Directory of Open Access Journals (Sweden)

    Christian Tetzlaff

    Full Text Available Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monitor the development between 13 and 95 days in vitro (DIV of cortical cell cultures (n = 20 and find four different phases, related to their morphological maturation: An initial low-activity state (≈19 DIV is followed by a supercritical (≈20 DIV and then a subcritical one (≈36 DIV until the network finally reaches stable criticality (≈58 DIV. Using network modeling and mathematical analysis we describe the dynamics of the emergent connectivity in such developing systems. Based on physiological observations, the synaptic development in the model is determined by the drive of the neurons to adjust their connectivity for reaching on average firing rate homeostasis. We predict a specific time course for the maturation of inhibition, with strong onset and delayed pruning, and that total synaptic connectivity should be strongly linked to the relative levels of excitation and inhibition. These results demonstrate that the interplay between activity and connectivity guides developing networks into criticality suggesting that this may be a generic and stable state of many networks in vivo and in vitro.

  3. 76 FR 78216 - Organ Procurement and Transplantation Network

    Science.gov (United States)

    2011-12-16

    ..., tissues, and cellular and tissue-based products or HCT/Ps. The Food and Drug Administration (FDA... similar supporting statements for OPTN oversight. The commenters agreed that the use of the existing solid... comment stated that VCA do not fit as organs under HRSA oversight due to differences between solid organs...

  4. Brain network response underlying decisions about abstract reinforcers.

    Science.gov (United States)

    Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

    2014-12-01

    Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. Self-organized semiconductor nano-network on graphene

    Science.gov (United States)

    Son, Dabin; Kim, Sang Jin; Lee, Seungmin; Bae, Sukang; Kim, Tae-Wook; Kang, Jae-Wook; Lee, Sang Hyun

    2017-04-01

    A network structure consisting of nanomaterials with a stable structural support and charge path on a large area is desirable for various electronic and optoelectronic devices. Generally, network structures have been fabricated via two main strategies: (1) assembly of pre-grown nanostructures onto a desired substrate and (2) direct growth of nanomaterials onto a desired substrate. In this study, we utilized the surface defects of graphene to form a nano-network of ZnO via atomic layer deposition (ALD). The surface of pure and structurally perfect graphene is chemically inert. However, various types of point and line defects, including vacancies/adatoms, grain boundaries, and ripples in graphene are generated by growth, chemical or physical treatments. The defective sites enhance the chemical reactivity with foreign atoms. ZnO nanoparticles formed by ALD were predominantly deposited at the line defects and agglomerated with increasing ALD cycles. Due to the formation of the ZnO nano-network, the photocurrent between two electrodes was clearly changed under UV irradiation as a result of the charge transport between ZnO and graphene. The line patterned ZnO/graphene (ZnO/G) nano-network devices exhibit sensitivities greater than ten times those of non-patterned structures. We also confirmed the superior operation of a fabricated flexible photodetector based on the line patterned ZnO/G nano-network.

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

    International Nuclear Information System (INIS)

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

    2008-01-01

    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. 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.

  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. Organization of Multi-controller Interaction in Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Sergey V. Morzhov

    2018-01-01

    Full Text Available Software Defined Networking (SDN is a promising paradigm for network management. It is a centralized network intelligence on a dedicated server, which runs network operating system, and is called SDN controller. It was assumed that such an architecture should have an improved network performance and monitoring. However, the centralized control architecture of the SDNs brings novel challenges to reliability, scalability, fault tolerance and interoperability. These problems are especially acute for large data center networks and can be solved by combining SDN controllers into clusters, called multi-controllers. Multi-controller architecture became very important for SDN-enabled networks nowadays. This paper gives a comprehensive overview of SDN multi-controller architectures. The authors review several most popular distributed controllers in order to indicate their strengths and weaknesses. They also investigate and classify approaches used. This paper explains in details the difference among various types of multi-controller architectures, the distribution method and the communication system. Furthermore, it provides already implemented architectures and some examples of architectures under consideration by describing their design, communication process, and performance results. In this paper, the authors show their own classification of multi-controllers and claim that, despite the existence of undeniable advantages, all reviewed controllers have serious drawbacks, which must be eliminated. These drawbacks hamper the development of multi-controllers and their widespread adoption in corporate networks. In the end, the authors conclude that now it is impossible to find a solution capable to solve all the tasks assigned to it adequately and fully. The article is published in the authors’ wording.

  14. Developmental changes in organization of structural brain networks.

    Science.gov (United States)

    Khundrakpam, Budhachandra S; Reid, Andrew; Brauer, Jens; Carbonell, Felix; Lewis, John; Ameis, Stephanie; Karama, Sherif; Lee, Junki; Chen, Zhang; Das, Samir; Evans, Alan C

    2013-09-01

    Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

  15. Capturing spatial heterogeneity of soil organic carbon under changing climate

    Science.gov (United States)

    Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

    2015-12-01

    The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution

  16. 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...... 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...... 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....

  17. Human and Organizational Risk Modeling: Critical Personnel and Leadership in Network Organizations

    National Research Council Canada - National Science Library

    Schreiber, Craig

    2006-01-01

    Network organizations offer learning, adaptive and resilient capabilities that are particularly useful in high velocity environments as these capabilities allow the organization to effectively respond to change...

  18. 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.

  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

    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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

    Science.gov (United States)

    Hortos, William S.

    2006-05-01

    algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

  6. Evolution of interstellar organic compounds under asteroidal hydrothermal conditions

    Science.gov (United States)

    Vinogradoff, V.; Bernard, S.; Le Guillou, C.; Remusat, L.

    2018-05-01

    Carbonaceous chondrites (CC) contain a diversity of organic compounds. No definitive evidence for a genetic relationship between these complex organic molecules and the simple organic molecules detected in the interstellar medium (ISM) has yet been reported. One of the many difficulties arises from the transformations of organic compounds during accretion and hydrothermal alteration on asteroids. Here, we report results of hydrothermal alteration experiments conducted on a common constituent of interstellar ice analogs, Hexamethylenetetramine (HMT - C6H12N4). We submitted HMT to asteroidal hydrothermal conditions at 150 °C, for various durations (up to 31 days) and under alkaline pH. Organic products were characterized by gas chromatography mass spectrometry, infrared spectroscopy and synchrotron-based X-ray absorption near edge structure spectroscopy. Results show that, within a few days, HMT has evolved into (1) a very diverse suite of soluble compounds dominated by N-bearing aromatic compounds (> 150 species after 31 days), including for instance formamide, pyridine, pyrrole and their polymers (2) an aromatic and N-rich insoluble material that forms after only 7 days of experiment and then remains stable through time. The reaction pathways leading to the soluble compounds likely include HMT dissociation, formose and Maillard-type reactions, e.g. reactions of sugar derivatives with amines. The present study demonstrates that, if interstellar organic compounds such as HMT had been accreted by chondrite parent bodies, they would have undergone chemical transformations during hydrothermal alteration, potentially leading to the formation of high molecular weight insoluble organic molecules. Some of the diversity of soluble and insoluble organic compounds found in CC may thus result from asteroidal hydrothermal alteration.

  7. 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

  8. 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.

  9. 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.

  10. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available 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.

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

    OpenAIRE

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

    2017-01-01

    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 fac...

  12. Fully convolutional neural networks improve abdominal organ segmentation

    Science.gov (United States)

    Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

    2018-03-01

    Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

  13. Effects of Perchlorate on Organic Molecules under Simulated Mars Conditions

    Science.gov (United States)

    Carrier, B. L.; Kounaves, S. P.

    2014-12-01

    Perchlorate (ClO4-) was discovered in the northern polar region of Mars by the Mars Phoenix Lander in 2008 and has also been recently detected by the Curiosity Rover in Gale Crater [1,2]. Perchlorate has also been shown to be formed under current Mars conditions via the oxidation of mineral chlorides, further supporting the theory that perchlorate is present globally on Mars [3]. The discovery of perchlorate on Mars has raised important questions about the effects of perchlorate on the survival and detection of organic molecules. Although it has been shown that pyrolysis in the presence of perchlorate results in the alteration or destruction of organic molecules [4], few studies have been conducted on the potential effects of perchlorate on organic molecules under martian surface conditions. Although perchlorate is typically inert under Mars-typical temperatures [5], perchlorate does absorb high energy UV radiation, and has been shown to decompose to form reactive oxychlorine species such as chlorite (ClO2-) when exposed to martian conditions including UV or ionizing radiation [6,7]. Here we investigate the effects of perchlorate on the organic molecules tryptophan, benzoic acid and mellitic acid in order to determine how perchlorate may alter these compounds under Mars conditions. Experiments are performed in a Mars Simulation Chamber (MSC) capable of reproducing the temperature, pressure, atmospheric composition and UV flux found on Mars. Soil simulants are prepared consisting of SiO2 and each organic, as well as varying concentrations of perchlorate salts, and exposed in the MSC. Subsequent to exposure in the MSC samples are leached and the leachate analyzed by HPLC and LC-MS to determine the degree of degradation of the original organic and the identity of any potential decomposition products formed by oxidation or chlorination. References: [1] Kounaves et al., J. Geophys. Res. Planets, Vol. 115, p. E00E10, 2010 [2] Glavin et al., J. Geophys. Res. Planets, Vol

  14. Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

    Science.gov (United States)

    Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R

    2017-08-15

    The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Designing container shipping network under changing demand and freight rates

    Directory of Open Access Journals (Sweden)

    C. Chen

    2010-03-01

    Full Text Available This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non-linear programming problem (MINP with an objective of maximizing the average unit ship-slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship-slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi-level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.

  16. 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.

  17. 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)

  18. Performance of different tomato cultivars under organic and inorganic regimes

    International Nuclear Information System (INIS)

    Ali, I.; Khattak, A. M.; Ali, M.; Ullah, K.

    2015-01-01

    To study the performance of different tomato cultivars under organic and inorganic regimes an experiment was conducted at New Developmental Farm, The University of Agriculture, Peshawar, Pakistan during the summer 2013-14. The experiment was laid out in RCBD with split plot arrangement having four replications. Organic regimes (FYM, poultry manure and mushroom compost) and inorganic (NPK) regimes were allotted to main plot, while cultivars (Roma VF, Roma, Super Classic, Bambino and Rio Grande) were subjected to sub plots. Organic and Inorganic regimes significantly (P ≤ 0.01) influenced all the studied attributes of tomato cultivars. Among different cultivars, Roma gave maximum plant survival (93.8 percentage), number of leaves plant (84.1), number of flower inflorescence (5.4), number of fruits inflorescence (4.3), number of fruit plant (25.4), fruit size (63.9 cm) fruit weight plant (9.1 kg) and total yield (22.9 t ha). However, it was closely followed by cultivar Rio Grande for number of leaves plant (79.6), number of flower inflorescence (5.1), number of fruits inflorescence (4.0) and number of fruits plant (24.9). Cultivar Super Classic produced minimum number of leaves plant (67.7), flower inflorescence (4.8), fruit size (60.6 cm), fruit weight plant (8.6 kg) and total yield (21.7 t ha). Similarly, highest plant survival (90.0 percentage), number of flower inflorescence (5.1), number of fruits inflorescence (4.0), number of fruit plant (25.4), fruit size (62.4 ml), fruit weight plant (8.90 kg) and total yield (22.9 t ha) were recorded in plants provided with organic conditions Roma cultivar performed better than other cultivars under the agro climatic condition of Peshawar followed by cultivar Rio Grande. Therefore, organic tomato production, and these two cultivars are recommended to be grown in Peshawar area. (author)

  19. 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

  20. 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.

  1. 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)

  2. 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.

  3. Susceptibility of Permafrost Soil Organic Carbon under Warming Climate

    Science.gov (United States)

    Yang, Z.; Wullschleger, S. D.; Liang, L.; Graham, D. E.; Gu, B.

    2015-12-01

    Degradation of soil organic carbon (SOC) that has been stored in permafrost is a key concern under warming climate because it could provide a positive feedback. Studies and conceptual models suggest that SOC degradation is largely controlled by the decomposability of SOC, but it is unclear exactly what portions of SOC are susceptible to rapid breakdown and what mechanisms may be involved in SOC degradation. Using a suite of analytical techniques, we examined the dynamic consumption and production of labile SOC compounds, including sugars, alcohols, and small molecular weight organic acids in incubation experiments (up to 240 days at either -2 or 8 °C) with a tundra soil under anoxic conditions, where SOC respiration and iron(III) reduction were monitored. We observe that sugars and alcohols are main components in SOC accounting for initial rapid release of CO2 and CH4 through anaerobic fermentation, whereas the fermentation products such as acetate and formate are subsequently utilized as primary substrates for methanogenesis. Iron(III) reduction is correlated to acetate production and methanogenesis, suggesting its important roles as an electron acceptor in tundra SOC respiration. These observations corroborate strongly with the glucose addition during incubation, in which rapid CO2 and CH4 production is observed concurrently with rapid production and consumption of organics such as acetate. Thus, the biogeochemical processes we document here are pertinent to understanding the accelerated SOC decomposition with temperature and could provide basis for model predicting feedbacks to climate warming in the Arctic.

  4. 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....

  5. 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.

  6. Analysis of Informationization Construction of Business Financial Management under the Network Economy

    Science.gov (United States)

    Dong, Yahui; Zhang, Pengwei; Li, Wei

    To strengthen the informationization construction of the financial management has great significance to the achievement of business management informationization, and under the network economic environment, it is an important task of the financial management that how to conduct informationization construction of traditional financial management to provide true, reliable and complete financial information system for the business managers. This paper thoroughly researches the problem of financial information orientation management (FIOM) by taking the method of combining theory with practice. This paper puts forward the thinking method of financial information management, makes the new contents of E-finance. At last, this paper rebuilds the system of finance internal control from four aspects such as control of organization and management, system development control and safety control of network system.

  7. 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

  8. Network formation under heterogeneous costs: The multiple group model

    NARCIS (Netherlands)

    Kamphorst, J.J.A.; van der Laan, G.

    2007-01-01

    It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between

  9. Organic Matter Responses to Radiation under Lunar Conditions

    Science.gov (United States)

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

    2016-01-01

    Abstract 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. Key Words: Radiation—Moon—Regolith—Amino acids—Biomarkers. Astrobiology 16, 900–912. PMID:27870583

  10. Maintenance of electromechanical equipment in quality organization under operating conditions

    International Nuclear Information System (INIS)

    Mercier, J.P.

    1984-01-01

    The paper outlines the principles adopted by the Thermal Production Service of Electricite de France on the basis of the experience of the first years of operation of its 900 MW(e)PWR units for the purpose of improving quality organization in operating conditions in respect of the maintenance of electromechanical safety equipment. This organization is based on application of the usual principles for quality assurance, adapted in accordance with current French regulations. The paper first recalls the now traditional methods of applying the principles of quality organization in the area of equipment maintenance. It then defines particular so-called ''delicate'' activities which, in accordance with the above regulations, are subjected to additional quality organizational procedures; this applies in particular to the area of pre-maintenance preparation and studies and to the control exercised by the French safety authorities over the execution of those activities. The paper explains how the application of the regulations improves maintenance practices compared with standard quality organization. It describes how the attempt to establish a frontier between these two types of activity (current and ''delicate'') has led to the definition of a classification criterion which is technically correct and simple to use and is based on the professional skills of those performing each activity. The paper then describes in greater detail the principal rules for the performance of those tasks which come under the standard organization and those to which more stringent criteria apply. Lastly, it explains the thinking behind equipment surveillance programmes and the analysis of anomalies discovered through surveillance measures or brought to light by operating incidents, the aim of these being to benefit from the experience gained

  11. 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.

  12. Possibility of a ferromagnetic and conducting metal-organic network

    Science.gov (United States)

    Mabrouk, Manel; Hayn, Roland; Denawi, Hassan; Ben Chaabane, Rafik

    2018-05-01

    In this paper, we present first principles calculations based on the spin-polarized generalized gradient approximation with on-site Coulomb repulsion term (SGGA + U), to explore the electronic and magnetic properties of the novel planar metal-organic networks TM-Pc and TM-TCNB (where TM means a transition metal of the 3d series: Ti, V, Cr, …, or Zn, Pc - Phthalocyanine, and TCNB - Tetracyanobenzene) as free-standing sheets. This work is an extension of two earlier research works dealing with the Mn (Mabrouk et al., 2015) and Fe (Mabrouk et al., 2017) cases. Our theoretical investigations demonstrate that TM-Pc are more stable than TM-TCNB. Our results unveil that all the TM-Pc frameworks have an insulating behavior with the exception of Mn-Pc which is half-metallic and favor antiferromagnetic order in the case of our magnetic systems except for V-Pc which is ferromagnetic. In contrast, the TM-TCNB networks are metallic at least in one spin direction and exhibit long-range ferromagnetic coupling in case for magnetic structures, which represent ideal candidates and an interesting prospect of unprecedented applications in spintronics. In addition, these results may shed light to achieve a new pathway on further experimental research in molecular spintronics.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

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

    International Nuclear Information System (INIS)

    Kounavis, P.

    2016-01-01

    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.

  20. 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

  1. 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)

  2. 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

  3. ORGANIC CARBON AND TOTAL NITROGEN IN THE DENSIMETRIC FRACTIONS OF ORGANIC MATTER UNDER DIFFERENT SOIL MANAGEMEN

    Directory of Open Access Journals (Sweden)

    MARCELO RIBEIRO VILELA PRADO

    2016-01-01

    Full Text Available The evaluation of land use and management by the measurement of soil organic matter and its fractions has gained attention since it helps in the understanding of the dynamics of their contribution to soil productivity, especially in tropical environments. This study was conducted in the municipality of Colorado do Oeste, state of Rondônia, Brazil and its aim was to determinethe quantity of organic carbon and total nitrogen in the light and heavy fractions of organic matter in the surface layers of a typic hapludalf under different land use systems: Native Forest: open evergreen forest, reference environment; Agroforestry System 1: teak (Tectona grandis LF and kudzu (Pueraria montana; Agroforestry System 2: coffee (Coffea canephora, marandu palisade grass (Brachiaria brizantha cv. Marandu, “pinho cuiabano” (Parkia multijuga, teak and kudzu.; Agroforestry System 3: teak and cocoa (Theobroma cacao; Silvopasture System: teak, cocoa and marandu palisade grass; and Extensive Grazing System: marandu palisade grass. The experimental design was a randomized block in split-split plots (use systems versus soil layers of 0-0.05 and 0.05-0.10 m with three replications. The results showed that relative to Native Forest, the Agroforestry System 2 had equal- and greater amounts of organic carbon and total nitrogen respectively (light and heavy fractions in the soil organic matter, with the light fraction being responsible for storage of approximately 45% and 70% of the organic carbon and total nitrogen, respectively. Therefore, the light densimetric fraction proved to be useful in the early identification of the general decline of the soil organic matter in the land use systems evaluated.

  4. Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism.

    Science.gov (United States)

    Duan, Xujun; Chen, Heng; He, Changchun; Long, Zhiliang; Guo, Xiaonan; Zhou, Yuanyue; Uddin, Lucina Q; Chen, Huafu

    2017-10-03

    Although evidence is accumulating that autism spectrum disorder (ASD) is associated with disruption of functional connections between and within brain networks, it remains largely unknown whether these abnormalities are related to specific frequency bands. To address this question, network contingency analysis was performed on brain functional connectomes obtained from 213 adolescent participants across nine sites in the Autism Brain Imaging Data Exchange (ABIDE) multisite sample, to determine the disrupted connections between and within seven major cortical networks in adolescents with ASD at Slow-5, Slow-4 and Slow-3 frequency bands and further assess whether the aberrant intra- and inter-network connectivity varied as a function of ASD symptoms. Overall under-connectivity within and between large-scale intrinsic networks in ASD was revealed across the three frequency bands. Specifically, decreased connectivity strength within the default mode network (DMN), between DMN and visual network (VN), ventral attention network (VAN), and between dorsal attention network (DAN) and VAN was observed in the lower frequency band (slow-5, slow-4), while decreased connectivity between limbic network (LN) and frontal-parietal network (FPN) was observed in the higher frequency band (slow-3). Furthermore, weaker connectivity within and between specific networks correlated with poorer communication and social interaction skills in the slow-5 band, uniquely. These results demonstrate intrinsic under-connectivity within and between multiple brain networks within predefined frequency bands in ASD, suggesting that frequency-related properties underlie abnormal brain network organization in the disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. 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

  6. 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

  7. Functional neural networks underlying response inhibition in adolescents and adults.

    Science.gov (United States)

    Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

    2007-07-19

    This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

  8. Stabilization of Networked Control Systems Under Feedback-based Communication

    National Research Council Canada - National Science Library

    Zhang, Lei; Hristu-Varsakelis, Dimitrios

    2004-01-01

    We study the stabilization of a networked control system (NSC) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller...

  9. 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.

  10. 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.

  11. 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.

  12. Reliability of Broadcast Communications Under Sparse Random Linear Network Coding

    OpenAIRE

    Brown, Suzie; Johnson, Oliver; Tassi, Andrea

    2018-01-01

    Ultra-reliable Point-to-Multipoint (PtM) communications are expected to become pivotal in networks offering future dependable services for smart cities. In this regard, sparse Random Linear Network Coding (RLNC) techniques have been widely employed to provide an efficient way to improve the reliability of broadcast and multicast data streams. This paper addresses the pressing concern of providing a tight approximation to the probability of a user recovering a data stream protected by this kin...

  13. ORGANIZATION OF CLOUD COMPUTING INFRASTRUCTURE BASED ON SDN NETWORK

    Directory of Open Access Journals (Sweden)

    Alexey A. Efimenko

    2013-01-01

    Full Text Available The article presents the main approaches to cloud computing infrastructure based on the SDN network in present data processing centers (DPC. The main indexes of management effectiveness of network infrastructure of DPC are determined. The examples of solutions for the creation of virtual network devices are provided.

  14. Some scale-free networks could be robust under selective node attacks

    Science.gov (United States)

    Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

    2011-04-01

    It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

  15. Governing the Organic Cocoa Network from Ghana: Towards Hybrid Governance Arrangements?

    NARCIS (Netherlands)

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

    2015-01-01

    In this paper, we examine the processes of initiation, construction and transformation of the organic cocoa network from Ghana. We address in particular how the state responded to and engaged with civil-society actors in the organic cocoa network and to what extent state involvement reshaped

  16. Salience network dynamics underlying successful resistance of temptation

    Science.gov (United States)

    Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

    2017-01-01

    Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

  17. Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

    Science.gov (United States)

    Zhang, WenJun

    2007-07-01

    Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

  18. On library information resources construction under network environment

    International Nuclear Information System (INIS)

    Guo Huifang; Wang Jingjing

    2014-01-01

    Information resources construction is the primary task and critical measures for libraries. In the 2lst century, the knowledge economy era, with the continuous development of computer network technology, information resources have become an important part of libraries which have been a significant indicator of its capacity construction. The development of socialized Information, digitalization and internalization has put forward new requirements for library information resources construction. This paper describes the impact of network environment on construction of library information resources and proposes the measures of library information resources. (authors)

  19. 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

    2014-10-01

    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.

  20. Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

    Directory of Open Access Journals (Sweden)

    Juan F. Monsalve-Posada

    2015-01-01

    Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

  1. Autonomous Distributed Self-Organization for Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-11-01

    Full Text Available This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently. A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

  2. Autonomous distributed self-organization for mobile wireless sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Tang, Hung-Kai

    2009-01-01

    This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

  3. 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.

  4. 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...

  5. A study on the evolution of crack networks under thermal fatigue loading

    International Nuclear Information System (INIS)

    Kamaya, Masayuki; Taheri, Said

    2008-01-01

    The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components

  6. Robust collaborative process interactions under system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2013-01-01

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes its state, it sends messages to the relevant processes to inform about this change. However, server crashes

  7. Identification of gene networks underlying dystocia in dairy cattle

    Science.gov (United States)

    Dystocia is a trait with a high impact in the dairy industry. Among its risk factors are calf weight, gestation length, breed and conformation. Biological networks have been proposed to capture the genetic architecture of complex traits, where GWAS show limitations. The objective of this study was t...

  8. Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

    Science.gov (United States)

    Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

    2016-10-01

    Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

  9. Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

    Science.gov (United States)

    Hoomod, Haider K.; Kareem Jebur, Tuka

    2018-05-01

    Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

  10. 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…

  11. Convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks

    Science.gov (United States)

    Long, Yin; Zhang, Xiao-Jun; Wang, Kui

    2018-05-01

    In this paper, convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks (RBDNs) are studied. First, we find and demonstrate that the average degree is convergent in the form of power law. Meanwhile, we discover that the ratios of the back items to front items of convergent reminder are independent of network link number for large network size, and we theoretically prove that the limit of the ratio is a constant. Moreover, since it is difficult to calculate the analytical solution of the average degree for large network sizes, we adopt numerical method to obtain approximate expression of the average degree to approximate its analytical solution. Finally, simulations are presented to verify our theoretical results.

  12. 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.

  13. 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.

  14. Coverage-maximization in networks under resource constraints.

    Science.gov (United States)

    Nandi, Subrata; Brusch, Lutz; Deutsch, Andreas; Ganguly, Niloy

    2010-06-01

    Efficient coverage algorithms are essential for information search or dispersal in all kinds of networks. We define an extended coverage problem which accounts for constrained resources of consumed bandwidth B and time T . Our solution to the network challenge is here studied for regular grids only. Using methods from statistical mechanics, we develop a coverage algorithm with proliferating message packets and temporally modulated proliferation rate. The algorithm performs as efficiently as a single random walker but O(B(d-2)/d) times faster, resulting in significant service speed-up on a regular grid of dimension d . The algorithm is numerically compared to a class of generalized proliferating random walk strategies and on regular grids shown to perform best in terms of the product metric of speed and efficiency.

  15. 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

  16. 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

  17. 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.

  18. Morphological self-organizing feature map neural network with applications to automatic target recognition

    Science.gov (United States)

    Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

    2005-01-01

    The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

  19. Functional organization of the vascular network of Physarum polycephalum

    International Nuclear Information System (INIS)

    Baumgarten, Werner; Hauser, Marcus J B

    2013-01-01

    The plasmodium of the slime mould Physarum polycephalum forms a transportation network of veins, in which protoplasm is transported due to peristaltic pumping. This network forms a planar, weighted, undirected graph that, for the first time, can be extracted automatically from photographs or movies. Thus, data from real transportation networks have now become available for the investigation of network properties. We determine the local drag of the vein segments and use these data to calculate the transport efficiency. We unravel which veins form the backbone of the transportation network by using a centrality measure from graph theory. The principal vein segments lie on relatively ample cycles of veins, and the most important segments are those that belong simultaneously to two of these principal cycles. Each principal cycle contains a series of smaller cycles of veins of lower transport efficiency, thus reflecting the hierarchical and self-similar structure of the transportation network. Finally, we calculate accessibility maps that show how easily different nodes of the network may be reached from a given reference node. (paper)

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

    Directory of Open Access Journals (Sweden)

    Tuikkala Johannes

    2012-03-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions 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.

  1. 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.

  2. 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.

  3. 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

    2015-01-01

    Abstract 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. PMID:26713863

  4. 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.

  5. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems.

    Directory of Open Access Journals (Sweden)

    Martin Rosvall

    Full Text Available To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network--the optimal number of levels and modular partition at each level--with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks.

  6. A Network Perspective on Individual-Level Ambidexterity in Organizations

    DEFF Research Database (Denmark)

    Rogan, Michelle; Mors, Marie Louise

    2014-01-01

    in the internal and external networks of 79 senior managers in a management consulting firm revealed significant differences in the density, contact heterogeneity, and informality of ties in the networks of senior managers who engaged in both exploration and exploitation compared with managers that predominately......Addressing the call for a deeper understanding of ambidexterity at the individual level, we propose that managers’ networks are an important yet understudied factor in the ability to balance the trade-off between exploring for new business and exploiting existing business. Analyses of 1,449 ties...... explored or exploited. The findings suggest that managers’ networks are important levers for their ability to behave ambidextrously and offer insights into the microfoundations of organizational ambidexterity....

  7. Local organization of graphene network inside graphene / polymer composites

    NARCIS (Netherlands)

    Alekseev, A.; Chen, D.; Tkalya, E.; Gomes Ghislandi, M.; Syurik, Y.V.; Ageev, O.A.; Loos, J.; With, de G.

    2012-01-01

    The local electrical properties of a conductive graphene/polystyrene (PS) composite sample are studied by scanning probe microscopy (SPM) applying various methods for electrical properties investigation. We show that the conductive graphene network can be separated from electrically isolated

  8. 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

  9. Network Organization Unfolds over Time during Periods of Anxious Anticipation

    OpenAIRE

    McMenamin, Brenton W.; Langeslag, Sandra J.E.; Sirbu, Mihai; Padmala, Srikanth; Pessoa, Luiz

    2014-01-01

    Entering a state of anxious anticipation triggers widespread changes across large-scale networks in the brain. The temporal aspects of this transition into an anxious state are poorly understood. To address this question, an instructed threat of shock paradigm was used while recording functional MRI in humans to measure how activation and functional connectivity change over time across the salience, executive, and task-negative networks and how they interact with key regions implicated in emo...

  10. The advertising creations network : implications to society and organizations

    OpenAIRE

    Παζαρζή, Νίνα Ε.

    2007-01-01

    This article investigates television-advertising production in the context of the systemic thinking. Advertising rhetoric is based on shared codes that are used by particular professional networks of the «urban elites». New technologies, new cinematographic techniques, latest fads, reformed postmodern arguments, etc are developed by «lead users» and subsequently are passed along those networks. In this respect, particular innovative practices can gradually become a part of the ...

  11. Self-Organized Governance Networks for Ecosystem Management: Who Is Accountable?

    Directory of Open Access Journals (Sweden)

    Thomas Hahn

    2011-06-01

    Full Text Available Governance networks play an increasingly important role in ecosystem management. The collaboration within these governance networks can be formalized or informal, top-down or bottom-up, and designed or self-organized. Informal self-organized governance networks may increase legitimacy if a variety of stakeholders are involved, but at the same time, accountability becomes blurred when decisions are taken. Basically, democratic accountability refers to ways in which citizens can control their government and the mechanisms for doing so. Scholars in ecosystem management are generally positive to policy/governance networks and emphasize its potential for enhancing social learning, adaptability, and resilience in social-ecological systems. Political scientists, on the other hand, have emphasized the risk that the public interest may be threatened by governance networks. I describe and analyze the multilevel governance network of Kristianstads Vattenrike Biosphere Reserve (KVBR in Southern Sweden, with the aim of understanding whether and how accountability is secured in the governance network and its relation to representative democracy. The analysis suggests that the governance network of KVBR complements representative democracy. It deals mainly with "low politics"; the learning and policy directions are developed in the governance network, but the decisions are embedded in representative democratic structures. Because several organizations and agencies co-own the process and are committed to the outcomes, there is a shared or extended accountability. A recent large investment in KVBR caused a major crisis at the municipal level, fueled by the financial crisis. The higher levels of the governance network, however, served as a social memory and enhanced resilience of the present biosphere development trajectory. For self-organized networks, legitimacy is the bridge between adaptability and accountability; accountability is secured as long as the

  12. Labeling of Pesticide Products under the National Organic Program

    Science.gov (United States)

    This notice describes how registrants can obtain EPA approval of label language indicating that all ingredients in a pesticide product and all uses of that pesticide meet the criteria defined in the USDA National Organic Program Rule.

  13. Greenhouse gas fluxes from agricultural soils under organic and non-organic management — A global meta-analysis

    International Nuclear Information System (INIS)

    Skinner, Colin; Gattinger, Andreas; Muller, Adrian; Mäder, Paul; Fließbach, Andreas; Stolze, Matthias; Ruser, Reiner; Niggli, Urs

    2014-01-01

    It is anticipated that organic farming systems provide benefits concerning soil conservation and climate protection. A literature search on measured soil-derived greenhouse gas (GHG) (nitrous oxide and methane) fluxes under organic and non-organic management from farming system comparisons was conducted and followed by a meta-analysis. Up to date only 19 studies based on field measurements could be retrieved. Based on 12 studies that cover annual measurements, it appeared with a high significance that area-scaled nitrous oxide emissions from organically managed soils are 492 ± 160 kg CO 2 eq. ha −1 a −1 lower than from non-organically managed soils. For arable soils the difference amounts to 497 ± 162 kg CO 2 eq. ha −1 a −1 . However, yield-scaled nitrous oxide emissions are higher by 41 ± 34 kg CO 2 eq. t −1 DM under organic management (arable and use). To equalize this mean difference in yield-scaled nitrous oxide emissions between both farming systems, the yield gap has to be less than 17%. Emissions from conventionally managed soils seemed to be influenced mainly by total N inputs, whereas for organically managed soils other variables such as soil characteristics seemed to be more important. This can be explained by the higher bioavailability of the synthetic N fertilisers in non-organic farming systems while the necessary mineralisation of the N sources under organic management leads to lower and retarded availability. Furthermore, a higher methane uptake of 3.2 ± 2.5 kg CO 2 eq. ha −1 a −1 for arable soils under organic management can be observed. Only one comparative study on rice paddies has been published up to date. All 19 retrieved studies were conducted in the Northern hemisphere under temperate climate. Further GHG flux measurements in farming system comparisons are required to confirm the results and close the existing knowledge gaps. - Highlights: • Lower area-scaled nitrous oxide emissions from soils managed organically compared

  14. 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...

  15. Feasibility of Optical Packet Switched WDM Networks without Packet Synchronisation Under Bursty Traffic Conditions

    DEFF Research Database (Denmark)

    Fjelde, Tina; Hansen, Peter Bukhave; Kloch, Allan

    1999-01-01

    We show that complex packet synchronisation may be avoided in optical packetswitched networks. Detailed traffic analysis demonstrates that packet lossratios of 1e-10 are feasible under bursty traffic conditions for a highcapacity network consisting of asynchronously operated add-drop switch...

  16. [Critical appraisal of organ procurement under Maastricht 3 condition].

    Science.gov (United States)

    Puybasset, L; Bazin, J-E; Beloucif, S; Bizouarn, P; Crozier, S; Devalois, B; Eon, B; Fieux, F; Gisquet, E; Guibet-Lafaye, C; Kentish, N; Lienhart, A; Nicolas-Robin, A; Otero Lopez, M; Pelluchon, C; Roussin, F; Beydon, L

    2012-05-01

    The ethics committee of the French Society of Anesthesia and Intensive Care (Sfar) has been requested by the French Biomedical Agency to consider the issue of organ donation in patients after a decision of withdrawing life supporting therapies has been taken. This category of organ donation is performed in the USA, Canada, United Kingdom, the Netherlands and Belgium. The three former countries have published recommendations, which formalize procedures and operations. The Sfar ethics committee has considered this issue and envisioned the different aspects of the whole process. Consequently, it sounds a note of caution regarding the applicability of this type of organ procurement in unselected patient following a decision to withdraw life supporting therapies. According to the French regulation concerning organ procurement in brain dead patients, the committee stresses the need to restrict this specific way of procurement to severely brain injured patients, once confirmatory investigations predicting a catastrophic prognosis have been performed. It suggests that the nature of the confirmatory investigation required should be formalized by the French Biomedical Agency on behalf of the French parliamentarians. This should help preserving population trust regarding organ procurement and provide a framework to medical decision. This text has been endorsed by the Sfar. Copyright © 2012. Published by Elsevier SAS.

  17. Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

    Science.gov (United States)

    Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo

    2009-08-01

    In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.

  18. Hemispheric lateralization of topological organization in structural brain networks.

    Science.gov (United States)

    Caeyenberghs, Karen; Leemans, Alexander

    2014-09-01

    The study on structural brain asymmetries in healthy individuals plays an important role in our understanding of the factors that modulate cognitive specialization in the brain. Here, we used fiber tractography to reconstruct the left and right hemispheric networks of a large cohort of 346 healthy participants (20-86 years) and performed a graph theoretical analysis to investigate this brain laterality from a network perspective. Findings revealed that the left hemisphere is significantly more "efficient" than the right hemisphere, whereas the right hemisphere showed higher values of "betweenness centrality" and "small-worldness." In particular, left-hemispheric networks displayed increased nodal efficiency in brain regions related to language and motor actions, whereas the right hemisphere showed an increase in nodal efficiency in brain regions involved in memory and visuospatial attention. In addition, we found that hemispheric networks decrease in efficiency with age. Finally, we observed significant gender differences in measures of global connectivity. By analyzing the structural hemispheric brain networks, we have provided new insights into understanding the neuroanatomical basis of lateralized brain functions. Copyright © 2014 Wiley Periodicals, Inc.

  19. 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.

  20. Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

    Science.gov (United States)

    Francis, Andrew; Moulton, Vincent

    2018-06-07

    Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. 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.

  2. Organic dairy farming in Norway under the 100% organically produced feed requirement

    OpenAIRE

    Flaten, Ola; Lien, Gudbrand

    2009-01-01

    The derogation to use a percentage of cheaper non-organic feeds in organic livestock diets for herbivores expired from January 2008. (In Norway, a maximum 15% of conventional feedstuffs per year was allowed until 24 August 2005, 5% in the interim.) This study aimed to assess changes in resource use and financial impacts for organic dairy herds of the 100% organic feeding rule (compared with 85% organic feeds) using a two-stage stochastic programming modelling framework. In this study, the obj...

  3. 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

  4. 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.

  5. 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

  6. Self organization of wireless sensor networks using ultra-wideband radios

    Science.gov (United States)

    Dowla, Farid U [Castro Valley, CA; Nekoogar, Franak [San Ramon, CA; Spiridon, Alex [Palo Alto, CA

    2009-06-16

    A novel UWB communications method and system that provides self-organization for wireless sensor networks is introduced. The self-organization is in terms of scalability, power conservation, channel estimation, and node synchronization in wireless sensor networks. The UWB receiver in the present invention adds two new tasks to conventional TR receivers. The two additional units are SNR enhancing unit and timing acquisition and tracking unit.

  7. 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.

  8. 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 ...

  9. 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.

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

    Indian Academy of Sciences (India)

    Though it is a common practice to run the organic reactions in solvent media, the ... this concept is simple. That is, the ... to vigorous research activity and reinvestigation of known reac- tions to achieve ... experimental procedure, work up technique and saving in labour. These would be ... This is true not only of the crystals of ...

  11. Maize cultivar performance under diverse organic production systems

    Science.gov (United States)

    Maize cultivar performance can vary widely among different production systems. The need for high-performing hybrids for organic systems with wide adaptation to various macroenvironments is becoming increasingly important. The goal of this study was to characterize inbred lines developed by distinc...

  12. Critical appraisal of organ procurement under Maastricht 3 condition.

    Science.gov (United States)

    Puybasset, L; Bazin, J-E; Beloucif, S; Bizouarn, P; Crozier, S; Devalois, B; Eon, B; Fieux, F; Gisquet, E; Guibet-Lafaye, C; Kentish, N; Lienhart, A; Nicolas-Robin, A; Otero Lopez, M; Pelluchon, C; Roussin, F; Beydon, L

    2014-02-01

    The ethics committee of the French Society of Anesthesia and Intensive Care (Sfar) has been requested by the French Biomedical Agency to consider the issue of organ donation in patients after the decision to withdraw life-supportive therapies has been taken. This type of organ donation is performed in the USA, Canada, the United Kingdom, the Netherlands and Belgium. The three former countries have published recommendations formalizing procedures and operations. The French Society of Anesthesia and Intensive Care (Société française d'anesthésie et de reanimation [Sfar]) ethics committee has considered this issue and envisioned the different aspects of the whole process. Consequently, it sounded a note of caution regarding the applicability of this type of organ procurement in unselected patients following a decision to withdraw life-supportive therapies. According to French regulations concerning organ procurement in brain-dead patients, the committee stresses the need to restrict this specific way of procurement to severely brain-injured patients, once confirmatory investigations predicting a catastrophic prognosis have been performed. This suggests that the nature of the confirmatory investigation required should be formalized by the French Biomedical Agency on behalf of the French parliamentarians, which should help preserve population trust regarding organ procurement and provide a framework for medical decision. This text has been endorsed by the Sfar. Copyright © 2013 Société française d’anesthésie et de réanimation (Sfar). Published by Elsevier SAS. All rights reserved.

  13. 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.

  14. Validation of organ procurement and transplant network (OPTN)/united network for organ sharing (UNOS) criteria for imaging diagnosis of hepatocellular carcinoma.

    Science.gov (United States)

    Fowler, Kathryn J; Karimova, E Jane; Arauz, Anthony R; Saad, Nael E; Brunt, Elizabeth M; Chapman, William C; Heiken, Jay P

    2013-06-27

    Imaging diagnosis of hepatocellular carcinoma (HCC) presents an important pathway for transplant exception points and priority for cirrhotic patients. The purpose of this retrospective study is to evaluate the validity of the new Organ Procurement and Transplant Network (OPTN) classification system on patients undergoing transplantation for HCC. One hundred twenty-nine patients underwent transplantation for HCC from April 14, 2006 to April 18, 2011; a total of 263 lesions were reported as suspicious for HCC on pretransplantation magnetic resonance imaging. Magnetic resonance imaging examinations were reviewed independently by two experienced radiologists, blinded to final pathology. Reviewers identified major imaging features and an OPTN classification was assigned to each lesion. Final proof of diagnosis was pathology on explant or necrosis along with imaging findings of ablation after transarterial chemoembolization. Application of OPTN imaging criteria in our population resulted in high specificity for the diagnosis of HCC. Sensitivity in diagnosis of small lesions (≥1 and based on preoperative imaging but would not have met criteria under the new system. Eleven percent of the patients not meeting OPTN criteria were found to have T2 stage tumor burden on pathology. The OPTN imaging policy introduces a high level of specificity for HCC but may decrease sensitivity for small lesions. Management may be impacted in a number of patients, potentially requiring longer surveillance periods or biopsy to confirm diagnosis.

  15. Creation, organizing and development of the French nuclear documentation network

    International Nuclear Information System (INIS)

    Vergnes, Gisele; Cheron, Christiane; Guilloux, Raymond

    1974-01-01

    This historical account covers the creation of the French nuclear documentation network, the preliminary research, aims, structures and first accomplishments of the Association Francaise de Documentation et d'Information Nucleaire (AFDIN) (French Association of Nuclear Documentation and Information) and its relations with the international system INIS [fr

  16. 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

  17. 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.

  18. Signaling mechanisms underlying the robustness and tunability of the plant immune network

    Science.gov (United States)

    Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

    2014-01-01

    Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

  19. 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.

  20. A Comparative Study of Accounting Entities Under Different Business Organizations

    Institute of Scientific and Technical Information of China (English)

    LUO Hong-lan; XU Guo-xin; FAN Jin

    2001-01-01

    In terms of accounting, all types of business enterprises regardless of their organizational form are separate accounting entities. But different types of organization forms entail remarkable differences in the establishments, legal positions, liabilities, taxation obligations and accounting practices of the business enterprises as accounting entities. A good knowledge of such difference is beneficial to the promotion of the development of all types of business enterprises in China.

  1. 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)

  2. 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

  3. 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

  4. 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.

  5. 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

  6. Soil Rhizosphere Microbial Communities and Enzyme Activities under Organic Farming

    Science.gov (United States)

    This study investigated the activities of ß-glucosidase (C cycling, ß-glucosaminidase (C and N cycling), acid phosphatase (P cycling) and arylsulfatase (S cycling) under lettuce (Lactuca sativa), potato (Solanum Tuberosum), onion (Allium cepa L), broccoli (Brassica oleracea var. botrytis) and Tall f...

  7. Exploring the patterns and evolution of self-organized urban street networks through modeling

    Science.gov (United States)

    Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

    2013-03-01

    As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

  8. Organized technology. Networks and innovation in technical systems

    International Nuclear Information System (INIS)

    Shrum, W.

    1985-01-01

    The book is based on a study of radioactive waste and solar cell research. Social network methods are used to illuminate the differences between technologies such as nuclear waste disposal, dominated by the federal government, and potentially profitable technologies such as photovoltaics, where the private sector plays a larger role. The book examines the interaction of government agencies, national laboratories, private firms, universities, regulatory agencies, Congress, and public-interest groups in the technology development process

  9. Sleeping of a Complex Brain Networks with Hierarchical Organization

    Science.gov (United States)

    Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun

    2009-01-01

    The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

  10. 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.

  11. NASCENT: an automatic protein interaction network generation tool for non-model organisms.

    Science.gov (United States)

    Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

    2009-04-24

    Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

  12. North-east transmission networks : organization and operations

    International Nuclear Information System (INIS)

    Roberge, F.

    2003-01-01

    A review of Quebec's electric power industry was presented along with an outline of non-regulated activity and regulated activities in terms of power generation, transmission, distribution and customer service. Both the transmission and distribution components of Quebec's electric power industry are regulated by the Regie de l'energie. Transmission networks offer access to all wholesalers. Hydro-Quebec TransEnergie was created in 1997 as a functionally independent open access transmission provider with high reliability standards. TransEnergie can address seams issues with neighbouring networks. The three types of services offered in terms of tariffs were also discussed along with data regarding Hydro-Quebec assets, revenue and net income. Hydro-Quebec's relation with the New Brunswick, Ontario, New York and New England were presented along with the issue of congestion and congestion costs. Congestion was defined as an incapacity to deliver energy at low cost because of a limited grid capacity, which results in a need to use more expensive energy. Solutions to decrease congestion include: building new transmission lines; using specialized equipment at existing distribution points; constructing strategically placed power generating stations; reducing the power load; and, increasing network control. The factors that influence investments in transport were also discussed. 1 tab., 9 figs

  13. Confession-building, long-distance networks, and the organization of Jesuit science.

    Science.gov (United States)

    Harris, S J

    1996-01-01

    The ability of the Society of Jesus to engage in a broad and enduring tradition of scientific activity is here addressed in terms of its programmatic commitment to the consolidation and extension of the Catholic confession (i.e., to a multipronged program of confession-building) and its mastery of the administrative apparatus necessary to operate long-distance networks. The Society's early move into two major apostolates, one in education and the other in the overseas missions, brought Jesuits into regular contact with the educated elites of Europe and at the same time placed the society's missionaries in remote parts of the natural world. The modes of organization of travel and communication required by the Society's long-distance networks (i.e., the training and deployment of reliable agents willing to work under direction in remote locations and capable of providing trustworthy reports and observations to their superiors through regular exchange of correspondence) not only facilitated scientific communication and collaboration within the order, it also provided Jesuits with the resources they needed to engage successfully in 'ministries among the learned'. Evidence of a sustained attempt by Jesuit authors to assume the role of Kulturträger is found in the several genres of scientific publications that dominate the society's scientific corpus. Thus the society's early recognition of the "apostolic value" of scientific publications in recruiting friends and allies among Europe's intellectual elites, I argue, allowed a robust interest in natural knowledge to emerge as a legitimate part of the Jesuit vocation.

  14. Extra-capacity versus protection for supply networks under attack

    International Nuclear Information System (INIS)

    Bricha, Naji; Nourelfath, Mustapha

    2014-01-01

    This article develops a game-theoretical model to deal with the protection of facilities, in the context of the capacitated fixed-charge location and capacity acquisition problem. A set of investment alternatives is available for direct protection of facilities. Furthermore, extra-capacity of neighbouring functional facilities can be used after attacks to avoid the backlog of demands and backorders. The proposed model considers a non-cooperative two-period game between the players, and an algorithm is presented to determine the equilibrium solution and the optimal defender strategy under capacity constraints. A method is developed to evaluate the utilities of the defender and the attacker. The benefit of the proposed approach is illustrated using a numerical example. The defence strategy of our model is compared to other strategies, and the obtained results clearly indicate the superiority of our model in finding the best trade-off between direct protection investment and extra-capacity deployment

  15. Beyond the network effect: towards an alternative understanding of global urban organizations

    NARCIS (Netherlands)

    James, P.; Verrest, H.; Gupta, J.; Pfeffer, K.; Verrest, H.; Ros-Tonen, M.

    2015-01-01

    Global organizations providing network relations for cities are bourgeoning. Organizations such as Metropolis, UN-Habitat, ICLEI - Local Governments for Sustainability, the Global Compact Cities Programme, and the C40, as well as City-to-City arrangements, have become increasingly important to

  16. 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.

  17. The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study

    Directory of Open Access Journals (Sweden)

    Lin Cai

    2018-04-01

    Full Text Available Early childhood (7–8 years old and early adolescence (11–12 years old constitute two landmark developmental stages that comprise considerable changes in neural cognition. However, very limited information from functional neuroimaging studies exists on the functional topological configuration of the human brain during specific developmental periods. In the present study, we utilized continuous resting-state functional near-infrared spectroscopy (rs-fNIRS imaging data to examine topological changes in network organization during development from early childhood and early adolescence to adulthood. Our results showed that the properties of small-worldness and modularity were not significantly different across development, demonstrating the developmental maturity of important functional brain organization in early childhood. Intriguingly, young children had a significantly lower global efficiency than early adolescents and adults, which revealed that the integration of the distributed networks strengthens across the developmental stages underlying cognitive development. Moreover, local efficiency of young children and adolescents was significantly lower than that of adults, while there was no difference between these two younger groups. This finding demonstrated that functional segregation remained relatively steady from early childhood to early adolescence, and the brain in these developmental periods possesses no optimal network configuration. Furthermore, we found heterogeneous developmental patterns in the regional nodal properties in various brain regions, such as linear increased nodal properties in the frontal cortex, indicating increasing cognitive capacity over development. Collectively, our results demonstrated that significant topological changes in functional network organization occurred during these two critical developmental stages, and provided a novel insight into elucidating subtle changes in brain functional networks across

  18. 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

  19. Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks.

    Science.gov (United States)

    Gorochowski, Thomas E; Grierson, Claire S; di Bernardo, Mario

    2018-03-01

    Network motifs are significantly overrepresented subgraphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue, we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organization. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network of Escherichia coli . Our findings have implications for understanding how networked systems are constructed from motif parts and elucidate constraints that guide their evolution.

  20. Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus.

    Science.gov (United States)

    Shi, Yulin; Ikrar, Taruna; Olivas, Nicholas D; Xu, Xiangmin

    2014-06-15

    Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

  1. Altered organization of face processing networks in temporal lobe epilepsy

    Science.gov (United States)

    Riley, Jeffrey D.; Fling, Brett W.; Cramer, Steven C.; Lin, Jack J.

    2015-01-01

    SUMMARY Objective Deficits in social cognition are common and significant in people with temporal lobe epilepsy (TLE), but the functional and structural underpinnings remain unclear. The present study investigated how the side of seizure focus impacts face processing networks in temporal lobe epilepsy. Methods We used functional magnetic resonance imaging (fMRI) of a face processing paradigm to identify face responsive regions in 24 individuals with unilateral temporal lobe epilepsy (Left = 15; Right = 9) and 19 healthy controls. fMRI signals of face responsive regions ispilateral and contralateral to the side of seizure onset were delineated in TLE and compared to the healthy controls with right and left side combined. Diffusion tensor images were acquired to investigate structural connectivity between face regions that differed in fMRI signals between the two groups. Results In temporal lobe epilepsy, activation of the cortical face processing networks varied according to side of seizure onset. In temporal lobe epilepsy, the laterality of amygdala activation was shifted to the side contralateral to the seizure focus while controls showed no significant asymmetry. Furthermore, compared to controls, patients with TLE showed decreased activation of the occipital face responsive region in the ipsilateral side and an increased activity of the anterior temporal lobe in the contralateral side to the seizure focus. Probabilistic tractography revealed that the occipital face area and anterior temporal lobe are connected via the inferior longitudinal fasciculus, which in individuals with temporal lobe epilepsy showed reduced integrity. Significance Taken together, these findings suggest that brain function and white matter integrity of networks subserving face processing are impaired on the side of seizure onset, accompanied by altered responses on the side contralateral to the seizure. PMID:25823855

  2. 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.

  3. 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

  4. 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

  5. The role of gender in social network organization

    DEFF Research Database (Denmark)

    Psylla, Ioanna; Sapiezynski, Piotr; Mones, Enys

    2017-01-01

    interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders...... are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual's characteristics and social behavior reveals their gender by posing...

  6. Functional organization of the language network in three- and six-year-old children.

    Science.gov (United States)

    Vissiennon, Kodjo; Friederici, Angela D; Brauer, Jens; Wu, Chiao-Yi

    2017-04-01

    The organization of the language network undergoes continuous changes during development as children learn to understand sentences. In the present study, functional magnetic resonance imaging and behavioral measures were utilized to investigate functional activation and functional connectivity (FC) in three-year-old (3yo) and six-year-old (6yo) children during sentence comprehension. Transitive German sentences varying the word order (subject-initial and object-initial) with case marking were presented auditorily. We selected children who were capable of processing the subject-initial sentences above chance level accuracy from each age group to ensure that we were tapping real comprehension. Both age groups showed a main effect of word order in the left posterior superior temporal gyrus (pSTG), with greater activation for object-initial compared to subject-initial sentences. However, age differences were observed in the FC between left pSTG and the left inferior frontal gyrus (IFG). The 6yo group showed stronger FC between the left pSTG and Brodmann area (BA) 44 of the left IFG compared to the 3yo group. For the 3yo group, in turn, the FC between left pSTG and left BA 45 was stronger than with left BA 44. Our study demonstrates that while task-related activation was comparable, the small behavioral differences between age groups were reflected in the underlying functional organization revealing the ongoing development of the neural language network. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

    DEFF Research Database (Denmark)

    Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

    2013-01-01

    Epidemics theory has been used in different contexts in order to describe the propagation of diseases, human interactions or natural phenomena. In computer science, virus spreading has been also characterized using epidemic models. Although in the past the use of epidemic models...... 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...

  8. 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.

  9. 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...

  10. Comparative, Population-Level Analysis of Social Networks in Organizations

    Science.gov (United States)

    Jacobs, Abigail Z.

    2017-01-01

    As social behavior moves increasingly online, the study of social behavior has followed. Online traces of social systems, whether to study online behavior directly or the online traces of offline activity, have made possible previously unavailable empirical analyses of people, groups and organizations. However, practically observing any social…

  11. Paper 1: The EUROCAT network--organization and processes

    DEFF Research Database (Denmark)

    Boyd, Patricia A; Haeusler, Martin; Barisic, Ingeborg

    2011-01-01

    . The monitoring of new developments in prenatal diagnosis, medication during pregnancy, use of folic acid, and investigation of clusters and exposures are overseen by working groups responsible for organizing research and producing regular reports. The EUROCAT Web site includes current data on prevalence rates...

  12. Cultural intelligence and network organizations in society: Case of Tehran neighborhood councils

    Directory of Open Access Journals (Sweden)

    Salamzadeh Yashar

    2016-01-01

    Full Text Available Network communications is one of the modern ideas in the field of organizational behavior. On the other hand, the ability to communicate with employees and understand the cultural differences between them in a multicultural environment is one of the key skills that managers and employees need them in the nowadays organizations. These skills are introduced as cultural intelligence in organizations that have ability to respond to many challenges in multicultural environments. This article was aimed to analysis the relationship between cultural intelligence and network communication. These questionnaires were distributed between 134 members at the Tehran neighborhood councils. In order to analyzing data and concluding results, SPSS, and then Pearson correlation test were used. The research was done based on structural equation modeling (SEM. The result indicated that there was significant positive relationship between cultural intelligence and network communication. Also there was significant positive relationship between each dimension of cultural intelligence and network communication. Findings show that cultural intelligence is a basic factor in network communication and confirm the main hypothesis of this study which represents the existence of a positive and meaningful relation between cultural intelligence and network communication. Furthermore, the results show that considering this kind of intelligence, especially in network organizations which has a high ethnic and cultural variety, could be very useful for improve employees and managers communications.

  13. Capacity planning of link restorable optical networks under dynamic change of traffic

    Science.gov (United States)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2005-11-01

    Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.

  14. 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.

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

    Science.gov (United States)

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

    2015-08-01

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

  16. Intra-Organizational Two-Mode Networks Analysis of a Public Organization

    Directory of Open Access Journals (Sweden)

    Anna Ujwary-Gil

    2017-10-01

    Full Text Available The article focuses on the analysis of intra-organizational and two-mode networks of knowledge, resources and tasks. Each of these networks consists of a human and non-human actor in the terminology of the actor-network theory (ANT, or of only non-human actors. This type of research is rare in the theory of organization and management, even though the first article on meta-networks dates back to nearly two decades ago (Krackhardt & Carley, 1998. The article analyses the prominences and ties between particular network nodes (actors, knowledge, resources and tasks, assessing their effective use in an organization. The author selected a public organization operating in the university education sector, where saturation with communication, resource and knowledge-sharing are relatively high. The application of the network analysis provides a totally different perspective on an organization, taking into account the inter-relationship, which allows a holistic (complex outlook on the analyzed object. Especially, as it measures particular nodes as related to one another, not as isolated variables, as in classical research, where observations are independent.

  17. 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...

  18. 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)

  19. Mechanisms underlying the organizer formation in Bufo arenarum embryos.

    Science.gov (United States)

    Manes, M E; Nieto, O L

    1989-06-01

    In the early gastrula of Bufo arenarum the prospective mesoderm was previously identified as a marginal belt of grey cells. To analyze their differentiation capacity explants of these cells were cultured within ectodermal vesicles, in isolation and in combination with vegetal components. When cultured in isolation, dorsal and ventral fragments from the deep marginal zone behaved differently. Whilst ventral explants produced blood cells, dorsal explants failed to differentiate, remaining as masses of yolk-laden cells. On the other hand, both cultures were drastically modified when associated with superficial cells from the blastoporal zone, which caused the following effects: a) Promotion of differentiation in dorsal marginal explants, able now to produce notochordal and somitic structures, in addition to mesenchymatic cells. b) Promotion of dorsalization in ventral marginal explants, which changed their expected destiny developing axial components, similar to those furnished by "activated" dorso marginal explants. On the contrary, combined cultures of animal and vegetal pieces were unable to generate mesodermal structures. These studies suggest that the axial mesoderm, identified as the "organizer", develops from a marginal substrate of genuine mesodermal cells through a dorsalizing inductive stimulus originated in superficial periblastoporal cells.

  20. Italian public health care organizations: specialization, institutional deintegration, and public networks relationships.

    Science.gov (United States)

    Del Vecchio, Mario; De Pietro, Carlo

    2011-01-01

    The Italian National Health Service (INHS) has undergone profound changes over the past three decades. With establishment of the INHS in 1978--a tax-based public health care system with universal coverage--one of the underlying principles was integration. The recognition of health and health care as requiring integrated answers led to the creation of a single public organization, the Local Health Unit, responsible for the health status of the population of its catchment area. At the beginning of the 1990s, the scenario radically changed. The creation of hospital trusts, the development of quasi-market mechanisms and management control tools, the adoption of a prospective payment system for reimbursing health care providers--all were signs of deintegration and institutional unbundling. Two structural changes have deeply sustained this deintegration: patients' empowerment and the increased possibilities for outsourcing practices. In more recent years, a new reintegration effort has occurred, often led by regional governments and based on institutional cooperation and network relationships. However, the earlier structural changes require innovative approaches and solutions if public health care organizations want to retain their leading role.

  1. Behaviour of organic iodides under pwr accident conditions

    International Nuclear Information System (INIS)

    Alm, M.

    1982-01-01

    Laboratory experiments were performed to study the behaviour of radioactive methyl iodide under PWR loss-of-coolant conditions. The pressure relief equipment consisted of an autoclave for simulating the primary circuit and of an expansion vessel for simulating the conditions after a rupture in the reactor coolant system. After pressure relief, the composition of the CH 3 sup(127/131)I-containing steam-air mixture within the expansion vessel was analysed at 80 0 C over a period of 42 days. On the basis of the values measured and of data taken from the literature, both qualitative and quantitative assessments have been made as to the behaviour of radioactive methyl iodide in the event of loss-of-coolant accidents. (author)

  2. Experiments regarding organism behaviour under deuterium-depleted water influence

    International Nuclear Information System (INIS)

    Stefanescu, I.; Steflea, D.; Titescu, Gh.

    1999-01-01

    Deuterium-depleted water (DDW) is water that has an deuterium content D/(D+H) lower than 145 ppm. The role of naturally occurring D in living organisms was examined by using DDW instead of natural water. The DDW significantly decreased the growth rate of the L 929 fibroblast cell line and also inhibited the tumour growth. These suggest that the naturally occurring D has a central role in signal transduction involved in cell cycle regulation. Beginning with 1996, Institute of Cryogenics and Isotopic Separation, a DDW producer, co-operated with Romanian specialized institutes for evaluation of biological effects of DDW. These investigation lead to the following conclusions: 1. DDW caused a tendency of increasing the basal tone, accompanied by intensification of vasoconstrictor effects of phenylephrine, noradrenaline and angiotensin; the increase of the basal tone and vascular reactivity produced by DDW persists after removing the vascular in endothelium. 2. DDW stimulates immunodefence reactions, represented by the opsonic, bactericidal and phagocyte capacity of the immune system, together with increase in the number of polymorphonuclear neutrophils. 3. Animals treated with DDW showed an increase of the resistance both to the sublethal and to lethal gamma radiation doses, suggesting a radioprotective action. 4. Investigation regarding artificial reproduction of fish with DDW fecundated solutions confirmed favourable influence both in embryo growth stage and resistance in the following growing stages. 5. It was studied germination, growth and quantitative character variability of two genotypes of Avena Sativa; one can remark the favourable influence of DDW on biological process in plants in various ontogenetic stages. (authors)

  3. Experiments regarding organism's behaviour under deuterium-depleted water influence

    International Nuclear Information System (INIS)

    Stefanescu, I.; Steflea, D.; Titescu, Gh.

    1999-01-01

    Deuterium-depleted water (DDW) has an isotopic content smaller than 45 ppm D/(D+H). The role of naturally occurring D in living organisms was examined by using DDW instead of natural water. The DDW significantly decreased the growth rate of the L929 fibroblast cell line, and also inhibited the tumour growth. These suggest that the naturally occurring D has a central role in signal transduction involved in cell cycle regulation. Beginning with 1996 the Institute of Cryogenics and Isotope Separation, DDW producer, co-operated with Romanian specialised institutes for biological effect's evaluation of DDW. These investigations led to the following conclusions: - DDW caused a tendency of increasing the basal tone, accompanied by the intensification of the vasoconstrictor effects of phenylefrine, noradrenaline and angiotensin; the increase of the basal tone and vascular reactivity produced by the DDW persists after the removal of the vascular endothelium. - DDW stimulates immune defence reactions, represented by the opsonic, bactericidal and phagocyte capacity of the immune system, together with increase in the numbers of polymorphonuclear neutrophils. - Animals treated with DDW showed an increase of the resistance both to sublethal and to lethal gamma radiation doses, suggesting a radioprotective action. - Investigation regarding artificial reproduction of fish with DDW fecundated solutions confirmed favourable influence both in embryo growth stage and in resistance in the following growth stages. - One has studied germination growth and quantitative character's variability at two genotypes of Avena Sativa; one can remark the favourable influence of DDW on biological process at plants in various ontogenic stages. (authors)

  4. Congenital Heart Information Network

    Science.gov (United States)

    ... heart defects. Important Notice The Congenital Heart Information Network website is temporarily out of service. Please join ... and Uwe Baemayr for The Congenital Heart Information Network Exempt organization under Section 501(c)3. Copyright © ...

  5. Greenhouse gas fluxes from agricultural soils under organic and non-organic management — A global meta-analysis

    Energy Technology Data Exchange (ETDEWEB)

    Skinner, Colin, E-mail: colin.skinner@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Gattinger, Andreas, E-mail: andreas.gattinger@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Muller, Adrian, E-mail: adrian.mueller@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Mäder, Paul, E-mail: paul.maeder@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Fließbach, Andreas, E-mail: andreas.fliessbach@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Stolze, Matthias, E-mail: matthias.stolze@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland); Ruser, Reiner, E-mail: reiner.ruser@uni-hohenheim.de [Fertilisation and Soil Matter Dynamics (340i), Institute of Crop Science, University of Hohenheim, Fruwirthstraße 20, 70599 Stuttgart (Germany); Niggli, Urs, E-mail: urs.niggli@fibl.org [Research Institute of Organic Agriculture (FiBL), Ackerstrasse 21, 5070 Frick (Switzerland)

    2014-01-01

    It is anticipated that organic farming systems provide benefits concerning soil conservation and climate protection. A literature search on measured soil-derived greenhouse gas (GHG) (nitrous oxide and methane) fluxes under organic and non-organic management from farming system comparisons was conducted and followed by a meta-analysis. Up to date only 19 studies based on field measurements could be retrieved. Based on 12 studies that cover annual measurements, it appeared with a high significance that area-scaled nitrous oxide emissions from organically managed soils are 492 ± 160 kg CO{sub 2} eq. ha{sup −1} a{sup −1} lower than from non-organically managed soils. For arable soils the difference amounts to 497 ± 162 kg CO{sub 2} eq. ha{sup −1} a{sup −1}. However, yield-scaled nitrous oxide emissions are higher by 41 ± 34 kg CO{sub 2} eq. t{sup −1} DM under organic management (arable and use). To equalize this mean difference in yield-scaled nitrous oxide emissions between both farming systems, the yield gap has to be less than 17%. Emissions from conventionally managed soils seemed to be influenced mainly by total N inputs, whereas for organically managed soils other variables such as soil characteristics seemed to be more important. This can be explained by the higher bioavailability of the synthetic N fertilisers in non-organic farming systems while the necessary mineralisation of the N sources under organic management leads to lower and retarded availability. Furthermore, a higher methane uptake of 3.2 ± 2.5 kg CO{sub 2} eq. ha{sup −1} a{sup −1} for arable soils under organic management can be observed. Only one comparative study on rice paddies has been published up to date. All 19 retrieved studies were conducted in the Northern hemisphere under temperate climate. Further GHG flux measurements in farming system comparisons are required to confirm the results and close the existing knowledge gaps. - Highlights: • Lower area-scaled nitrous

  6. The role of gender in social network organization

    DEFF Research Database (Denmark)

    Psylla, Ioanna; Sapiezynski, Piotr; Mones, Enys

    2017-01-01

    in isolation. Here we use a dataset of high resolution data collected using mobile phones, as well as detailed questionnaires, to study gender differences in a large cohort. We consider mobility behavior and individual personality traits among a group of more than 800 university students. We also investigate...... interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders...... are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual's characteristics and social behavior reveals their gender by posing...

  7. 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...

  8. A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

    Science.gov (United States)

    Puchaty, Ethan M.

    In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

  9. A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Bian Changzhi

    2015-01-01

    Full Text Available This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the improved network under all scenarios of uncertain demand. The proposed model generates globally near-optimal Pareto solutions for network configurations based on the Monte Carlo simulation and nondominated sorting genetic algorithms II. Numerical experiments implemented on Nguyen-Dupuis test network show trade-offs among construction cost, the expectation, and standard deviation of total travel time under uncertainty are obvious. Investment on transportation facilities is an efficient method to improve the network performance and reduce risk under demand uncertainty, but it has an obvious marginal decreasing effect.

  10. 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

  11. Dynamics of the cell-cycle network under genome-rewiring perturbations

    International Nuclear Information System (INIS)

    Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna

    2013-01-01

    The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes

  12. DESYNC: Self-Organizing Desynchronization and TDMA on Wireless Sensor Networks

    OpenAIRE

    Degesys, Julius; Rose, Ian; Patel, Ankit; Nagpal, Radhika

    2006-01-01

    Desynchronization is a novel primitive for sensor networks: it implies that nodes perfectly interleave periodic events to occur in a round-robin schedule. This primitive can be used to evenly distribute sampling burden in a group of nodes, schedule sleep cycles, or organize a collision-free TDMA schedule for transmitting wireless messages. Here we present Desync, a biologically-inspired self-maintaining algorithm for desynchronization in a single-hop network. We present (1) theoretical result...

  13. The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study.

    Science.gov (United States)

    Cai, Lin; Dong, Qi; Niu, Haijing

    2018-04-01

    Early childhood (7-8 years old) and early adolescence (11-12 years old) constitute two landmark developmental stages that comprise considerable changes in neural cognition. However, very limited information from functional neuroimaging studies exists on the functional topological configuration of the human brain during specific developmental periods. In the present study, we utilized continuous resting-state functional near-infrared spectroscopy (rs-fNIRS) imaging data to examine topological changes in network organization during development from early childhood and early adolescence to adulthood. Our results showed that the properties of small-worldness and modularity were not significantly different across development, demonstrating the developmental maturity of important functional brain organization in early childhood. Intriguingly, young children had a significantly lower global efficiency than early adolescents and adults, which revealed that the integration of the distributed networks strengthens across the developmental stages underlying cognitive development. Moreover, local efficiency of young children and adolescents was significantly lower than that of adults, while there was no difference between these two younger groups. This finding demonstrated that functional segregation remained relatively steady from early childhood to early adolescence, and the brain in these developmental periods possesses no optimal network configuration. Furthermore, we found heterogeneous developmental patterns in the regional nodal properties in various brain regions, such as linear increased nodal properties in the frontal cortex, indicating increasing cognitive capacity over development. Collectively, our results demonstrated that significant topological changes in functional network organization occurred during these two critical developmental stages, and provided a novel insight into elucidating subtle changes in brain functional networks across development. Copyright

  14. Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children.

    Science.gov (United States)

    Wen, Hongwei; Liu, Yue; Rekik, Islem; Wang, Shengpei; Zhang, Jishui; Zhang, Yue; Peng, Yun; He, Huiguang

    2017-08-01

    Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017

  15. 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

  16. 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.

  17. 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.

  18. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

    Directory of Open Access Journals (Sweden)

    Guihua Jiang

    Full Text Available Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs and 15 age-, gender-matched normal controls (NCs were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  19. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

    Science.gov (United States)

    Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

    2013-01-01

    Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  20. Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence

    OpenAIRE

    Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C.; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

    2013-01-01

    Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then ...

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

    International Nuclear Information System (INIS)

    Zhang Guiqing; Yang Qiuying; Chen Tianlun

    2008-01-01

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

  2. 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.

  3. Prediction of ozone tropospheric degradation rate constant of organic compounds by using artificial neural networks

    International Nuclear Information System (INIS)

    Fatemi, M.H.

    2006-01-01

    Ozone tropospheric degradation of organic compound is very important in environmental chemistry. The lifetime of organic chemicals in the atmosphere can be calculated from the knowledge of the rate constant of their reaction with free radicals such as OH and NO 3 or O 3 . In the present work, the rate constant for the tropospheric degradation of 137 organic compounds by reaction with ozone, the least widely and successfully modeled degradation process, are predicted by quantitative structure activity relationships modeling based on a variety of theoretical descriptors, which screened and selected by genetic algorithm variable subset selection procedure. These descriptors which can be used as inputs for generated artificial neural networks are; HOMO-LUMO gap, number of double bonds, number of single bonds, maximum net charge on C atom, minimum (>0.1) bond order of C atom and Minimum e-e repulsion of H atom. After generation, optimization and training of artificial neural network, network was used for the prediction of log KO 3 for the validation set. The root mean square error for the neural network calculated log KO 3 for training, prediction and validation set are 0.357, 0.460 and 0.481, respectively, which are smaller than those obtained by multiple linear regressions model (1.217, 0.870 and 0.968, respectively). Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ozone tropospheric degradations rate constant of organic compounds

  4. 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.

  5. 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.

  6. 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.

  7. 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)

  8. Multirelational organization of large-scale social networks in an online world.

    Science.gov (United States)

    Szell, Michael; Lambiotte, Renaud; Thurner, Stefan

    2010-08-03

    The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a nonlinear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multidimensional nature of these interactions has largely been ignored, mostly because of lack of data. Here, for the first time, we analyze a complete, multirelational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering, and fatter-tail degree distribution. We then explore how the interdependence of different network types determines the organization of the social system. In particular, we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach, we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.

  9. 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

  10. 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

  11. 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

  12. 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…

  13. 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.

  14. 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.

  15. Organized mesoporous silica films as templates for the elaboration of organized nanoparticle networks

    International Nuclear Information System (INIS)

    Gacoin, T; Besson, S; Boilot, J P

    2006-01-01

    Tremendous work achieved in the last 20 years on nanoparticle synthesis has allowed us to study many new physical properties that are found in the nanometre size range. New developments are now expected when considering assemblies of nanoparticles such as 2D or 3D organized arrays. These systems are indeed expected to exhibit original physical properties resulting from particle-particle interactions. Studies in this field are clearly dependent on the elaboration of materials with controlled particle size, organization and interparticle distance. This paper presents a strategy of elaboration that is based on the use of organized mesoporous silica films as templates. These films are made by sol-gel polymerization around surfactant assemblies and further elimination of the surfactant. This provides porous matrices with a pore organization that is the almost perfect replica of the initial micellar structure. The use of such films for the elaboration of organized arrays of nanoparticles is detailed in the case of CdS and Ag particles. The formation of particles inside the pores is achieved through impregnation with precursors that are allowed to diffuse inside the pores. This leads to particles with a size and a spatial arrangement that is directly related to the initial pore structure of the films. This process opens a wide range of investigations due to the relative ease of fabrication over large surfaces and the numerous possibilities offered by the elaboration of porous films with different pore sizes and organizations

  16. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment.

    Science.gov (United States)

    Yi, Li-Ye; Liang, Xia; Liu, Da-Ming; Sun, Bo; Ying, Sun; Yang, Dong-Bo; Li, Qing-Bin; Jiang, Chuan-Lu; Han, Ying

    2015-10-01

    Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown. We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks. Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients. Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI. © 2015 John Wiley & Sons Ltd.

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

    Science.gov (United States)

    Qiu, Xiangzhe; Zhang, Yanjun; Feng, Hongbo; Jiang, Donglang

    2016-01-01

    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 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 characteristic 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 functional evidence for the abnormalities of brain networks in DM.

  18. 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.

  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. 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.

  1. Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

    Science.gov (United States)

    Ramírez, Carlos; Mendoza, Luis

    2018-04-01

    Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

  2. 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.

  3. ICoNOs MM: The IT-enabled Collaborative Networked Organizations Maturity Model

    NARCIS (Netherlands)

    Santana Tapia, R.G.

    2009-01-01

    The focus of this paper is to introduce a comprehensive model for assessing and improving maturity of business-IT alignment (B-ITa) in collaborative networked organizations (CNOs): the ICoNOs MM. This two dimensional maturity model (MM) addresses five levels of maturity as well as four domains to

  4. 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

  5. Metal–organic covalent network chemical vapor deposition for gas separation

    NARCIS (Netherlands)

    Boscher, N.D.; Wang, M.; Perrotta, A.; Heinze, K.; Creatore, A.; Gleason, K.K.

    2016-01-01

    The chemical vapor deposition (CVD) polymerization of metalloporphyrin building units is demonstrated to provide an easily up-scalable one-step method toward the deposition of a new class of dense and defect-free metal–organic covalent network (MOCN) layers. The resulting hyper-thin and flexible

  6. 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

  7. 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…

  8. Self-Organization Scheme for Balanced Routing in Large-Scale Multi-Hop Networks

    DEFF Research Database (Denmark)

    Badiu, Mihai Alin; Saad, David; Coon, Justin P.

    2018-01-01

    We propose a self-organization scheme for cost-effective and load-balanced routing in multi-hop networks. To avoid overloading nodes that provide favourable routing conditions, we assign each node with a cost function that penalizes high loads. Thus, finding routes to sink nodes is formulated...

  9. 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

    (Cunningham 2006; Findley and Rudloff 2012). Building on network science and spatial analysis, the overall objective of this chapter is to bridge these strands of literature and lay the foundations for a more formal approach to social and spatial networks of belligerents in the region. Examining...... 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...... 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...

  10. Effect of organic matter on the uptake of phosphorus by rice plants under different moisture conditions

    International Nuclear Information System (INIS)

    Ghosh, Geetanjali

    1974-01-01

    In studies on the effect of three levels of moisture and two levels of organic matter in two alluvial soils, the uptake of P by rice plant both from soil and fertilizer sources was the highest and Eh the lowest under submerged conditions. No marked difference in total uptake of P was observed in upland and alternate submerged condition; organic matter application showed an appreciable effect under submerged condition. (author)

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

    Science.gov (United States)

    Bzdok, Danilo; Varoquaux, Gaël; Grisel, Olivier; Eickenberg, Michael; Poupon, Cyril; Thirion, Bertrand

    2016-06-01

    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.

  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. 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

  14. A method for under-sampled ecological network data analysis: plant-pollination as case study

    Directory of Open Access Journals (Sweden)

    Peter B. Sorensen

    2012-01-01

    Full Text Available In this paper, we develop a method, termed the Interaction Distribution (ID method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1, pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2, qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.

  15. Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

    Science.gov (United States)

    Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

    2012-01-01

    The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

  16. 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.

  17. Structural characterization of PTX3 disulfide bond network and its multimeric status in cumulus matrix organization.

    Science.gov (United States)

    Inforzato, Antonio; Rivieccio, Vincenzo; Morreale, Antonio P; Bastone, Antonio; Salustri, Antonietta; Scarchilli, Laura; Verdoliva, Antonio; Vincenti, Silvia; Gallo, Grazia; Chiapparino, Caterina; Pacello, Lucrezia; Nucera, Eleonora; Serlupi-Crescenzi, Ottaviano; Day, Anthony J; Bottazzi, Barbara; Mantovani, Alberto; De Santis, Rita; Salvatori, Giovanni

    2008-04-11

    PTX3 is an acute phase glycoprotein that plays key roles in resistance to certain pathogens and in female fertility. PTX3 exerts its functions by interacting with a number of structurally unrelated molecules, a capacity that is likely to rely on its complex multimeric structure stabilized by interchain disulfide bonds. In this study, PAGE analyses performed under both native and denaturing conditions indicated that human recombinant PTX3 is mainly composed of covalently linked octamers. The network of disulfide bonds supporting this octameric assembly was resolved by mass spectrometry and Cys to Ser site-directed mutagenesis. Here we report that cysteine residues at positions 47, 49, and 103 in the N-terminal domain form three symmetric interchain disulfide bonds stabilizing four protein subunits in a tetrameric arrangement. Additional interchain disulfide bonds formed by the C-terminal domain cysteines Cys(317) and Cys(318) are responsible for linking the PTX3 tetramers into octamers. We also identified three intrachain disulfide bonds within the C-terminal domain that we used as structural constraints to build a new three-dimensional model for this domain. Previously it has been shown that PTX3 is a key component of the cumulus oophorus extracellular matrix, which forms around the oocyte prior to ovulation, because cumuli from PTX3(-/-) mice show defective matrix organization. Recombinant PTX3 is able to restore the normal phenotype ex vivo in cumuli from PTX3(-/-) mice. Here we demonstrate that PTX3 Cys to Ser mutants, mainly assembled into tetramers, exhibited wild type rescue activity, whereas a mutant, predominantly composed of dimers, had impaired functionality. These findings indicate that protein oligomerization is essential for PTX3 activity within the cumulus matrix and implicate PTX3 tetramers as the functional molecular units required for cumulus matrix organization and stabilization.

  18. Learning gene networks under SNP perturbations using eQTL datasets.

    Directory of Open Access Journals (Sweden)

    Lingxue Zhang

    2014-02-01

    Full Text Available The standard approach for identifying gene networks is based on experimental perturbations of gene regulatory systems such as gene knock-out experiments, followed by a genome-wide profiling of differential gene expressions. However, this approach is significantly limited in that it is not possible to perturb more than one or two genes simultaneously to discover complex gene interactions or to distinguish between direct and indirect downstream regulations of the differentially-expressed genes. As an alternative, genetical genomics study has been proposed to treat naturally-occurring genetic variants as potential perturbants of gene regulatory system and to recover gene networks via analysis of population gene-expression and genotype data. Despite many advantages of genetical genomics data analysis, the computational challenge that the effects of multifactorial genetic perturbations should be decoded simultaneously from data has prevented a widespread application of genetical genomics analysis. In this article, we propose a statistical framework for learning gene networks that overcomes the limitations of experimental perturbation methods and addresses the challenges of genetical genomics analysis. We introduce a new statistical model, called a sparse conditional Gaussian graphical model, and describe an efficient learning algorithm that simultaneously decodes the perturbations of gene regulatory system by a large number of SNPs to identify a gene network along with expression quantitative trait loci (eQTLs that perturb this network. While our statistical model captures direct genetic perturbations of gene network, by performing inference on the probabilistic graphical model, we obtain detailed characterizations of how the direct SNP perturbation effects propagate through the gene network to perturb other genes indirectly. We demonstrate our statistical method using HapMap-simulated and yeast eQTL datasets. In particular, the yeast gene network

  19. 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...

  20. Molecular System Dynamics for Self-Organization in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Milner StuartD

    2010-01-01

    Full Text Available We have been looking at the properties of physical configurations that occur in nature in order to characterize, predict, and control network robustness in dynamic communication networks. Our framework is based on the definition of a potential energy function to characterize robustness in communication networks and the study of first- and second-order variations of the potential energy to provide prediction and control strategies for network-performance optimization. This paper describes novel investigations within this framework that draw from molecular system dynamics. The Morse potential, which governs the energy stored in bonds within molecules, is considered for the characterization of the potential energy of communication links in the presence of physical constraints such as the power available at the transmitters in a network. The inclusion of the Morse potential translates into improved control strategies, where forces on network nodes drive the release, retention, or reconfiguration of communication links based on their role within the network architecture. The performance of the proposed approach is measured in terms of the number of source-to-destination connections that have an end-to-end communications path. Simulation results show the effectiveness of our control mechanism, where the physical topology reorganizes to maximize the number of source-to-destination communicating pairs. The algorithms developed are completely distributed, show constant time complexity and produce optimal solutions from local interactions, thus preserving the system's self-organizing capability.

  1. 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)

  2. Dynamics of Intracellular Polymers in Enhanced Biological Phosphorus Removal Processes under Different Organic Carbon Concentrations

    Directory of Open Access Journals (Sweden)

    Lizhen Xing

    2013-01-01

    Full Text Available 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.

  3. 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

  4. 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.

  5. 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

  6. What is the energy policy-planning network and who dominates it?: A network and QCA analysis of leading energy firms and organizations

    International Nuclear Information System (INIS)

    Crawford, Seth

    2012-01-01

    This study examines the structure of the energy industry and the energy policy-planning network (EPPN). I use cross-sectional director interlocks from 2002 to examine the social networks amongst a sample of the largest energy firms, between these firms and the EPPN, and to calculate relative network centrality measures for the firms. I then use qualitative comparative analysis (QCA) to isolate specific combinations of energy firm attributes that are associated with network position. I find that the energy industry has several key intra-firm interlocks that link dominant companies to each other and that the industry is well represented on the boards of EPPN organizations. Additionally, several dominant energy firms provide links between ultra-conservative and moderate policy development organizations. Finally, QCA models suggest that firms with many employees, high revenue, and who produce oil are most likely to hold prominent positions in the EPPN—though above average political campaign contributions offer an alternative path into the network. - Highlights: ► Identifies organizations in the Energy Policy-Planning Network (EPPN). ► Examines measures of network association between EPPN organizations and energy firms. ► Isolates key attributes of energy firms who are highly embedded within the EPPN. ► Large, oil producing firms hold key positions in the network. ► EPPN organizations act as a bridge between many firms, linking them indirectly.

  7. 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.

  8. 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.

  9. 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.

  10. Emergence of amplitude death scenario in a network of oscillators under repulsive delay interaction

    International Nuclear Information System (INIS)

    Bera, Bidesh K.; Hens, Chittaranjan; Ghosh, Dibakar

    2016-01-01

    Highlights: • Amplitude death is observed using repulsive mean coupling. • Analytical conditions for amplitude death are derived. • Effect of asymmetry time delay coupling for death is discussed. - Abstract: We report the existence of amplitude death in a network of identical oscillators under repulsive mean coupling. Amplitude death appears in a globally coupled network of identical oscillators with instantaneous repulsive mean coupling only when the number of oscillators is more than two. We further investigate that, amplitude death may emerge even in two coupled oscillators as well as network of oscillators if we introduce delay time in the repulsive mean coupling. We have analytically derived the region of amplitude death island and find out how strength of delay controls the death regime in two coupled or a large network of coupled oscillators. We have verified our results on network of delayed Mackey–Glass systems where parameters are set in hyperchaotic regime. We have also tested our coupling approach in two paradigmatic limit cycle oscillators: Stuart–Landau and Van der Pol oscillators.

  11. Emergence of amplitude death scenario in a network of oscillators under repulsive delay interaction

    Energy Technology Data Exchange (ETDEWEB)

    Bera, Bidesh K., E-mail: bideshbera18@gmail.com [Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108 (India); Hens, Chittaranjan, E-mail: chittaranjanhens@gmail.com [Department of Mathematics, Bar-Ilan University, Ramat Gan 52900 (Israel); Ghosh, Dibakar, E-mail: dibakar@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108 (India)

    2016-07-15

    Highlights: • Amplitude death is observed using repulsive mean coupling. • Analytical conditions for amplitude death are derived. • Effect of asymmetry time delay coupling for death is discussed. - Abstract: We report the existence of amplitude death in a network of identical oscillators under repulsive mean coupling. Amplitude death appears in a globally coupled network of identical oscillators with instantaneous repulsive mean coupling only when the number of oscillators is more than two. We further investigate that, amplitude death may emerge even in two coupled oscillators as well as network of oscillators if we introduce delay time in the repulsive mean coupling. We have analytically derived the region of amplitude death island and find out how strength of delay controls the death regime in two coupled or a large network of coupled oscillators. We have verified our results on network of delayed Mackey–Glass systems where parameters are set in hyperchaotic regime. We have also tested our coupling approach in two paradigmatic limit cycle oscillators: Stuart–Landau and Van der Pol oscillators.

  12. 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.

  13. 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.

  14. An Automation System for Optimizing a Supply Chain Network Design under the Influence of Demand Uncertainty

    OpenAIRE

    Polany, Rany

    2012-01-01

    This research develops and applies an integrated hierarchical framework for modeling a multi-echelon supply chain network design, under the influence of demand uncertainty. The framework is a layered integration of two levels: macro, high-level scenario planning combined with micro, low-level Monte Carlo simulation of uncertainties in demand. To facilitate rapid simulation of the effects of demand uncertainty, the integrated framework was implemented as a dashboard automation system using Mic...

  15. A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

    OpenAIRE

    Changzhi, Bian

    2015-01-01

    This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the...

  16. Experimental evidence of dynamic re-organization of evolving landscapes under changing climatic forcing

    Science.gov (United States)

    Singh, Arvind; Tejedor, Alejandro; Zaliapin, Ilya; Reinhardt, Liam; Foufoula-Georgiou, Efi

    2015-04-01

    The aim of this study is to better understand the dynamic re-organization of an evolving landscape under a scenario of changing climatic forcing for improving our knowledge of geomorphic transport laws under transient conditions and developing predictive models of landscape response to external perturbations. Real landscape observations for long-term analysis are limited and to this end a high resolution controlled laboratory experiment was conducted at the St. Anthony Falls laboratory at the University of Minnesota. Elevation data were collected at temporal resolution of 5 mins and spatial resolution of 0.5 mm as the landscape approached steady state (constant uplift and precipitation rate) and in the transient state (under the same uplift and 5x precipitation). The results reveal rapid topographic re-organization under a five-fold precipitation increase with the fluvial regime expanding into the previously debris dominated regime, accelerated erosion happening at hillslope scales, and rivers shifting from an erosion-limited to a transport-limited regime. From a connectivity and clustering analysis of the erosional and depositional events, we demonstrate the strikingly different spatial patterns of landscape evolution under steady-state (SS) and transient-state (TS), even when the time under SS is "stretched" compared to that under TS such as to match the total volume and PDF of erosional and depositional amounts. We quantify the spatial coupling of hillslopes and channels and demonstrate that hillslopes lead and channels follow in re-organizing the whole landscape under such an amplified precipitation regime.

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

    Science.gov (United States)

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

    2017-07-07

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

  18. 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.

  19. 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.

  20. Disrupted Nodal and Hub Organization Account for Brain Network Abnormalities in Parkinson's Disease.

    Science.gov (United States)

    Koshimori, Yuko; Cho, Sang-Soo; Criaud, Marion; Christopher, Leigh; Jacobs, Mark; Ghadery, Christine; Coakeley, Sarah; Harris, Madeleine; Mizrahi, Romina; Hamani, Clement; Lang, Anthony E; Houle, Sylvain; Strafella, Antonio P

    2016-01-01

    The recent application of graph theory to brain networks promises to shed light on complex diseases such as Parkinson's disease (PD). 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 (HCs) and 42 patients, were investigated in 120 nodes for local efficiency, betweenness centrality, and degree. Hub regions were identified in the HC and patient groups. We found nodal and hub changes in patients compared with HCs, including the right pre-supplementary motor area (SMA), left anterior insula, bilateral mid-insula, bilateral dorsolateral prefrontal cortex (DLPFC), and right caudate nucleus. In general, nodal regions within the sensorimotor network (i.e., right pre-SMA 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 DLPFC 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 PD.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Marketing for health-care organizations: an introduction to network management.

    Science.gov (United States)

    Boonekamp, L C

    1994-01-01

    The introduction of regulated competition in health care in several Western countries confronts health care providing organizations with changing relationships, with their environment and a need for knowledge and skills to analyse and improve their market position. Marketing receives more and more attention, as recent developments in this field of study provide a specific perspective on the relationships between an organization and external and internal parties. In doing so, a basis is offered for network management. A problem is that the existing marketing literature is not entirely appropriate for the specific characteristics of health care. After a description of the developments in marketing and its most recent key concepts, the applicability of these concepts in health-care organizations is discussed. States that for the health-care sector, dominated by complex networks of interorganizational relationships, the strategic marketing vision on relationships can be very useful. At the same time however, the operationalization of these concepts requires special attention and a distinct role of the management of health-care organizations, because of the characteristics of such organizations and the specific type of their service delivery.

  9. Keeping the wheels turning : multi-level dynamics in organizing networks of practice

    OpenAIRE

    Agterberg, M.; Hooff, B. van den; Huysman, M.

    2008-01-01

    This paper addresses organizing dynamics of intra-firm ‘networks of practice’ (NOPs). It unravels different dimensions that play a role in knowledge sharing within NOPs: (1) practice dimension; (2) social dimension; and (3) organizational dimension. Based on a unique interpretive case study, we ‘unpack’ each dimension and consider them as dynamic based on either positive or negative forces that influence knowledge sharing in NOPs. By introducing the metaphor of a cogwheel, we argue that maint...

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. A mathematical framework for modelling and evaluating natural gas pipeline networks under hydrogen injection

    Energy Technology Data Exchange (ETDEWEB)

    Tabkhi, F.; Azzaro-Pantel, C.; Pibouleau, L.; Domenech, S. [Laboratoire de Genie Chimique, UMR5503 CNRS/INP/UPS, 5 rue Paulin Talabot F-BP1301, 31106 Toulouse Cedex 1 (France)

    2008-11-15

    This article presents the framework of a mathematical formulation for modelling and evaluating natural gas pipeline networks under hydrogen injection. The model development is based on gas transport through pipelines and compressors which compensate for the pressure drops by implying mainly the mass and energy balances on the basic elements of the network. The model was initially implemented for natural gas transport and the principle of extension for hydrogen-natural gas mixtures is presented. The objective is the treatment of the classical fuel minimizing problem in compressor stations. The optimization procedure has been formulated by means of a nonlinear technique within the General Algebraic Modelling System (GAMS) environment. This work deals with the adaptation of the current transmission networks of natural gas to the transport of hydrogen-natural gas mixtures. More precisely, the quantitative amount of hydrogen that can be added to natural gas can be determined. The studied pipeline network, initially proposed in [1] is revisited here for the case of hydrogen-natural gas mixtures. Typical quantitative results are presented, showing that the addition of hydrogen to natural gas decreases significantly the transmitted power: the maximum fraction of hydrogen that can be added to natural gas is around 6 mass% for this example. (author)

  15. 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.

  16. Synchronisation of networked Kuramoto oscillators under stable Lévy noise

    Science.gov (United States)

    Kalloniatis, Alexander C.; Roberts, Dale O.

    2017-01-01

    We study the Kuramoto model on several classes of network topologies examining the dynamics under the influence of Lévy noise. Such noise exhibits heavier tails than Gaussian and allows us to understand how 'shocks' influence the individual oscillator and collective system behaviour. Skewed α-stable Lévy noise, equivalent to fractional diffusion perturbations, are considered. We perform numerical simulations for Erdős-Rényi (ER) and Barabási-Albert (BA) scale free networks of size N = 1000 while varying the Lévy index α for the noise. We find that synchrony now assumes a surprising variety of forms, not seen for Gaussian-type noise, and changing with α: a noise-generated drift, a smooth α dependence of the point of cross-over of ER and BA networks in the degree of synchronisation, and a severe loss of synchronisation at low values of α. We also show that this robustness of the BA network across most values of α can also be understood as a consequence of the Laplacian of the graph working within the fractional Fokker-Planck equation of the linearised system, close to synchrony, with both eigenvalues and eigenvectors alternately contributing in different regimes of α.

  17. 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.

    Directory of Open Access Journals (Sweden)

    Amanda Tse

    Full Text Available 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

  18. 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

  19. Organ-specific proteomics analysis for identification of response mechanism in soybean seedlings under flooding stress.

    Science.gov (United States)

    Khatoon, Amana; Rehman, Shafiq; Hiraga, Susumu; Makino, Takahiro; Komatsu, Setsuko

    2012-10-22

    Flooding is one of the severe environmental factors which impair growth and yield in soybean plant. To investigate the organ specific response mechanism of soybean under flooding stress, changes in protein species were analyzed using a proteomics approach. Two-day-old soybeans were subjected to flooding for 5 days. Proteins were extracted from root, hypocotyl and leaf, and separated by two-dimensional polyacrylamide gel electrophoresis. In root, hypocotyl and leaf, 51, 66 and 51 protein species were significantly changed, respectively, under flooding stress. In root, metabolism related proteins were increased; however these proteins were decreased in hypocotyl and leaf. In all 3 organs, cytoplasm localized proteins were decreased, and leaf chloroplastic proteins were also decreased. Isoflavone reductase was commonly decreased at protein level in all 3 organs; however, mRNA of isoflavone reductase gene was up-regulated in leaf under flooding stress. Biophoton emission was increased in all 3 organs under flooding stress. The up-regulation of isoflavone reductase gene at transcript level; while decreased abundance at protein level indicated that flooding stress affected the mRNA translation to proteins. These results suggest that concurrence in expression of isoflavone reductase gene at mRNA and protein level along with imbalance in other disease/defense and metabolism related proteins might lead to impaired growth of root, hypocotyl and leaf of soybean seedlings under flooding stress. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. 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.)

  1. 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.)

  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. Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles.

    Science.gov (United States)

    Fleury, Marie-Josée; Grenier, Guy; Vallée, Catherine; Aubé, Denise; Farand, Lambert

    2017-03-10

    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. 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. 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. 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.

  4. Forming a three-dimensional porous organic network via solid-state explosion of organic single crystals.

    Science.gov (United States)

    Bae, Seo-Yoon; Kim, Dongwook; Shin, Dongbin; Mahmood, Javeed; Jeon, In-Yup; Jung, Sun-Min; Shin, Sun-Hee; Kim, Seok-Jin; Park, Noejung; Lah, Myoung Soo; Baek, Jong-Beom

    2017-11-17

    Solid-state reaction of organic molecules holds a considerable advantage over liquid-phase processes in the manufacturing industry. However, the research progress in exploring this benefit is largely staggering, which leaves few liquid-phase systems to work with. Here, we show a synthetic protocol for the formation of a three-dimensional porous organic network via solid-state explosion of organic single crystals. The explosive reaction is realized by the Bergman reaction (cycloaromatization) of three enediyne groups on 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene. The origin of the explosion is systematically studied using single-crystal X-ray diffraction and differential scanning calorimetry, along with high-speed camera and density functional theory calculations. The results suggest that the solid-state explosion is triggered by an abrupt change in lattice energy induced by release of primer molecules in the 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene crystal lattice.

  5. A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

    Science.gov (United States)

    Tsumori, Kenji; Ozawa, Seiichi

    When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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)

  12. What does the functional organization of cortico-hippocampal networks tell us about the functional organization of memory?

    Science.gov (United States)

    Reagh, Zachariah M; Ranganath, Charan

    2018-04-25

    Historically, research on the cognitive processes that support human memory proceeded, to a large extent, independently of research on the neural basis of memory. Accumulating evidence from neuroimaging, however, has enabled the field to develop a broader and more integrative perspective. Here, we briefly outline how advances in cognitive neuroscience can potentially shed light on concepts and controversies in human memory research. We argue that research on the functional properties of cortico-hippocampal networks informs us about how memories might be organized in the brain, which, in turn, helps to reconcile seemingly disparate perspectives in cognitive psychology. Finally, we discuss several open questions and directions for future research. Copyright © 2018. Published by Elsevier B.V.

  13. Photoluminescent lanthanide-organic bilayer networks with 2,3-pyrazinedicarboxylate and oxalate.

    Science.gov (United States)

    Soares-Santos, Paula C R; Cunha-Silva, Luís; Paz, Filipe A Almeida; Ferreira, Rute A S; Rocha, João; Carlos, Luís D; Nogueira, Helena I S

    2010-04-05

    The hydrothermal reaction between lanthanide nitrates and 2,3-pyrazinedicarboxylic acid led to a new series of two-dimensional (2D) lanthanide-organic frameworks: [Ln(2)(2,3-pzdc)(2)(ox)(H(2)O)(2)](n) [where 2,3-pzdc(2-) = 2,3-pyrazinedicarboxylate, ox(2-) = oxalate, and Ln(III) = Ce, Nd, Sm, Eu, Gd, Tb, or Er]. The structural details of these materials were determined by single-crystal X-ray diffraction (for Ce(3+) and Nd(3+)) that revealed the formation of a layered structure. Cationic monolayers of {(infinity)(2)[Ln(2,3-pzdc)(H(2)O)](+)} are interconnected via the ox(2-) ligand leading to the formation of neutral (infinity)(2)[Ln(2)(2,3-pzdc)(2)(ox)(H(2)O)(2)] bilayer networks; structural cohesion of the crystalline packing is reinforced by the presence of highly directional O-H...O hydrogen bonds between adjacent bilayers. Under the employed hydrothermal conditions 2,3-pyrazinedicarboxylic acid can be decomposed into ox(2-) and 2-pyrazinecarboxylate (2-pzc(-)), as unequivocally proved by the isolation of the discrete complex [Tb(2)(2-pzc)(4)(ox)(H(2)O)(6)].10H(2)O. Single-crystal X-ray diffraction of this latter complex revealed its co-crystallization with an unprecedented (H(2)O)(16) water cluster. Photoluminescence measurements were performed for the Nd(3+), Sm(3+), Eu(3+), and Tb(3+) compounds which show, under UV excitation at room temperature, the Ln(3+) characteristic intra-4f(N) emission peaks. The energy level of the triplet states of 2,3-pyrazinedicarboxylic acid (18939 cm(-1)) and oxalic acid (24570 cm(-1)) was determined from the 12 K emission spectrum of the Gd(3+) compound. The (5)D(0) and (5)D(4) lifetime values (0.333 +/- 0.006 and 0.577 +/- 0.017 ms) and the absolute emission quantum yields (0.13 +/- 0.01 and 0.05 +/- 0.01) were determined for the Eu(3+) and Tb(3+) compounds, respectively. For the Eu(3+) compound the energy transfer efficiency arising from the ligands' excited states was estimated (0.93 +/- 0.01).

  14. Organization of Individual Work of Students under Competence-Oriented Approach to Education in Higher School

    Science.gov (United States)

    Ualiyeva, Nazym T.; Murzalinova, Alma Z.

    2016-01-01

    The main objective of this research is to identify the essence, content and specifics of organization of individual work of higher school students under competence-oriented approach. The research methodology is related to the choice of competence-oriented approach to ensure transformation of individual work into individual activity in…

  15. Method of treating organic material. [addition of formate, heating under pressure, and distilling the mass

    Energy Technology Data Exchange (ETDEWEB)

    Bergstrom, H O.V.; Cederquist, K N

    1932-02-08

    A method is given of treating organic material such as wood, peat, shale, etc. It is characterized by the addition of formate to the material, before, during, or after heating it under pressure with alkalis, earth alkalis, et cetera, and by the mass thus produced undergoing dry distillation. The patent has three more claims.

  16. AC characterization of bulk organic solar cell in the dark and under illumination

    International Nuclear Information System (INIS)

    Váry, Michal; Perný, Milan; Šály, Vladimír; Packa, Juraj

    2014-01-01

    Highlights: • A study of organic bulk photovoltaic (PV) solar cell. • Current–voltage characteristics in the dark and under illumination. • AC measurements, both under illumination and in the dark conditions. • Equivalent AC circuit. • Effective lifetime assigned with electron–hole recombination and diffusion time of the electron was estimated. - Abstract: Impedance spectroscopy has been used widely to evaluate the transport processes in photovoltaic, mainly based on inorganic semiconductors, structures – solar cells. The aim of this research was to characterize improved organic bulk photovoltaic (PV) solar cells exploiting this method. Progress in technology of investigated organic solar cell involves the use of an active layer based on low band gap type of polymer. The organic PV cell with front transparent electrode and rear metal electrode and active layer produced by Konarka Technologies was analyzed by electrical DC and AC measurements. Current–voltage (I–V) characteristics in the dark and under illumination were measured and basic PV parameters were calculated. AC measurements, both under illumination and in the dark conditions, were processed in order to identify electronic behavior using equivalent AC circuit which was suggested by fitting of measured impedance data. Circuit with the best correlation to measured data is analyzed in details. Voltage and frequency dependences of fitted equivalent circuit components and calculated parameters are explained and presented in the paper

  17. 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.

  18. 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.

  19. 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.

  20. Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

    Science.gov (United States)

    Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

    2015-02-04

    In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

  1. Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

    Directory of Open Access Journals (Sweden)

    Yong Cui

    2015-02-01

    Full Text Available In the wireless sensor networks (WSNs for electric field measurement system under the High-Voltage Direct Current (HVDC transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes’ neighbor lists based on the Received Signal Strength Indicator (RSSI values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

  2. 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

  3. 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)

  4. 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.

  5. Organizations as Cognitive Systems: is Knowledge AN Emergent Property of Information Networks?

    Science.gov (United States)

    Biggiero, Lucio

    The substitution of knowledge to information as the entity that organizations process and deliver raises a number of questions concerning the nature of knowledge. The dispute on the codifiability of tacit knowledge and that juxtaposing the epistemology of practice vs. the epistemology of possession can be better faced by revisiting two crucial debates. One concerns the nature of cognition and the other the famous mind-body problem. Cognition can be associated with the capability of manipulating symbols, like in the traditional computational view of organizations, interpreting facts or symbols, like in the narrative approach to organization theory, or developing mental states (events), like argued by the growing field of organizational cognition. Applied to the study of organizations, the mind-body problem concerns the possibility (if any) and the forms in which organizational mental events, like trust, identity, cultures, etc., can be derived from the structural aspects (technological, cognitive or communication networks) of organizations. By siding in extreme opposite positions, the two epistemologies appear irreducible one another and pay its own inner consistency with remarkable difficulties in describing and explaining some empirical phenomena. Conversely, by legitimating the existence of both tacit and explicit knowledge, by emphasizing the space of human interactions, and by assuming that mental events can be explained with the structural aspects of organizations, Nonaka's SECI model seems an interesting middle way between the two rival epistemologies.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.

    Science.gov (United States)

    Stringer, Simon M; Rolls, Edmund T

    2006-12-01

    A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.

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

    Science.gov (United States)

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

    2018-04-01

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

  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. Three-Dimensional Networked Metal-Organic Frameworks with Conductive Polypyrrole Tubes for Flexible Supercapacitors.

    Science.gov (United States)

    Xu, Xingtao; Tang, Jing; Qian, Huayu; Hou, Shujin; Bando, Yoshio; Hossain, Md Shahriar A; Pan, Likun; Yamauchi, Yusuke

    2017-11-08

    Metal-organic frameworks (MOFs) with high porosity and a regular porous structure have emerged as a promising electrode material for supercapacitors, but their poor electrical conductivity limits their utilization efficiency and capacitive performance. To increase the overall electrical conductivity as well as the efficiency of MOF particles, three-dimensional networked MOFs are developed via using preprepared conductive polypyrrole (PPy) tubes as the support for in situ growth of MOF particles. As a result, the highly conductive PPy tubes that run through the MOF particles not only increase the electron transfer between MOF particles and maintain the high effective porosity of the MOFs but also endow the MOFs with flexibility. Promoted by such elaborately designed MOF-PPy networks, the specific capacitance of MOF particles has been increased from 99.2 F g -1 for pristine zeolitic imidazolate framework (ZIF)-67 to 597.6 F g -1 for ZIF-PPy networks, indicating the importance of the design of the ZIF-PPy continuous microstructure. Furthermore, a flexible supercapacitor device based on ZIF-PPy networks shows an outstanding areal capacitance of 225.8 mF cm -2 , which is far above other MOFs-based supercapacitors reported up to date, confirming the significance of in situ synthetic chemistry as well as the importance of hybrid materials on the nanoscale.

  14. A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

    Science.gov (United States)

    Shen, Lili; Guo, Jiming; Wang, Lei

    2018-06-06

    The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

  15. 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.

  16. Transformation-invariant visual representations in self-organizing spiking neural networks.

    Science.gov (United States)

    Evans, Benjamin D; Stringer, Simon M

    2012-01-01

    The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  17. Transform-invariant visual representations in self-organizing spiking neural networks

    Directory of Open Access Journals (Sweden)

    Benjamin eEvans

    2012-07-01

    Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  18. 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).

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. Application of self-organizing competition artificial neural network to logging data explanation of sandstone-hosted uranium deposits

    International Nuclear Information System (INIS)

    Xu Jianguo; Xu Xianli; Wang Weiguo

    2008-01-01

    The article describes the model construction of self-organizing competition artificial neural network, its principle and automatic recognition process of borehole lithology in detail, and then proves the efficiency of the neural network model for automatically recognizing the borehole lithology with some cases. The self-organizing competition artificial neural network has the ability of self- organization, self-adjustment and high permitting errors. Compared with the BP algorithm, it takes less calculation quantity and more rapidly converges. Furthermore, it can automatically confirm the category without the known sample information. Trial results based on contrasting the identification results of the borehole lithology with geological documentations, indicate that self-organizing artificial neural network can be well applied to automatically performing the category of borehole lithology, during the logging data explanation of sandstone-hosted uranium deposits. (authors)

  8. xHeinz: an algorithm for mining cross-species network modules under a flexible conservation model

    NARCIS (Netherlands)

    El-Kebir, Mohammed; Soueidan, Hayssam; Hume, Thomas; Beisser, Daniela; Dittrich, Marcus; Müller, Tobias; Blin, Guillaume; Heringa, Jaap; Nikolski, Macha; Wessels, Lodewyk F.A.; Klau, G.W.

    2015-01-01

    Motivation: Integrative network analysis methods provide robust interpretations of differential high-throughput molecular profile measurements. They are often used in a biomedical context - to generate novel hypotheses about the underlying cellular processes or to derive biomarkers for

  9. Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

    International Nuclear Information System (INIS)

    Lin Min; Wang Gang; Chen Tianlun

    2007-01-01

    A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

  10. Tobacco Industry vs. the World Health Organization: a historical confrontation between social networks of stakeholders

    Directory of Open Access Journals (Sweden)

    Sérgio Boeira

    2007-04-01

    Full Text Available The aim of this article is to present an introduction to the history of the tobacco industry and the confrontation between its social network of stakeholders and the network led by the World Health Organization (WHO, with a focus on the Brazilian context and the role of the Alliance for the Control of Tobacco Use (ACT as the coordinator of multiple stakeholders opposing the tobacco industry strategies in Brazil. The article seeks to describe the problematic relationship between tobacco production and export on the one hand and tobacco control on the other, as exemplified by the approval, in February 2005, of the first international public health treaty (WHO Framework Convention for Tobacco Control. The text is based on research leading to a PhD thesis in 2000, which has been updated through articles and ongoing research since then, with the aim of monitoring the unfolding of this issue that is central to the public health policies

  11. 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.

  12. Image Fusion Based on the Self-Organizing Feature Map Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhaoli; SUN Shenghe

    2001-01-01

    This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

  13. 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)

  14. 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.

  15. 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.

  16. 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.

  17. Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

    Energy Technology Data Exchange (ETDEWEB)

    Harden, Jennifer W. [Stanford Univ., Stanford, CA (United States); U.S. Geological Survey, Menlo Park, CA (United States); Hugelius, Gustaf [Stanford Univ., Stanford, CA (United States); Stockholm Univ., Stockholm (Sweden); Ahlstrom, Anders [Stanford Univ., Stanford, CA (United States); Department of Physical Geography and Ecosystem Science, Lund (Sweden); Blankinship, Joseph C. [Univ. of Arizona, Tucson, AZ (United States); Bond-Lamberty, Ben [Univ. of Maryland, College Park, MD (United States); Lawrence, Corey R. [U.S. Geological Survey, Denver, CO (United States); Loisel, Julie [Texas A & M Univ., College Station, TX (United States); Malhotra, Avni [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jackson, Robert B. [Stanford Univ., Stanford, CA (United States); Ogle, Stephen [Colorado State Univ., Fort Collins, CO (United States); Phillips, Claire [USDA-ARS Forage Seed and Cereal Research Unit, Corvallis, OR (United States); Ryals, Rebecca [Univ. of Hawai' i at Manoa, Honolulu, HI (United States); Todd-Brown, Katherine [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vargas, Rodrigo [Univ. of Delaware, Newark, DE (United States); Vergara, Sintana E. [Univ. of California, Berkeley, CA (United States); Cotrufo, M. Francesca [Colorado State Univ., Fort Collins, CO (United States); Keiluweit, Marco [Univ. of Massachusetts, Amherst, MA (United States); Heckman, Katherine A. [USDA Forest Service, Houghton, MI (United States); Crow, Susan E. [Univ. of Hawai' i at Manoa, Honolulu, HI (United States); Silver, Whendee L. [Univ. of California, Berkeley, CA (United States); DeLonge, Marcia [Union of Concerned Scientists, Washington, D.C. (United States); Nave, Lucas E. [Univ. of Michigan, Pellston, MI (United States)

    2017-10-05

    Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, 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 organic matter and C and their management for sustained production and climate regulation.

  18. Multiplex Competition, Collaboration, and Funding Networks Among Health and Social Organizations: Toward Organization-based HIV Interventions for Young Men Who Have Sex With Men.

    Science.gov (United States)

    Fujimoto, Kayo; Wang, Peng; Kuhns, Lisa M; Ross, Michael W; Williams, Mark L; Garofalo, Robert; Klovdahl, Alden S; Laumann, Edward O; Schneider, John A

    2017-02-01

    Young men who have sex with men (YMSM) have the highest rates of human immunodeficiency virus (HIV) infection in the United States. Decades into the HIV epidemic, the relationships that YMSM-serving health and social organizations have with one another has not been studied in depth. The aim of this study was to examine the competition, collaboration, and funding source structures of multiplex organization networks and the mechanisms that promote fruitful relationships among these organizations. The study data collection method was a survey of health and social organizations from 2013-2014 in 2 cities, Chicago, IL and Houston, TX. Study participants were representatives from 138 health and social organizations. Responses to survey questions were used to reconstruct competition, collaboration, and combined competition-collaboration networks. While taking into consideration the collaborative relationships among organizations, we provide statistical evidence that organizations of similar type, similar social media use patterns, comparable patterns of funding, and similar network contexts tended to compete with one another. This competition was less likely to be accompanied by any sort of collaboration if the organizations shared common funding sources. Competition that excludes potential collaboration may be detrimental to mobilizing the collective efforts that serve local YMSM communities. System-level interventions may provide promising approaches to scaling-up HIV prevention and treatment efforts so as to encourage organizations to form partnerships with otherwise competing providers.

  19. Multiplex competition, collaboration, and funding networks among health and social organizations: Towards organization-based HIV interventions for young men who have sex with men

    Science.gov (United States)

    Fujimoto, Kayo; Wang, Peng; Kuhns, Lisa; Ross, Michael W; Williams, Mark L.; Garofalo, Robert; Klovdahl, Alden S.; Laumann, Edward O.; Schneider, John A.

    2016-01-01

    Background Young men who have sex with men (YMSM) have the highest rates of HIV infection in the United States. Decades into the HIV epidemic, the relationships that YMSM-serving health and social organizations have with one another has not been studied in depth. Objectives The aim of this study was to examine the competition, collaboration and funding source structures of multiplex organization networks and the mechanisms that promote fruitful relationships among these organizations. Research Design The study data collection method was a survey of health and social organizations from 2013–2014 in two cities, Chicago IL, and Houston TX. Subjects Study participants were representatives from 138 health and social organizations. Measures Responses to survey questions were used to reconstruct competition, collaboration and combined competition-collaboration networks. Results While taking into consideration the collaborative relationships among organizations, we provide solid statistical evidence that organizations of similar type, similar social media use patterns, comparable patterns of funding, and similar network contexts tended to compete with one another. This competition was less likely to be accompanied by any sort of collaboration if the organizations shared common funding sources. Conclusions Competition that excludes potential collaboration may be detrimental to mobilizing the collective efforts that serve local YMSM communities. System-level interventions may provide promising approaches to scaling-up HIV prevention and treatment efforts so as to encourage organizations to form partnerships with otherwise competing providers. PMID:27676400

  20. Deformation and concentration fluctuations under stretching in a polymer network with free chains. The ''butterfly'' effect

    International Nuclear Information System (INIS)

    Ramzi, A.

    1994-06-01

    Small Angle Neutron Scattering gives access to concentration fluctuations of mobile labeled polymer chains embedded in a polymer network. At rest they appear progressively larger than for random mixing, with increasing ratio. Under uniaxial stretching, they decrease towards ideal mixing along the direction perpendicular to stretching, and can grow strongly along the parallel one, including the zero scattering vector q limit. This gives rise to intensity contours with double-winged patterns, in the shape of the figure '8', or of 'butterfly'. Random crosslinking and end-linking of monodisperse chains have both been studied. The strength of the 'butterfly' effect increases with the molecular weight of the free chains, the crosslinking ratio, the network heterogeneity, and the elongation ratio. Eventually, the signal collapses on an 'asymptotic' function I(q), of increasing correlation length with the elongation ratio. Deformation appears heterogeneous, maximal for soft areas, where the mobile chains localize preferentially. This could be due to spontaneous fluctuations, or linked to frozen fluctuations of the crosslink density. However, disagreement with the corresponding theoretical expressions makes it necessary to account for the spatial correlations of crosslink density, and their progressive unscreening as displayed by the asymptotic behavior. Networks containing pending labeled chains and free labeled stars lead to more precise understanding of the diffusion of free species and the heterogeneity of the deformation. It seems that the latter occurs even without diffusion for heterogeneous enough networks. In extreme cases (of the crosslinking parameters), the spatial correlations display on apparent fractal behavior, of dimensions 2 to 2.5, which is discussed here in terms of random clusters. 200 refs., 95 figs., 21 tabs., 10 appends