Emergence of a small-world functional network in cultured neurons

The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

Modelling QoS of a pervasive MVNO/M2M using semi-group theory

This paper aims to develop a mathematical model based on semi-group theory, which allows to improve quality of service (QoS), including the reduction of the carbon path, in a pervasive environment of a Mobile Virtual Network Operator (MVNO). This paper generalise an interrelationship Machine to Machine (M2M) mathematical model, based on semi-group theory. This paper demonstrates that using available technology and with a solid mathematical model, is possible to streamline relationships between building agents, to control pervasive spaces so as to reduce the impact in carbon footprint through the reduction of GHG.

Basic theory behind parameterizing atmospheric convection

Last fall, a network of the European Cooperation in Science and Technology (COST), called “Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models” (COST Action ES0905; see http://w3.cost.esf.org/index.php?id=205&action_number=ES0905), organized a 10-day training course on atmospheric convection and its parameterization. The aim of the workshop, held on the island of Brac, Croatia, was to help young scientists develop an in-depth understanding of the core theory underpinning convection parameterizations. The speakers also sought to impart an appreciation of the various approximations, compromises, and ansatz necessary to translate theory into operational practice for numerical models.

Asynchronous distributed parallelization of mobile network optimization algorithms

It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

Making internalization theory good for practice: the essence of Alan Rugman’s contributions to international business

This perspectives paper and its associated commentaries examine Alan Rugman's conceptual contribution to international business scholarship. Most significantly, we highlight Rugman's version of internalization theory as an approach that integrates transaction cost economics and ‘classical’ internalization theory with elements from the resource-based view, such that it is especially relevant to strategic management. In reviewing his oeuvre, we also offer observations on his ideas for ‘new internalization theory’. We classify his other novel insights into four categories: Network Multinationals; National competitiveness; Development and public policy; and Emerging Economy MNEs. This special section offers multiple views on how his work informed the larger academic debate and considers how these ideas might evolve in the longer term.

Formal validation of automated policy refinement in the management of network security systems

Policy hierarchies and automated policy refinement are powerful approaches to simplify administration of security services in complex network environments. A crucial issue for the practical use of these approaches is to ensure the validity of the policy hierarchy, i.e. since the policy sets for the lower levels are automatically derived from the abstract policies (defined by the modeller), we must be sure that the derived policies uphold the high-level ones. This paper builds upon previous work on Model-based Management, particularly on the Diagram of Abstract Subsystems approach, and goes further to propose a formal validation approach for the policy hierarchies yielded by the automated policy refinement process. We establish general validation conditions for a multi-layered policy model, i.e. necessary and sufficient conditions that a policy hierarchy must satisfy so that the lower-level policy sets are valid refinements of the higher-level policies according to the criteria of consistency and completeness. Relying upon the validation conditions and upon axioms about the model representativeness, two theorems are proved to ensure compliance between the resulting system behaviour and the abstract policies that are modelled.

Modeling connectivity in terms of network activity

A new complex network model is proposed which is founded on growth, with new connections being established proportionally to the current dynamical activity of each node, which can be understood as a generalization of the Barabasi-Albert static model. By using several topological measurements, as well as optimal multivariate methods (canonical analysis and maximum likelihood decision), we show that this new model provides, among several other theoretical kinds of networks including Watts-Strogatz small-world networks, the greatest compatibility with three real-world cortical networks.

Structural parameters of polyacrylamide hydrogels obtained by the Equilibrium Swelling Theory

In this paper, the synthesis and structural characterization of a series of polyacrylamide hydrogels with different degrees of reticulation are reported. Although the Equilibrium Swelling Theory was recognized as a simple and reliable tool for the determination of structural hydrogels network parameters like equilibrium degree of swelling, cross-link ratio and mesh size, this is the first application of this methodology for polyacrylamide hydrogels. By changing the total monomer content in the synthesis solution (%T) from 5 to 30%, at a fixed value of cross-linker content in the total monomer amount (%C) of 5%, the final parameter obtained, the mesh size, can be tuned from 2 to 0.3 nm. It was also possible to change the mesh size (0.19-0.35) by varying %C from 5 to 12% (at %T = 20%). Scanning Electron Microscopy images for the most different formulations are shown and corroborate data obtained from the theory. (c) 2008 Elsevier Ltd. All rights reserved.

Towards an epistemological theory of historical consciousness

This paper presents a theoretical analysis of the concept of historical consciousness. It argues that a focus on the epistemological problems of the concept can be a way of constructing a theory of the concept that both incorporates the diverse perspectives that exist in research about the concept and specifies how a historical consciousness can be developed in an individual.

The network of intertextual relations in Naipaul's half a life and magic seeds

Esta dissertação mapeia a rede de relações intertextuais em Half a Life (2001) e sua continuação Magic Seeds (2004), os romances mais recentes do Prêmio Nobel de Literatura de 2001, V. S. Naipaul, como contribuição para o estudo da obra do autor. A noção de intertextualidade permeia os estudos literários, e o termo tem sido largamente empregado desde que foi cunhado por Julia Kristeva nos anos sessenta. Desde então as mais variadas, e muitas vezes divergentes, teorias sobre intertextualidade compartilham a idéia de que um texto só adquire significado pleno na interação com outros textos. A abordagem metodológica proposta é baseada na teoria da transtextualidade de Gérard Genette. Esta escolha implica o estudo de intertextos, paratextos, metatextos, arquitextos e hipertextos que constituem a interface entre os dois romances e outros escritos. O nome do protagonista "William Somerset Chandran" constitui o fio que guia o estudo das várias relações transtextuais nos dois romances. A partir do prenome do protagonista – William – este estudo situa os romances no contexto da tradição do Bildungsroman, e argumenta que estes estabelecem uma paródia arquitextual do gênero na medida em que subvertem seu cerne, ou seja, a formação do caráter do protagonista. O nome do meio do protagonista – Somerset – remete à ficcionalização do escritor Somerset Maugham na narrativa, ao mesmo tempo em que esta desmistifica a ótica ocidental sobre o hinduísmo popularizada por Maugham em The Razor's Edge. O sobrenome do protagonista – Chandran – leva ao estudo do conjunto de referências à origem indiana de Naipaul e o papel desta na produção do autor. Este nome se reporta ao romance de Narayan The Bachelor of Arts, cujo protagonista também é nomeado Chandran. Narayan é um escritor de destaque na literatura anglo-indiana e referência recorrente na obra de Naipaul. Os temas de migração e choque cultural apresentados nos dois romances têm sido presença constante na obra de Naipaul. Esta pesquisa mapeia a relação de continuidade entre os dois romances em questão e o conjunto da obra de Naipaul, salientando o papel da ambientação geográfica da narrativa, marcada pela jornada do protagonista através de três continentes. A teoria da transtextualidade é uma ferramenta operacional para a pesquisa, a qual examina a densidade das referências geográficas, históricas e literárias em Half a Life e Magic Seeds, visando aportar elementos para o estudo da produção literária de Naipaul, na medida em que estes romances recentes condensam e revisitam a visão de mundo deste autor.

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

A cooperative game theory analysis for transmission loss allocation

This paper presents an analysis and discussion, based on cooperative game theory, for the allocation of the cost of losses to generators and demands in transmission systems. We construct a cooperative game theory model in which the players are represented by equivalent bilateral exchanges and we search for a unique loss allocation solution, the Core. Other solution concepts, such as the Shapley Value, the Bilateral Shapley Value and the Kernel are also explored. Our main objective is to illustrate why is not possible to find an optimal solution for allocating the cost of losses to the users of a network. Results and relevant conclusions are presented for a 4-bus system and a 14-bus system. (c) 2007 Elsevier B.V. All rights reserved.

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.