921 resultados para self-organized critical


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Objectives To consider the various specific substances-taking activities in sport an examination of three psychological models of doping behaviour utilised by researchers is presented in order to evaluate their real and potential impact, and to improve the relevance and efficiency of anti-doping campaigns. Design Adopting the notion of a "research program" (Lakatos, 1978) from the philosophy of science, a range of studies into the psychology of doping behaviour are classified and critically analysed. Method Theoretical and practical parameters of three research programs are critically evaluated (i) cognitive; (ii) drive; and (iii) situated-dynamic. Results The analysis reveals the diversity of theoretical commitments of the research programs and their practical consequences. The «cognitive program» assumes that athletes are accountable for their acts that reflect the endeavour to attain sporting and non-sporting goals. Attitudes, knowledge and rational decisions are understood to be the basis of doping behaviour. The «drive program» characterises the variety of traces and consequences on psychological and somatic states coming from athlete's experience with sport. Doping behaviour here is conceived of as a solution to reduce unconscious psychological and somatic distress. The «situated-dynamic program» considers a broader context of athletes' doping activity and its evolution during a sport career. Doping is considered as emergent and self-organized behaviour, grounded on temporally critical couplings between athletes' actions and situations and the specific dynamics of their development during the sporting life course. Conclusions These hypothetical, theoretical and methodological considerations offer a more nuanced understanding of doping behaviours, making an effective contribution to anti-doping education and research by enabling researchers and policy personnel to become more critically reflective about their explicit and implicit assumptions regarding models of explanations for doping behaviour.

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Individuals often imitate each other to fall into the typical group, leading to a self-organized state of typical behaviors in a community. In this paper, we model self-organization in social tagging systems and illustrate the underlying interaction and dynamics. Specifically, we introduce a model in which individuals adjust their own tagging tendency to imitate the average tagging tendency. We found that when users are of low confidence, they tend to imitate others and lead to a self-organized state with active tagging. On the other hand, when users are of high confidence and are stubborn to change, tagging becomes inactive. We observe a phase transition at a critical level of user confidence when the system changes from one regime to the other. The distributions of post length obtained from the model are compared to real data, which show good agreement. © 2011 American Physical Society.

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With each directed acyclic graph (this includes some D-dimensional lattices) one can associate some Abelian algebras that we call directed Abelian algebras (DAAs). On each site of the graph one attaches a generator of the algebra. These algebras depend on several parameters and are semisimple. Using any DAA, one can define a family of Hamiltonians which give the continuous time evolution of a stochastic process. The calculation of the spectra and ground-state wave functions (stationary state probability distributions) is an easy algebraic exercise. If one considers D-dimensional lattices and chooses Hamiltonians linear in the generators, in finite-size scaling the Hamiltonian spectrum is gapless with a critical dynamic exponent z=D. One possible application of the DAA is to sandpile models. In the paper we present this application, considering one- and two-dimensional lattices. In the one-dimensional case, when the DAA conserves the number of particles, the avalanches belong to the random walker universality class (critical exponent sigma(tau)=3/2). We study the local density of particles inside large avalanches, showing a depletion of particles at the source of the avalanche and an enrichment at its end. In two dimensions we did extensive Monte-Carlo simulations and found sigma(tau)=1.780 +/- 0.005.

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We investigate the internal dynamics of two cellular automaton models with heterogeneous strength fields and differing nearest neighbour laws. One model is a crack-like automaton, transferring ail stress from a rupture zone to the surroundings. The other automaton is a partial stress drop automaton, transferring only a fraction of the stress within a rupture zone to the surroundings. To study evolution of stress, the mean spectral density. f(k(r)) of a stress deficit held is: examined prior to, and immediately following ruptures in both models. Both models display a power-law relationship between f(k(r)) and spatial wavenumber (k(r)) of the form f(k(r)) similar tok(r)(-beta). In the crack model, the evolution of stress deficit is consistent with cyclic approach to, and retreat from a critical state in which large events occur. The approach to criticality is driven by tectonic loading. Short-range stress transfer in the model does not affect the approach to criticality of broad regions in the model. The evolution of stress deficit in the partial stress drop model is consistent with small fluctuations about a mean state of high stress, behaviour indicative of a self-organised critical system. Despite statistics similar to natural earthquakes these simplified models lack a physical basis. physically motivated models of earthquakes also display dynamical complexity similar to that of a critical point system. Studies of dynamical complexity in physical models of earthquakes may lead to advancement towards a physical theory for earthquakes.

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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This paper describes a pilot study centred on the technology-enhanced self-development of competences in lifelong learning education carried out in the challenging context of the Association of Participants Àgora. The pilot study shows that the use of the TENCompetence infrastructure, i.e. in this case the Personal Development Planner tool, provides various kinds of benefits for adult participants with low educational profiles and who are traditionally excluded from the use of innovative learning technologies and the knowledge society. The selforganized training supported by the PDP tool aims at allowing the learners to create and control their own learning plans based on their interests and educational background including informal and non-formal experiences. In this sense, the pilot participants had the opportunity to develop and improve their competences in English language (basic and advanced levels) and ICT competence profiles which are mostly related to functional and communicative skills. Besides, the use of the PDP functionalities, such as the self-assessment, the planning and the self-regulating elements allowed the participants to develop reflective skills. Pilot results also provide indications for future developments in the field of technology support for self-organized learners. The paper introduces the context and the pilot scenario, indicates the evaluation methodology applied and discusses the most significant findings derived from the pilot study.

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We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

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The invaded cluster (IC) dynamics introduced by Machta et al. [Phys. Rev. Lett. 75, 2792 (1995)] is extended to the fully frustrated Ising model on a square lattice. The properties of the dynamics that exhibits numerical evidence of self-organized criticality are studied. The fluctuations in the IC dynamics are shown to be intrinsic of the algorithm and the fluctuation-dissipation theorem is no longer valid. The relaxation time is found to be very short and does not present a critical size dependence.

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We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

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We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

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Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

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Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

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El presente trabajo tiene como finalidad caracterizar conceptos y elementos clave del caos y de la complejidad existente en la relación entre las organizaciones y la comunidad. Esta relación parte de la base de satisfacer las necesidades de los actores involucrados y, así mismo, mejorar el desempeño de cada uno, y contribuir al bienestar de la sociedad y a la perdurabilidad de las empresas. Para alcanzar el objetivo planteado, inicialmente se hace necesario contextualizar conceptos que estarán presentes durante todo el escrito. Por esto se expondrán términos como teoría de la complejidad, teoría del caos, los aspectos más representativos de la relación comunitaria y el marketing y su impacto en las comunidades. La teoría de la complejidad permitirá entender los sistemas como un todo, en donde las relaciones e interacciones de cada una de sus diferentes partes nos conducen a innumerables escenarios posibles. También se buscará entender la importancia de la relación organización-comunidad, ya que la comunidad puede jugar un papel determinante cuando las organizaciones se adaptan a los cambios. Es de suma importancia establecer relaciones estratégicas con la comunidad, entendiendo a la comunidad como un sistema o grupo social con determinadas características, que permitan tanto a las organizaciones como a la misma comunidad entender, comprender y satisfacer eficazmente las necesidades subyacentes y, así, llegar a establecer un entorno de retroalimentación continua y sostenibilidad a lo largo del tiempo. Actualmente, el funcionamiento del mundo ha cambiado en cierta medida, ya que antes la base del conocimiento se centraba en función del orden y la regularidad. Ahora, en cambio, se destaca la creatividad y la dinámica que son causadas por el desorden y la irregularidad presentes en los sistemas. El mundo se plantea como un grupo de innumerables sistemas auto-organizados, donde su funcionamiento puede provocar resultados impredecibles o aleatorios. La materia de complejidad en los sistemas se ha desarrollado por diferentes autores según aproximaciones desde diferentes ramas de la ciencia, como la cibernética, basada en los mecanismos de retroalimentación y control; desde la teoría general de los sistemas, que da énfasis en el dinamismo presente en los sistemas y cómo la organización está presente en su estructura. En el presente proyecto se realizará un estudio de tipo teórico-conceptual: se seleccionarán las bases de datos, fuentes de información y los documentos más representativos o que proporcionen la mayor información posible que permita el completo entendimiento de la investigación y de sus alcances propuestos. Es así que esta investigación busca aportar más elementos dentro de los diferentes estudios que pretenden explicar y mejorar la perdurabilidad de las empresas bajo las diferentes líneas de investigación. A través del tiempo, el GIPE ha ido evolucionando de acuerdo con los resultados de las investigaciones y se ha centrado en cuatro líneas de investigación: Liderazgo, Realidad, Estrategia y Gerencia. El proyecto de investigación “Relación de las organizaciones con el medio y marketing” hace parte de la línea de gerencia y busca identificar oportunidades gerenciales para las organizaciones que las acerquen al conocimiento y manejo de las áreas funcionales (Facultad de Administración, 2013). Además, el proyecto se adentra en las organizaciones en entornos complejos y su relación con la comunidad, y se observa así la organización como un ser vivo que contribuye al bienestar de la sociedad que, finalmente, es lo que garantiza su perdurabilidad.

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We analyze by numerical simulations and mean-field approximations an asymmetric version of the stochastic sandpile model with height restriction in one dimension. Each site can have at most two particles. Single particles are inactive and do not move. Two particles occupying the same site are active and may hop to neighboring sites following an asymmetric rule. Jumps to the right or to the left occur with distinct probabilities. In the active state, there will be a net current of particles to the right or to the left. We have found that the critical behavior related to the transition from the active to the absorbing state is distinct from the symmetrical case, making the asymmetry a relevant field.