Invariability, orbits and fuzzy attractors

In this paper, we present a generalization of a new systemic approach to abstract fuzzy systems. Using a fuzzy relations structure will retain the information provided by degrees of membership. In addition, to better suit the situation to be modelled, it is advisable to use T-norm or T-conorm distinct from the minimum and maximum, respectively. This gain in generality is due to the completeness of the work on a higher level of abstraction. You cannot always reproduce the results obtained previously, and also sometimes different definitions with different views are obtained. In any case this approach proves to be much more effective when modelling reality.

Bistable attractors in a model of convection-driven spherical dynamos

The range of existence and the properties of two essentially different chaotic attractors found in a model of nonlinear convection-driven dynamos in rotating spherical shells are investigated. A hysteretic transition between these attractors is established as a function of the rotation parameter t. The width of the basins of attraction is also estimated. © 2012 The Royal Swedish Academy of Sciences.

Polarization attractors in harmonic mode-locked fiber laser

We report on a polarimetry of harmonic mode-locked erbium-doped fiber laser with carbon nanotubes saturable absorber. We find new types of vector solitons with locked, switching and precessing states of polarization. The underlying physics presents interplay between birefringence of a laser cavity created by polarization controller along with light induced anisotropy caused by polarization hole burning. © 2014 Optical Society of America.

Polarization attractors in harmonic mode-locked fiber laser with carbon nanotubes

We study polarization dynamics of a harmonic mode-locked erbium-doped fiber laser with carbon nanotubes absorber. New types of vector solitons are shown for multi-pulse and harmonic mode-locked operation with locked, switching and precessing polarization states. © 2014 OSA.

Relating bisimulations with attractors in boolean network models

When studying a biological regulatory network, it is usual to use boolean network models. In these models, boolean variables represent the behavior of each component of the biological system. Taking in account that the size of these state transition models grows exponentially along with the number of components considered, it becomes important to have tools to minimize such models. In this paper, we relate bisimulations, which are relations used in the study of automata (general state transition models) with attractors, which are an important feature of biological boolean models. Hence, we support the idea that bisimulations can be important tools in the study some main features of boolean network models.We also discuss the differences between using this approach and other well-known methodologies to study this kind of systems and we illustrate it with some examples.

Self-Organizing Map Neural Architectures Based on Limit Cycle Attractors

Recent efforts to develop large-scale neural architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason is that most conventional SOMs use a static encoding representation: Each input is typically represented by the fixed activation of a single node in the map layer. This not only carries information in an inefficient and unreliable way that impedes building robust multi-SOM neural architectures, but it is also inconsistent with rhythmic oscillations in biological neural networks. Here I develop and study an alternative encoding scheme that instead uses limit cycle attractors of multi-focal activity patterns to represent input patterns/sequences. Such a fundamental change in representation raises several questions: Can this be done effectively and reliably? If so, will map formation still occur? What properties would limit cycle SOMs exhibit? Could multiple such SOMs interact effectively? Could robust architectures based on such SOMs be built for practical applications? The principal results of examining these questions are as follows. First, conditions are established for limit cycle attractors to emerge in a SOM through self-organization when encoding both static and temporal sequence inputs. It is found that under appropriate conditions a set of learned limit cycles are stable, unique, and preserve input relationships. In spite of the continually changing activity in a limit cycle SOM, map formation continues to occur reliably. Next, associations between limit cycles in different SOMs are learned. It is shown that limit cycles in one SOM can be successfully retrieved by another SOM’s limit cycle activity. Control timings can be set quite arbitrarily during both training and activation. Importantly, the learned associations generalize to new inputs that have never been seen during training. Finally, a complete neural architecture based on multiple limit cycle SOMs is presented for robotic arm control. This architecture combines open-loop and closed-loop methods to achieve high accuracy and fast movements through smooth trajectories. The architecture is robust in that disrupting or damaging the system in a variety of ways does not completely destroy the system. I conclude that limit cycle SOMs have great potentials for use in constructing robust neural architectures.

Effect of light-sticks and electralunie attractors on surface-longline catches of swordfish (Xiphias gladius, Linnaeus, 1959) in the southwest equatorial Atlantic

Two experimental fishing trials were carried out off the coast of Pernambuco, Brazil, in 1999 and 2001, using a small artisanal longliner. In experiment 1, six-hook baskets with three chemical light-sticks on alternating hooks had significantly higher catch rates than those with zero or with a light-stick on every hook, with most swordfish accounted for by hooks with light-sticks. Analysis of the data from experiment 2 showed no significant difference between electralume attractors, consisting of AA lithium batteries protected by a solid cover and light-sticks that produce a fluorescent light when two chemical products are mixed. Significant differences were detected in mean CPUE by size class, with most swordfish belonging to class 'b' (125-170 cm lower jaw to fork length (LJFL)). No differences, however, were found for swordfish catches in classes 'a' (< 125 cm LJFL) and V, and no evidence was found of interaction between the two factors (attractor and size class). Although there was no significant difference between the total length-frequency distributions of swordfish caught with light-sticks and electralume attractors, signibcant differences were found for fish smaller than 125 cm LJFL, with electralume catches consisting of smaller swordfish than those of gear using light-sticks. (c) 2004 Elsevier B.V. All rights reserved.

Effect of light-sticks and electralume attractors on surface-longline catches of swordfish (Xiphias gladius, Linnaeus, 1959) in the southwest equatorial Atlantic

Two experimental fishing trials were carried out off the coast of Pernambuco, Brazil, in 1999 and 2001, using a small artisanal longliner. In experiment 1, six-hook baskets with three chemical light-sticks on alternating hooks had significantly higher catch rates than those with zero or with a light-stick on every hook, with most swordfish accounted for by hooks with light-sticks. Analysis of the data from experiment 2 showed no significant difference between electralume attractors, consisting of AA lithium batteries protected by a solid cover and light-sticks that produce a fluorescent light when two chemical products are mixed. Significant differences were detected in mean CPUE by size class, with most swordfish belonging to class ‘b’ (125–170 cm lower jaw to fork length (LJFL)). No differences, however, were found for swordfish catches in classes ‘a’ (<125 cm LJFL) and ‘b’, and no evidence was found of interaction between the two factors (attractor and size class). Although there was no significant difference between the total length-frequency distributions of swordfish caught with light-sticks and electralume attractors, significant differences were found for fish smaller than 125 cm LJFL, with electralume catches consisting of smaller swordfish than those of gear using light-sticks.

Interpersonal coordination tendencies, decision-making and information governing dynamics in rugby union

In this chapter, ideas from ecological psychology and nonlinear dynamics are integrated to characterise decision-making as an emergent property of self-organisation processes in the interpersonal interactions that occur in sports teams. A conceptual model is proposed to capture constraints on dynamics of decisions and actions in dyadic systems, which has been empirically evaluated in simulations of interpersonal interactions in team sports. For this purpose, co-adaptive interpersonal dynamics in team sports such as rubgy union have been studied to reveal control parameter and collective variable relations in attacker-defender dyads. Although interpersonal dynamics of attackers and defenders in 1 vs 1 situations showed characteristics of chaotic attractors, the informational constraints of rugby union typically bounded dyadic systems into low dimensional attractors. Our work suggests that the dynamics of attacker-defender dyads can be characterised as an evolving sequence since players' positioning and movements are connected in diverse ways over time.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

Adaptive and phase transition behavior in performance of discrete multi-articular actions by degenerate neurobiological systems

The identification of attractors is one of the key tasks in studies of neurobiological coordination from a dynamical systems perspective, with a considerable body of literature resulting from this task. However, with regards to typical movement models investigated, the overwhelming majority of actions studied previously belong to the class of continuous, rhythmical movements. In contrast, very few studies have investigated coordination of discrete movements, particularly multi-articular discrete movements. In the present study, we investigated phase transition behavior in a basketball throwing task where participants were instructed to shoot at the basket from different distances. Adopting the ubiquitous scaling paradigm, throwing distance was manipulated as a candidate control parameter. Using a cluster analysis approach, clear phase transitions between different movement patterns were observed in performance of only two of eight participants. The remaining participants used a single movement pattern and varied it according to throwing distance, thereby exhibiting hysteresis effects. Results suggested that, in movement models involving many biomechanical degrees of freedom in degenerate systems, greater movement variation across individuals is available for exploitation. This observation stands in contrast to movement variation typically observed in studies using more constrained bi-manual movement models. This degenerate system behavior provides new insights and poses fresh challenges to the dynamical systems theoretical approach, requiring further research beyond conventional movement models.

A Data Picture of Australia's Arts and Entertainment Sector 2010

Australia’s Arts and Entertainment Sector underpins cultural and social innovation, improves the quality of community life, is essential to maintaining our cities as world class attractors of talent and investment, and helps create ‘Brand Australia’ in the global marketplace of ideas (QUT Creative Industries Faculty 2010). The sector makes a significant contribution to the Australian economy. So what is the size and nature of this contribution? The Creative Industries Faculty at Queensland University of Technology recently conducted an exercise to source and present statistics in order to produce a data picture of Australia’s Arts and Entertainment Sector. The exercise involved gathering the latest statistics on broadcasting, new media, performing arts, and music composition, distribution and publishing as well as Australia’s performance in world markets.

Organized crime in Oceania

Oceania has a relatively low level of crime prevalence yet in the smaller and under-developed PICs we have shown that transnational crime has become increasingly common. A risk contained but potentially dangerous if state failure or fragility undermines law enforcement capacities. We predict that as the pace of globalization quickens and the demand for raw materials and resources grows some parts of the Pacific will be prone to criminal enterprises run by both indigenous and foreign crime groups. Australia and New Zealand will remain attractors of illicit goods notably ATS but will in turn be source countries for diminishing fish stock such as beche de mere and abalone as well forest timber. Finally the role of states such as Australia and New Zealand in helping to maintain law enforcement capacities throughout the region will be crucial if organized crime in Oceania is to be kept in check while demand for illicit resources grow.

Transnational organized crime in Oceania

Oceania has a relatively low level of crime prevalence yet in the smaller and under-developed PICs we have shown that transnational crime has become increasingly common. A risk contained but potentially dangerous if state failure or fragility undermines law enforcement capacities. We predict that as the pace of globalization quickens and the demand for raw materials and resources grows some parts of the Pacific will be prone to criminal enterprises run by both indigenous and foreign crime groups. Australia and New Zealand will remain attractors of illicit goods notably ATS but will in turn be source countries for diminishing fish stock such as beche de mere and abalone as well forest timber. Finally the role of states such as Australia and New Zealand in helping to maintain law enforcement capacities throughout the region will be crucial if organized crime in Oceania is to be kept in check while demand for illicit resources grow.

Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.