24 resultados para complexity in spatiotemporal evolution


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Policy issues which receive large inputs of scientific and technical information are frequently marred by acrimonious controversies between contributing experts. There are few if any examples of a public policy decision being based on a firm consensus of scientific and technical experts. Such a consensus is taken for granted by the `Rational' model of decision making and its derivatives. Comparing the dynamics of conflict in policy-relevant issues with those of conflict in `pure' science, one is struck by their great similarity. In both cases we witness examples of rhetorical statements about incompetence, conflicting interpretations of data, and interdisciplinary communication problems. Noting this similarity, this thesis attempts to answer the question, `Is there a similarity of cause: do the same causes lie at the roots of conflict in policy-relevant and policy-irrelevant science?' In answering this question this thesis examines recent controversies in a generally policy-irrelevant science - evolutionary biology. Three episodes of conflict are studied: the `Neutral Allele Theory', `Punctuated Equilibrium', and `Structuralist versus Functionalist approaches to evolution'. These controversies are analysed in terms of both Kuhn's account of scientific `crises' and Collingridge and Reeve's (1986) `Overcritical Model'. Comparing its findings with those of Collingridge and Reeve, this thesis concludes that, (a) there is a Kuhnian crisis in contemporary evolution theory and, (b) that common causes do lie at the roots of conflict in policy-relevant and policy-irrelevant science. Science has an inherent tendency to degenerate into acrimonious conflict but at the same time has mechanisms which eventually resolve such conflicts. Unfortunately, when science is incorporated into the policy arena these mechanisms are prevented from operating. This thesis reinforces Collingridge and Reeve's conclusion that science is of little use to policy.

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The thesis contributes to the evolving process of moving the study of Complexity from the arena of metaphor to something real and operational. Acknowledging this phenomenon ultimately changes the underlying assumptions made about working environments and leadership; organisations are dynamic and so should their leaders be. Dynamic leaders are behaviourally complex. Behavioural Complexity is a product of behavioural repertoire - range of behaviours; and behavioural differentiation - where effective leaders apply appropriate behaviour to the demands of the situation. Behavioural Complexity was operationalised using the Competing Values Framework (CVF). The CVF is a measure that captures the extent to which leaders demonstrate four behaviours on four quadrants: Control, Compete, Collaborate and Create, which are argued to be critical to all types of organisational leadership. The results provide evidence to suggest Behavioural Complexity is an enabler of leadership effectiveness; Organisational Complexity (captured using a new measure developed in the thesis) moderates Behavioural Complexity and leadership effectiveness; and leadership training supports Behavioural Complexity in contributing to leadership effectiveness. Most definitions of leadership come down to changing people’s behaviour. Such definitions have contributed to a popularity of focus in leadership research intent on exploring how to elicit change in others when maybe some of the popularity of attention should have been on eliciting change in the leader them self. It is hoped that this research will provoke interest into the factors that cause behavioural change in leaders that in turn enable leadership effectiveness and in doing so contribute to a better understanding of leadership in organisations.

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Bubbling fluidized bed technology is one of the most effective mean for interaction between solid and gas flow, mainly due to its good mixing and high heat and mass transfer rate. It has been widely used at a commercial scale for drying of grains such as in pharmaceutical, fertilizers and food industries. When applied to drying of non-pours moist solid particles, the water is drawn-off driven by the difference in water concentration between the solid phase and the fluidizing gas. In most cases, the fluidizing gas or drying agent is air. Despite of the simplicity of its operation, the design of a bubbling fluidized bed dryer requires an understanding of the combined complexity in hydrodynamics and the mass transfer mechanism. On the other hand, reliable mass transfer coefficient equations are also required to satisfy the growing interest in mathematical modelling and simulation, for accurate prediction of the process kinetics. This chapter presents an overview of the various mechanisms contributing to particulate drying in a bubbling fluidized bed and the mass transfer coefficient corresponding to each mechanism. In addition, a case study on measuring the overall mass transfer coefficient is discussed. These measurements are then used for the validation of mass transfer coefficient correlations and for assessing the various assumptions used in developing these correlations.

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Digital back-propagation (DBP) has recently been proposed for the comprehensive compensation of channel nonlinearities in optical communication systems. While DBP is attractive for its flexibility and performance, it poses significant challenges in terms of computational complexity. Alternatively, phase conjugation or spectral inversion has previously been employed to mitigate nonlinear fibre impairments. Though spectral inversion is relatively straightforward to implement in optical or electrical domain, it requires precise positioning and symmetrised link power profile in order to avail the full benefit. In this paper, we directly compare ideal and low-precision single-channel DBP with single-channel spectral-inversion both with and without symmetry correction via dispersive chirping. We demonstrate that for all the dispersion maps studied, spectral inversion approaches the performance of ideal DBP with 40 steps per span and exceeds the performance of electronic dispersion compensation by ~3.5 dB in Q-factor, enabling up to 96% reduction in complexity in terms of required DBP stages, relative to low precision one step per span based DBP. For maps where quasi-phase matching is a significant issue, spectral inversion significantly outperforms ideal DBP by ~3 dB.

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Background. The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. Results. We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). Conclusions. The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate µ at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of µ, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks. © 2010 Stich et al; licensee BioMed Central Ltd.

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Although the Ebbinghaus illusion is commonly used as an example of a simple size-contrast effect, previous studies have emphasised its complexity by identifying many factors that potentially influence the magnitude of the illusion. Here, in a series of three experiments, we attempt to simplify this complexity. In each trial, subjects saw a display comprising, on one side, a target stimulus surrounded by inducers and, on the other, an isolated probe stimulus. Their task was to indicate whether the probe appeared larger or smaller than the target. Probe size was adjusted with a one-up, one-down staircase procedure to find the point of subjective equality between probe and target. From these experiments, we argue that the apparent effects of inducer size are often confounded by the relative completeness of the inducing surround and that factors such as the similarity of the inducers and target are secondary. We suggest a simple model that can explain most of the data in terms of just two primary and independent factors: the relative size of the inducers and target, and the distance between the inducers and the target. The balance between these two factors determines whether the size of the target is underestimated or overestimated. © 2005 a Pion publication.

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The presence of high phase noise in addition to additive white Gaussian noise in coherent optical systems affects the performance of forward error correction (FEC) schemes. In this paper, we propose a simple scheme for such systems, using block interleavers and binary Bose–Chaudhuri–Hocquenghem (BCH) codes. The block interleavers are specifically optimized for differential quadrature phase shift keying modulation. We propose a method for selecting BCH codes that, together with the interleavers, achieve a target post-FEC bit error rate (BER). This combination of interleavers and BCH codes has very low implementation complexity. In addition, our approach is straightforward, requiring only short pre-FEC simulations to parameterize a model, based on which we select codes analytically. We aim to correct a pre-FEC BER of around (Formula presented.). We evaluate the accuracy of our approach using numerical simulations. For a target post-FEC BER of (Formula presented.), codes selected using our method result in BERs around 3(Formula presented.) target and achieve the target with around 0.2 dB extra signal-to-noise ratio.