25 Years of Self-Organized Criticality: Solar and Astrophysics

Shortly after the seminal paper {\sl "Self-Organized Criticality: An explanation of 1/f noise"} by Bak, Tang, and Wiesenfeld (1987), the idea has been applied to solar physics, in {\sl "Avalanches and the Distribution of Solar Flares"} by Lu and Hamilton (1991). In the following years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into the numerical SOC toy models, such as the discretization of magneto-hydrodynamics (MHD) processes. The novel applications stimulated also vigorous debates about the discrimination between SOC models, SOC-like, and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC studies from the last 25 years and highlight new trends, open questions, and future challenges, as discussed during two recent ISSI workshops on this theme.Comment: 139 pages, 28 figures, Review based on ISSI workshops "Self-Organized Criticality and Turbulence" (2012, 2013, Bern, Switzerland

Learning with delayed reinforcement in an exploratory probabilistic logic neural network

Imperial Users onl

Complex event types for agent-based simulation

This thesis presents a novel formal modelling language, complex event types (CETs), to describe behaviours in agent-based simulations. CETs are able to describe behaviours at any computationally represented level of abstraction. Behaviours can be specified both in terms of the state transition rules of the agent-based model that generate them and in terms of the state transition structures themselves. Based on CETs, novel computational statistical methods are introduced which allow statistical dependencies between behaviours at different levels to be established. Different dependencies formalise different probabilistic causal relations and Complex Systems constructs such as ‘emergence’ and ‘autopoiesis’. Explicit links are also made between the different types of CET inter-dependency and the theoretical assumptions they represent. With the novel computational statistical methods, three categories of model can be validated and discovered: (i) inter-level models, which define probabilistic dependencies between behaviours at different levels; (ii) multi-level models, which define the set of simulations for which an inter-level model holds; (iii) inferred predictive models, which define latent relationships between behaviours at different levels. The CET modelling language and computational statistical methods are then applied to a novel agent-based model of Colonic Cancer to demonstrate their applicability to Complex Systems sciences such as Systems Biology. This proof of principle model provides a framework for further development of a detailed integrative model of the system, which can progressively incorporate biological data from different levels and scales as these become available

Recent advances in petri nets and concurrency

CEUR Workshop Proceeding

Surveying trends in analogy-inspired product innovation

Analogies play a well-noted role in innovative design. Analogical reasoning is central to the practices of design-by-analogy and bio-inspired design. In both, analogies are used to derive abstracted principles from prior examples to generate new design solutions. While numerous laboratory and classroom studies of analogy usage have been published, relatively few studies have systematically examined real-world design-by-analogy to describe its characteristics and impacts. To better teach design-by-analogy and develop support tools for engineers, specific insights are needed regarding, for example, what types of product advantages are gained through design-by-analogy and how different design process characteristics influence its outcomes. This research comprises two empirical product studies which investigate analogical inspiration in real-world design to inform the development of new analogy methods and tools. The first, an exploratory pilot study of 57 analogy-inspired products, introduces the product study method and applies several categorical variables to classify product examples. These variables measure aspects such as the composition of the design team, the driving approach to analogical reasoning, and the achieved benefits of using the analogy-inspired concept. The full scale study of 70 analogy-inspired products uses formal collection and screening methods and a refined set of classification variables to analyze examples. It adopts a cross-sectional approach, using statistical tests of association to detect relationships among variables. Combined, these surveys of real-world analogy-inspired innovation inform the development of analogy tools and provide a general account of distant analogy usage across engineering disciplines. The cross-sectional product study method demonstrated in this work introduces a valuable tool for investigating factors and impacts of real-world analogy usage in design.M.S

On the development of slime mould morphological, intracellular and heterotic computing devices

The use of live biological substrates in the fabrication of unconventional computing (UC) devices is steadily transcending the barriers between science fiction and reality, but efforts in this direction are impeded by ethical considerations, the field’s restrictively broad multidisciplinarity and our incomplete knowledge of fundamental biological processes. As such, very few functional prototypes of biological UC devices have been produced to date. This thesis aims to demonstrate the computational polymorphism and polyfunctionality of a chosen biological substrate — slime mould Physarum polycephalum, an arguably ‘simple’ single-celled organism — and how these properties can be harnessed to create laboratory experimental prototypes of functionally-useful biological UC prototypes. Computing devices utilising live slime mould as their key constituent element can be developed into a) heterotic, or hybrid devices, which are based on electrical recognition of slime mould behaviour via machine-organism interfaces, b) whole-organism-scale morphological processors, whose output is the organism’s morphological adaptation to environmental stimuli (input) and c) intracellular processors wherein data are represented by energetic signalling events mediated by the cytoskeleton, a nano-scale protein network. It is demonstrated that each category of device is capable of implementing logic and furthermore, specific applications for each class may be engineered, such as image processing applications for morphological processors and biosensors in the case of heterotic devices. The results presented are supported by a range of computer modelling experiments using cellular automata and multi-agent modelling. We conclude that P. polycephalum is a polymorphic UC substrate insofar as it can process multimodal sensory input and polyfunctional in its demonstrable ability to undertake a variety of computing problems. Furthermore, our results are highly applicable to the study of other living UC substrates and will inform future work in UC, biosensing, and biomedicine

Biological Metaphors for Whiteness: Beyond Merit and Malice

The problem of persistent racial inequality is grounded in a failure of imagination. The general mainstream conception is that unfair racial inequality occurs only when there is intentional racism. Absent conscious racial malice, no racism is seen to exist. The only generally available alternative explanation for racial inequality is the meritocratic system. Viewing the distribution of resources as a product of a generally fair meritocratic system provides a defense against any charge of racism, and justifies the status quo. But in economics, business, computer science, and even biology, observers of complexity are coming to understand how dominant systems can prevail without superior merit, can maintain their position without any conscious guidance or intent, and can be organized without any collusion or direction. Markets, organisms, and ecologies coordinate themselves efficiently and organically, with surprising resilience. Whiteness operates like these other systems. This essay re-imagines Whiteness using images from perhaps unusual sources. Whiteness coalesces through the actions of multitudes of independent individuals, in the same way that slime mold forms when spore cells join together on the forest floor. Racial segregation results from simple self-organizing mathematical algorithms realized in the collective behavior of human beings moving in and out of neighborhoods. Whiteness sustains itself in the same way that cultural practices and self-serving beliefs do, without conscious intent. Whiteness carefully organizes itself in the same way that snowflakes and ants do, without anyone being in charge or giving direction

Mass Spectrometry-Based Metabolomics to Elucidate Functions in Marine Organisms and Ecosystems

Marine systems are very diverse and recognized as being sources of a wide range of biomolecules. This review provides an overview of metabolite profiling based on mass spectrometry (MS) approaches in marine organisms and their environments, focusing on recent advances in the field. We also point out some of the technical challenges that need to be overcome in order to increase applications of metabolomics in marine systems, including extraction of chemical compounds from different matrices and data management. Metabolites being important links between genotype and phenotype, we describe added value provided by integration of data from metabolite profiling with other layers of omics, as well as their importance for the development of systems biology approaches in marine systems to study several biological processes, and to analyze interactions between organisms within communities. The growing importance of MS-based metabolomics in chemical ecology studies in marine ecosystems is also illustrated