1,424 research outputs found
Computational universality of fungal sandpile automata
Hyphae within the mycelia of the ascomycetous fungi are compartmentalised by
septa. Each septum has a pore that allows for inter-compartmental and
inter-hyphal streaming of cytosol and even organelles. The compartments,
however, have special organelles, Woronin bodies, that can plug the pores. When
the pores are blocked, no flow of cytoplasm takes place. Inspired by the
controllable compartmentalisation within the mycelium of the ascomycetous fungi
we designed two-dimensional fungal automata. A fungal automaton is a cellular
automaton where communication between neighbouring cells can be blocked on
demand. We demonstrate computational universality of the fungal automata by
implementing sandpile cellular automata circuits there. We reduce the Monotone
Circuit Value Problem to the Fungal Automaton Prediction Problem. We construct
families of wires, cross-overs and gates to prove that the fungal automata are
P-complete
Fungal Automata
We study a cellular automaton (CA) model of information dynamics on a single
hypha of a fungal mycelium. Such a filament is divided in compartments (here
also called cells) by septa. These septa are invaginations of the cell wall and
their pores allow for flow of cytoplasm between compartments and hyphae. The
septal pores of the fungal phylum of the Ascomycota can be closed by organelles
called Woronin bodies. Septal closure is increased when the septa become older
and when exposed to stress conditions. Thus, Woronin bodies act as
informational flow valves. The one dimensional fungal automata is a binary
state ternary neighbourhood CA, where every compartment follows one of the
elementary cellular automata (ECA) rules if its pores are open and either
remains in state `0' (first species of fungal automata) or its previous state
(second species of fungal automata) if its pores are closed. The Woronin bodies
closing the pores are also governed by ECA rules. We analyse a structure of the
composition space of cell-state transition and pore-state transitions rules,
complexity of fungal automata with just few Woronin bodies, and exemplify
several important local events in the automaton dynamics
Exploring the Dynamics of Fungal Cellular Automata
Cells in a fungal hyphae are separated by internal walls (septa). The septa
have tiny pores that allow cytoplasm flowing between cells. Cells can close
their septa blocking the flow if they are injured, preventing fluid loss from
the rest of filament. This action is achieved by special organelles called
Woronin bodies. Using the controllable pores as an inspiration we advance one
and two-dimensional cellular automata into Elementary fungal cellular automata
(EFCA) and Majority fungal automata (MFA) by adding a concept of Woronin bodies
to the cell state transition rules. EFCA is a cellular automaton where the
communications between neighboring cells can be blocked by the activation of
the Woronin bodies (Wb), allowing or blocking the flow of information
(represented by a cytoplasm and chemical elements it carries) between them. We
explore a novel version of the fungal automata where the evolution of the
system is only affected by the activation of the Wb. We explore two case
studies: the Elementary Fungal Cellular Automata (EFCA), which is a direct
application of this variant for elementary cellular automata rules, and the
Majority Fungal Automata (MFA), which correspond to an application of the Wb to
two dimensional automaton with majority rule with Von Neumann neighborhood. By
studying the EFCA model, we analyze how the 256 elementary cellular automata
rules are affected by the activation of Wb in different modes, increasing the
complexity on applied rule in some cases. Also we explore how a consensus over
MFA is affected when the continuous flow of information is interrupted due to
the activation of Woronin bodies.Comment: 31 pages, 30 figure
Network Automata: Coupling structure and function in real-world networks
We introduce Network Automata, a framework which couples the topological
evolution of a network to its structure. It is useful for dealing with networks
in which the topology evolves according to some specified microscopic rules
and, simultaneously, there is a dynamic process taking place on the network
that both depends on its structure but is also capable of modifying it. It is a
generic framework for modeling systems in which network structure, dynamics,
and function are interrelated. At the practical level, this framework allows
for easy implementation of the microscopic rules involved in such systems. To
demonstrate the approach, we develop a class of simple biologically inspired
models of fungal growth.Comment: 7 pages, 5 figures, 1 tables. Revised content - surplus text and
figures remove
A new paradigm for SpeckNets:inspiration from fungal colonies
In this position paper, we propose the development of a new biologically inspired paradigm based on fungal colonies, for the application to pervasive adaptive systems. Fungal colonies have a number of properties that make them an excellent candidate for inspiration for engineered systems. Here we propose the application of such inspiration to a speckled computing platform. We argue that properties from fungal colonies map well to properties and requirements for controlling SpeckNets and suggest that an existing mathematical model of a fungal colony can developed into a new computational paradigm
Applications of percolation theory to fungal spread with synergy
There is increasing interest in the use of the percolation paradigm to analyze and predict the progress of disease spreading in spatially-structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is in uenced only by that of its neighbours. In a recent paper the percolation paradigm has been generalised to incorporate synergistic interactions in host infectivity and susceptibility and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by rst formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently tting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model tting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease control strategies that de ect epidemics from invasive to non-invasive regimes are discussed
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