2,079 research outputs found
Modeling the Heart as a Communication System
Electrical communication between cardiomyocytes can be perturbed during
arrhythmia, but these perturbations are not captured by conventional
electrocardiographic metrics. We developed a theoretical framework to quantify
electrical communication using information theory metrics in 2-dimensional cell
lattice models of cardiac excitation propagation. The time series generated by
each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon
entropy for each cell was calculated from the time series during four
clinically important heart rhythms: normal heartbeat, anatomical reentry,
spiral reentry, and multiple reentry. We also used mutual information to
perform spatial profiling of communication during these cardiac arrhythmias. We
found that information sharing between cells was spatially heterogeneous. In
addition, cardiac arrhythmia significantly impacted information sharing within
the heart. Entropy localized the path of the drifting core of spiral reentry,
which could be an optimal target of therapeutic ablation. We conclude that
information theory metrics can quantitatively assess electrical communication
among cardiomyocytes. The traditional concept of the heart as a functional
syncytium sharing electrical information cannot predict altered entropy and
information sharing during complex arrhythmia. Information theory metrics may
find clinical application in the identification of rhythm-specific treatments
which are currently unmet by traditional electrocardiographic techniques.Comment: 26 pages (including Appendix), 6 figures, 8 videos (not uploaded due
to size limitation
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
An Ansatz for undecidable computation in RNA-world automata
In this Ansatz we consider theoretical constructions of RNA polymers into
automata, a form of computational structure. The basis for transitions in our
automata are plausible RNA-world enzymes that may perform ligation or cleavage.
Limited to these operations, we construct RNA automata of increasing
complexity; from the Finite Automaton (RNA-FA) to the Turing Machine equivalent
2-stack PDA (RNA-2PDA) and the universal RNA-UPDA. For each automaton we show
how the enzymatic reactions match the logical operations of the RNA automaton,
and describe how biological exploration of the corresponding evolutionary space
is facilitated by the efficient arrangement of RNA polymers into a
computational structure. A critical theme of the Ansatz is the self-reference
in RNA automata configurations which exploits the program-data duality but
results in undecidable computation. We describe how undecidable computation is
exemplified in the self-referential Liar paradox that places a boundary on a
logical system, and by construction, any RNA automata. We argue that an
expansion of the evolutionary space for RNA-2PDA automata can be interpreted as
a hierarchical resolution of the undecidable computation by a meta-system (akin
to Turing's oracle), in a continual process analogous to Turing's ordinal
logics and Post's extensible recursively generated logics. On this basis, we
put forward the hypothesis that the resolution of undecidable configurations in
RNA-world automata represents a mechanism for novelty generation in the
evolutionary space, and propose avenues for future investigation of biological
automata
Modeling, Simulation and Application of Bacterial Transduction in Genetic Algorithms
At present, all methods in Evolutionary Computation are bioinspired in the fundamental principles of neo-Darwinism as well as on a vertical gene transfer. Thus, on a mechanism in which an organism receives genetic material from its ancestor. Horizontal, lateral or cross-population gene transfer is any process in which an organism transfers a genetic segment to another one that is not its offspring. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganism (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring a possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). The efficiency and performance of this algorithm was evaluated using a benchmark function and the 0/1 knapsack problem. The utility was illustrated designing an AM radio receiver, optimizing the main features of the electronic components of the AM radio circuit as well as those of the radio enclosure. Our results shown how PETRI approaches to higher fitness values as transduction probability comes near to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ‘bacterial colonies’
Design and Implementation of Cellular Automaton Simulating Domain Growth
Tato bakalářská práce se věnuje návrhu a implementaci grafického uživatelského rozhraní buněčného automatu simulující růst domén. Uživatelské rozhraní je implementováno v jazyce C++ s použitím frameworku Qt. Hlavním požadavkem je intuitivní ovládání a čistý kód, umožňující dalším úpravy programu. Apli\-kace nabízí možnost počátečního rozložení domén a jejich faktoru růstu. Během simulace lze provádět vybrané akce.This bachelor thesis is devoted to design and implementation of the graphical user interface of cellular automaton simulating domain growth. User interface is implemented in C++ with usage of framework Qt. Important elements are intuitive controls of the application and clean code, which allows another program modifications. Application allows user to set initial location of the domains and their growth factor. During simulation user can perform selected actions
Building a community to engineer synthetic cells and organelles from the bottom-up
Employing concepts from physics, chemistry and bioengineering, 'learning-by-building' approaches are becoming increasingly popular in the life sciences, especially with researchers who are attempting to engineer cellular life from scratch. The SynCell2020/21 conference brought together researchers from different disciplines to highlight progress in this field, including areas where synthetic cells are having socioeconomic and technological impact. Conference participants also identified the challenges involved in designing, manipulating and creating synthetic cells with hierarchical organization and function. A key conclusion is the need to build an international and interdisciplinary research community through enhanced communication, resource-sharing, and educational initiatives
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