Bio-inspired carbon electro-catalysis for the oxygen reduction reaction

We report the synthesis, characterisation and catalytic performance of two nature-inspired biomass-derived electro-catalysts for the oxygen reduction reaction in fuel cells. The catalysts were prepared via pyrolysis of a real food waste (lobster shells) or by mimicking the composition of lobster shells using chitin and CaCO3 particles followed by acid washing. The simplified model of artificial lobster was prepared for better reproducibility. The calcium carbonate in both samples acts as a pore agent, creating increased surface area and pore volume, though considerably higher in artificial lobster samples due to the better homogeneity of the components. Various characterisation techniques revealed the presence of a considerable amount of hydroxyapatite left in the real lobster samples after acid washing and a low content of carbon (23%), nitrogen and sulphur (<1%), limiting the surface area to 23 m2/g, and consequently resulting in rather poor catalytic activity. However, artificial lobster samples, with a surface area of ≈200 m2/g and a nitrogen doping of 2%, showed a promising onset potential, very similar to a commercially available platinum catalyst, with better methanol tolerance, though with lower stability in long time testing over 10,000 s.

A flexible bio-inspired hierarchical model for analyzing musical timbre

A flexible and multipurpose bio-inspired hierarchical model for analyzing musical timbre is presented in this paper. Inspired by findings in the fields of neuroscience, computational neuroscience, and psychoacoustics, not only does the model extract spectral and temporal characteristics of a signal, but it also analyzes amplitude modulations on different timescales. It uses a cochlear filter bank to resolve the spectral components of a sound, lateral inhibition to enhance spectral resolution, and a modulation filter bank to extract the global temporal envelope and roughness of the sound from amplitude modulations. The model was evaluated in three applications. First, it was used to simulate subjective data from two roughness experiments. Second, it was used for musical instrument classification using the k-NN algorithm and a Bayesian network. Third, it was applied to find the features that characterize sounds whose timbres were labeled in an audiovisual experiment. The successful application of the proposed model in these diverse tasks revealed its potential in capturing timbral information.

Aplicaciones de los modelos de predicción bio-inspirados en la administración

Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Binary Bat Algorithm for Feature Selection

Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

Optimal image colour extraction by differential evolution

Differential evolution is an optimisation technique that has been successfully employed in various applications. In this paper, we apply differential evolution to the problem of extracting the optimal colours of a colour map for quantised images. The choice of entries in the colour map is crucial for the resulting image quality as it forms a look-up table that is used for all pixels in the image. We show that differential evolution can be effectively employed as a method for deriving the entries in the map. In order to optimise the image quality, our differential evolution approach is combined with a local search method that is guaranteed to find the local optimal colour map. This hybrid approach is shown to outperform various commonly used colour quantisation algorithms on a set of standard images. Copyright © 2010 Inderscience Enterprises Ltd.

A learning approach to swarm-based path detection and tracking

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

Self-organized sociopolitical interactions as the best way to achieve organized patterns in human social systems: going beyond the top-down control of classical political regimes

La monografía presenta la auto-organización sociopolítica como la mejor manera de lograr patrones organizados en los sistemas sociales humanos, dada su naturaleza compleja y la imposibilidad de las tareas computacionales de los regímenes políticos clásico, debido a que operan con control jerárquico, el cual ha demostrado no ser óptimo en la producción de orden en los sistemas sociales humanos. En la monografía se extrapola la teoría de la auto-organización en los sistemas biológicos a las dinámicas sociopolíticas humanas, buscando maneras óptimas de organizarlas, y se afirma que redes complejas anárquicas son la estructura emergente de la auto-organización sociopolítica.

Expansion quality of epidemic protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for large and extreme-scale networked systems. This work investigates the expansion property of the network overlay topologies induced by epidemic protocols. An expansion quality index for overlay topologies is proposed and adopted for the design of epidemic membership protocols. A novel protocol is proposed, which explicitly aims at improving the expansion quality of the overlay topologies. The proposed protocol is tested with a global aggregation task and compared to other membership protocols. The analysis by means of simulations indicates that the expansion quality directly relates to the speed of dissemination and convergence of epidemic protocols and can be effectively used to design better protocols.

Connectivity recovery in epidemic membership protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for extreme-scale network system based on randomized communication. The protocols rely on a membership service to build decentralized and random overlay topologies. In a weakly connected overlay topology, a naive mechanism of membership protocols can break the connectivity, thus impairing the accuracy of the application. This work investigates the factors in membership protocols that cause the loss of global connectivity and introduces the first topology connectivity recovery mechanism. The mechanism is integrated into the Expander Membership Protocol, which is then evaluated against other membership protocols. The analysis shows that the proposed connectivity recovery mechanism is effective in preserving topology connectivity and also helps to improve the application performance in terms of convergence speed.

A core calculus for the analysis and implementation of biologically inspired languages

The application of Concurrency Theory to Systems Biology is in its earliest stage of progress. The metaphor of cells as computing systems by Regev and Shapiro opened the employment of concurrent languages for the modelling of biological systems. Their peculiar characteristics led to the design of many bio-inspired formalisms which achieve higher faithfulness and specificity. In this thesis we present pi@, an extremely simple and conservative extension of the pi-calculus representing a keystone in this respect, thanks to its expressiveness capabilities. The pi@ calculus is obtained by the addition of polyadic synchronisation and priority to the pi-calculus, in order to achieve compartment semantics and atomicity of complex operations respectively. In its direct application to biological modelling, the stochastic variant of the calculus, Spi@, is shown able to model consistently several phenomena such as formation of molecular complexes, hierarchical subdivision of the system into compartments, inter-compartment reactions, dynamic reorganisation of compartment structure consistent with volume variation. The pivotal role of pi@ is evidenced by its capability of encoding in a compositional way several bio-inspired formalisms, so that it represents the optimal core of a framework for the analysis and implementation of bio-inspired languages. In this respect, the encodings of BioAmbients, Brane Calculi and a variant of P Systems in pi@ are formalised. The conciseness of their translation in pi@ allows their indirect comparison by means of their encodings. Furthermore it provides a ready-to-run implementation of minimal effort whose correctness is granted by the correctness of the respective encoding functions. Further important results of general validity are stated on the expressive power of priority. Several impossibility results are described, which clearly state the superior expressiveness of prioritised languages and the problems arising in the attempt of providing their parallel implementation. To this aim, a new setting in distributed computing (the last man standing problem) is singled out and exploited to prove the impossibility of providing a purely parallel implementation of priority by means of point-to-point or broadcast communication.

Expressiveness in biologically inspired languages

A very recent and exciting new area of research is the application of Concurrency Theory tools to formalize and analyze biological systems and one of the most promising approach comes from the process algebras (process calculi). A process calculus is a formal language that allows to describe concurrent systems and comes with well-established techniques for quantitative and qualitative analysis. Biological systems can be regarded as concurrent systems and therefore modeled by means of process calculi. In this thesis we focus on the process calculi approach to the modeling of biological systems and investigate, mostly from a theoretical point of view, several promising bio-inspired formalisms: Brane Calculi and k-calculus family. We provide several expressiveness results mostly by means of comparisons between calculi. We provide a lower bound to the computational power of the non Turing complete MDB Brane Calculi by showing an encoding of a simple P-System into MDB. We address the issue of local implementation within the k-calculus family: whether n-way rewrites can be simulated by binary interactions only. A solution introducing divergence is provided and we prove a deterministic solution preserving the termination property is not possible. We use the symmetric leader election problem to test synchronization capabilities within the k-calculus family. Several fragments of the original k-calculus are considered and we prove an impossibility result about encoding n-way synchronization into (n-1)-way synchronization. A similar impossibility result is obtained in a pure computer science context. We introduce CCSn, an extension of CCS with multiple input prefixes and show, using the dining philosophers problem, that there is no reasonable encoding of CCS(n+1) into CCSn.

Miniemulsionen als räumliche Begrenzungen : Synthese von Polymer-Hydroxylapatit-Nanopartikeln, bio-inspirierten Nanokapseln und Polymer-Einzelkettenpartikeln

In der vorliegenden Arbeit wurden Miniemulsionen als räumliche Begrenzungen für die Synthese von unterschiedlichen funktionellen Materialien mit neuartigen Eigenschaften verwendet. Das erste Themengebiet umfasst die Herstellung von Polymer/Calciumphosphat-Hybridpartikeln und –Hybridkapseln über die templatgesteuerte Mineralisation von Calciumphosphat. Die funktionalisierte Oberfläche von Polymernanopartikeln, welche über die Miniemulsionspolymerisation hergestellt wurden, diente als Templat für die Kristallisation von Calciumphosphat auf den Partikeln. Der Einfluss der funktionellen Carboxylat- und Phosphonat-Oberflächengruppen auf die Komplexierung von Calcium-Ionen sowie die Mineralisation von Calciumphosphat auf der Oberfläche der Nanopartikel wurde mit mehreren Methoden (ionenselektive Elektroden, REM, TEM und XRD) detailliert analysiert. Es wurde herausgefunden, dass die Mineralisation bei verschiedenen pH-Werten zu vollkommen unterschiedlichen Kristallmorphologien (nadel- und plättchenförmige Kristalle) auf der Oberfläche der Partikel führt. Untersuchungen der Mineralisationskinetik zeigten, dass die Morphologie der Hydroxylapatit-Kristalle auf der Partikeloberfläche mit der Änderung der Kristallisationsgeschwindigkeit durch eine sorgfältige Wahl des pH-Wertes gezielt kontrolliert werden kann. Sowohl die Eigenschaften der als Templat verwendeten Polymernanopartikel (z. B. Größe, Form und Funktionalisierung), als auch die Oberflächentopografie der entstandenen Polymer/Calciumphosphat-Hybridpartikel wurden gezielt verändert, um die Eigenschaften der erhaltenen Kompositmaterialien zu steuern. rnEine ähnliche bio-inspirierte Methode wurde zur in situ-Herstellung von organisch/anorganischen Nanokapseln entwickelt. Hierbei wurde die flexible Grenzfläche von flüssigen Miniemulsionströpfchen zur Mineralisation von Calciumphosphat an der Grenzfläche eingesetzt, um Gelatine/Calciumphosphat-Hybridkapseln mit flüssigem Kern herzustellen. Der flüssige Kern der Nanokapseln ermöglicht dabei die Verkapselung unterschiedlicher hydrophiler Substanzen, was in dieser Arbeit durch die erfolgreiche Verkapselung sehr kleiner Hydroxylapatit-Kristalle sowie eines Fluoreszenzfarbstoffes (Rhodamin 6G) demonstriert wurde. Aufgrund der intrinsischen Eigenschaften der Gelatine/Calciumphosphat-Kapseln konnten abhängig vom pH-Wert der Umgebung unterschiedliche Mengen des verkapselten Fluoreszenzfarbstoffes aus den Kapseln freigesetzt werden. Eine mögliche Anwendung der Polymer/Calciumphosphat-Partikel und –Kapseln ist die Implantatbeschichtung, wobei diese als Bindeglied zwischen künstlichem Implantat und natürlichem Knochengewebe dienen. rnIm zweiten Themengebiet dieser Arbeit wurde die Grenzfläche von Nanometer-großen Miniemulsionströpfchen eingesetzt, um einzelne in der dispersen Phase gelöste Polymerketten zu separieren. Nach der Verdampfung des in den Tröpfchen vorhandenen Lösungsmittels wurden stabile Dispersionen sehr kleiner Polymer-Nanopartikel (<10 nm Durchmesser) erhalten, die aus nur wenigen oder einer einzigen Polymerkette bestehen. Die kolloidale Stabilität der Partikel nach der Synthese, gewährleistet durch die Anwesenheit von SDS in der wässrigen Phase der Dispersionen, ist vorteilhaft für die anschließende Charakterisierung der Polymer-Nanopartikel. Die Partikelgröße der Nanopartikel wurde mittels DLS und TEM bestimmt und mit Hilfe der Dichte und des Molekulargewichts der verwendeten Polymere die Anzahl an Polymerketten pro Partikel bestimmt. Wie es für Partikel, die aus nur einer Polymerkette bestehen, erwartet wird, stieg die mittels DLS bestimmte Partikelgröße mit steigendem Molekulargewicht des in der Synthese der Partikel eingesetzten Polymers deutlich an. Die Quantifizierung der Kettenzahl pro Partikel mit Hilfe von Fluoreszenzanisotropie-Messungen ergab, dass Polymer-Einzelkettenpartikel hoher Einheitlichkeit hergestellt wurden. Durch die Verwendung eines Hochdruckhomogenisators zur Herstellung der Einzelkettendispersionen war es möglich, größere Mengen der Einzelkettenpartikel herzustellen, deren Materialeigenschaften zurzeit näher untersucht werden.rn