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• Foreword.- Introduction.- About protocells.- Why modelling protocells.- Collective self-replication.- Self-replication in a vesicle.- Self-replication in a reproducing protocell.- Generic properties of dynamical models of protocells.- Introduction. -Generic properties of biological systems: data.- Generic properties of biological systems: concepts.- What shall we model.- Dynamical models of protocells and synchronization.- Simplified surface-reaction models of protocells.- Synchronization in surface reaction models.- Several linearly interacting replicators.- Several interacting replicators with nonlinear interactions.- Internal reaction models.- Models of self-replication.- Introduction.- Autocatalytic sets.- The properties of some replication models.- Products and substrates.- Reflexive autocatalytic food-generated (raf) sets.- A stochastic model of growing and dividing protocells.- Semipermeable protocells.- The role of active membranes.- The effects of passive membranes.- Coupled dynamics of rafs and protocells.- Maintaining novelties.-A comment on evolvable populations of protocells.- Conclusions, open questions and perspectives.- Introduction.- The hypothesis of spontaneous fission and synchronization.- The formation of self-sustaining autocatalytic cycles.- The role of membranes.- A virtual laboratory.
• (source: Nielsen Book Data)

The monograph discusses models of synthetic protocells, which are cell-like structures obtained from non-living matter endowed with some rudimentary kind of metabolism and genetics, but much simpler than biological cells. They should grow and proliferate, generating offsprings that resemble in some way the parent protocells with some variation, so that selection may take place. Sustainable protocell populations have not yet been obtained experimentally and mathematical models are therefore extremely important to address key questions concerning their synthesis and behavior. Different protocell "architectures" have been proposed and high-level abstract models like those that are presented in this book are particularly relevant to gain a better understanding of the different properites. These models are able to treat all the major dynamical phenomena in a unified framework, so they can be seen as "virtual laboratories" for protocell research. Particular attention is paid to the problem of synchronization of the fission rate of the whole protocell and the duplication rate of its "protogenetic" material, which is shown to be an emergent property that spontaneously develops in successive generations.The book is of interest for a broad range of scientists working in soft matter physics, chemistry and biology, interested in the role protocells may play on the development of new technologies with medical, environmental and industrial applications as well as scientists interested in the origin of life.
(source: Nielsen Book Data)

• One Artefact - Many Phenomena.- Taming the Complexity of Natural and Artificial Evolutionary Dynamics.- Models of Gene Regulation: Integrating Modern Knowledge into the Random Boolean Network Framework.- Attractors Perturbations in Biological Modelling: Avalanches and Cellular Differentiation.- Automatic Design of Boolean Networks for Modeling Cell Differentiation.- Towards the Engineering of Chemical Communication Between Semi-synthetic and Natural Cells.- Cumulative Learning Through Intrinsic Reinforcements.- Development of Categorization Abilities in Evolving Embodied Agents: A Study of Internal Representa-tions with External Social Inputs.- Regulatory Traits: Cultural Influences on Cultural Evolution.- Building up Serious Games with an Artificial Life Approach: Two Case Studies.- The Effects of Multivalency and Kinetics in Nanoscale Search by Molecular Spiders.- Towards the Use of Genetic Programming for the Prediction of Survival in Cancer.- A Neuro-evolutionary Approach to Electrocardiographic Signal Classification.- Self-organisation and Evolution for Trust-Adaptive Grid Computing Agents.- Honest vs. Cheating Bots in PATROL-Based Real-Time Strategy MMOGs.- Distribution Search on Evolutionary Many-Objective Optimization: Selection Mappings and Recombination Rate.- Concurrent Implementation Techniques Using Differential Evolution for Multi-core CPUs: A Comparative Study Using Statistical Tests.
• (source: Nielsen Book Data)

Evolution and complexity characterize both biological and artificial life - by direct modeling of biological processes and the creation of populations of interacting entities from which complex behaviors can emerge and evolve. This edited book includes invited chapters from leading scientists in the fields of artificial life, complex systems, and evolutionary computing. The contributions identify both fundamental theoretical issues and state-of-the-art real-world applications. The book is intended for researchers and graduate students in the related domains.
(source: Nielsen Book Data)

• Diffusion of Shapes (R S Shaw & N H Packard)
• FDC-Based Particle Swarm Optimization (A Azzini et al.)
• Predictive Neural Networks in the Design of Experiments (D De March et al.)
• Prefrontal Cortex and Action Sequences: A Review on Neural Computational Models (I Gaudiello et al.)
• Bio-Inspired ICT for Evolutionary Emotional Intelligence (M Villamira & P Cipresso)
• Cooperation in Corvids: A Simulative Study with Evolved Robots (O Miglino et al.)
• Distributed Processes in a Agent-Based Model of Innovation (L Ansaloni et al.)
• Imaginary or Actual Artificial Worlds Using a New Tool in the ABM Perspective (P Terna)
• Dynamics of Interconnected Boolean Networks with Scale-Free Topology (C Damiani et al.)
• Semi-Synthetical Minimal Cells (P Stano & P L Luisi)
• and Other Papers.
• (source: Nielsen Book Data)

The Italian community in Artificial Life and Evolutionary computation has grown remarkably in recent years, and this book is the first broad collection of its major interests and achievements (including contributions from foreign countries). The contributions in Artificial Life as well as in Evolutionary Computation allow one to see the deep connections between the two fields. The topics addressed are extremely relevant for present day research in Artificial Life and in Evolutionary Computation, which include important contributions from very well-known researchers. The volume provides a very broad picture of the Italian activities in this field.
(source: Nielsen Book Data)

• Diffusion of Shapes (R S Shaw & N H Packard)
• FDC-Based Particle Swarm Optimization (A Azzini et al.)
• Predictive Neural Networks in the Design of Experiments (D De March et al.)
• Prefrontal Cortex and Action Sequences: A Review on Neural Computational Models (I Gaudiello et al.)
• Bio-Inspired ICT for Evolutionary Emotional Intelligence (M Villamira & P Cipresso)
• Cooperation in Corvids: A Simulative Study with Evolved Robots (O Miglino et al.)
• Distributed Processes in a Agent-Based Model of Innovation (L Ansaloni et al.)
• Imaginary or Actual Artificial Worlds Using a New Tool in the ABM Perspective (P Terna)
• Dynamics of Interconnected Boolean Networks with Scale-Free Topology (C Damiani et al.)
• Semi-Synthetical Minimal Cells (P Stano & P L Luisi)
• and Other Papers.
• (source: Nielsen Book Data)

The Italian community in Artificial Life and Evolutionary computation has grown remarkably in recent years, and this book is the first broad collection of its major interests and achievements (including contributions from foreign countries). The contributions in Artificial Life as well as in Evolutionary Computation allow one to see the deep connections between the two fields. The topics addressed are extremely relevant for present day research in Artificial Life and in Evolutionary Computation, which include important contributions from very well-known researchers. The volume provides a very broad picture of the Italian activities in this field.
(source: Nielsen Book Data)

Metallic nanoparticles can be used to enhance optical absorption or emission in semiconductors, thanks to a strong interaction of collective excitations of free charges (plasmons) with electromagnetic fields. Herein we present direct imaging at the nanoscale of plasmon-exciton coupling in Au/ZnO nanostructures by combining scanning transmission electron energy loss and cathodoluminescence spectroscopy and mapping. The Au nanoparticles (~30 nm in diameter) are grown in-situ on ZnO nanotetrapods by means of a photochemical process without the need of binding agents or capping molecules, resulting in clean interfaces. Interestingly, the Au plasmon resonance is localized at the Au/vacuum interface, rather than presenting an isotropic distribution around the nanoparticle. Moreover, on the contrary, a localization of the ZnO signal has been observed inside the Au nanoparticle, as also confirmed by numerical simulations.