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1. |
Record Nr. |
UNINA9910782096203321 |
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Titolo |
Bacterial physiology [[electronic resource] ] : a molecular approach / / Walid El Sharoud, editor |
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Pubbl/distr/stampa |
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Berlin, : Springer, c2008 |
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ISBN |
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Edizione |
[1st ed. 2008.] |
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Descrizione fisica |
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1 online resource (388 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Bacteria - Physiology |
Molecular biology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Subcellular Organisation in Bacteria -- Molecular Components of the Bacterial Cytoskeleton -- Mechanosensitive Channels: Their Mechanisms and Roles in Preserving Bacterial Ultrastructure During Adaptation to Environmental Changes -- Structural and Functional Flexibility of Bacterial Respiromes -- Protein Secretion in Bacterial Cells -- Regulation of Transcription in Bacteria by DNA Supercoiling -- Quorum Sensing -- Environmental Sensing and the Role of Extracytoplasmic Function Sigma Factors -- Extracellular Sensors and Extracellular Induction Components in Stress Tolerance Induction -- Ribosome Modulation Factor -- The Role of RpoS in Bacterial Adaptation -- Phenotypic Variation and Bistable Switching in Bacteria. |
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Sommario/riassunto |
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The application of new molecular methodologies in the study of bacterial behaviour and cell architecture has enabled new revolutionary insights and discoveries in these areas. While this has also raised a number of scientific mysteries about bacteria, it certainly improved our understanding of these organisms as complex and adaptive entities rather than just simple tiny buckets of enzymes. The value of this recent knowledge in bacterial physiology is not only restricted to fundamental biology, but it also extends to biotechnology and drug-discovery disciplines where understanding cell behaviour and structure is essential for better exploitation of useful bacteria and effective eradication of harmful ones. This makes a new text accommodating recent developments in bacterial physiology highly relevant to a wide |
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range of readership including those interested in basic and applied knowledge. |
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2. |
Record Nr. |
UNINA9910797013003321 |
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Autore |
König Lukas |
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Titolo |
Complex behavior in evolutionary robotics / / Lukas König |
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Pubbl/distr/stampa |
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Boston : , : De Gruyter, , [2015] |
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©2015 |
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ISBN |
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1-5231-0453-8 |
3-11-040855-4 |
3-11-040918-6 |
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Descrizione fisica |
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1 online resource (262 p.) |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Front matter -- Acknowledgements -- Contents -- List of Figures -- List of Tables -- List of Notations -- 1. Introduction -- 2. Robotics, Evolution and Simulation -- 3. The Easy Agent Simulation -- 4. Evolution Using Finite State Machines -- 5. Evolution and the Genotype-Phenotype Mapping -- 6. Data Driven Success Prediction of Evolution in Complex Environments -- 7. Conclusion -- References -- Index |
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Sommario/riassunto |
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Es werden vier neue Lösungsansätze für Probleme aus dem Bereich Evolutionäre Robotik bzw. Agenten-Simulation wissenschaftlich untersucht. Von besonderem Interesse ist eine neuartige Methode zur Imitierung der natürlichen Evolution in ihrer Fähigkeit, die eigenen Mutations- und Rekombinationsoperationen während der Evolution von Robotern anzupassen. |
Today, autonomous robots are used in a rather limited range of applications such as exploration of inaccessible locations, cleaning floors, mowing lawns etc. However, ongoing hardware improvements (and human fantasy) steadily reveal new robotic applications of |
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significantly higher sophistication. For such applications, the crucial bottleneck in the engineering process tends to shift from physical boundaries to controller generation. As an attempt to automatize this process, Evolutionary Robotics has successfully been used to generate robotic controllers of various types. However, a major challenge of the field remains the evolution of truly complex behavior. Furthermore, automatically created controllers often lack analyzability which makes them useless for safety-critical applications. In this book, a simple controller model based on Finite State Machines is proposed which allows a straightforward analysis of evolved behaviors. To increase the model's evolvability, a procedure is introduced which, by adapting the genotype-phenotype mapping at runtime, efficiently traverses both the behavioral search space as well as (recursively) the search space of genotype-phenotype mappings. Furthermore, a data-driven mathematical framework is proposed which can be used to calculate the expected success of evolution in complex environments. |
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