دانلود کتاب Biological Functions For Information And Communication Technologies: Theory And Inspiration

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Column 1: Hierarchy in Nature and Society and Pascal’s ‘‘Pensées’’ [3, 4]......Page 2
4.2.1 Some Preliminaries of the Biochemistry of Signal Transduction......Page 4
Column 3: Darwin’s Theory of Evolution and Motoo Kimura’s Neutral Theory of Evolution......Page 6
Acknowledgements......Page 7
Cover......Page 1
Prologue......Page 5
Column 5: Hypothesis for Mechanism Underlying Inspiration (the Aha! Experience)......Page 9
3.3…Topological Properties of Intermolecular Interactions......Page 13
1.2.1 Brain Structures and Their Functions......Page 15
Column 1: Artificial Neural Networks and Machine Learning......Page 17
Column 9: Hierarchy in Nature and Society and Emergent Networks......Page 21
Column 10: Emergent Network Mechanism [48--50]......Page 22
1.2.4 Expansion of Time-Delay Neural Networks to Rotation-Invariant Pattern Recognition [9]......Page 23
References......Page 24
Column 2: Genetic Algorithms [11, 28, 29]......Page 25
1.3.1 Parameter-Free Genetic Algorithms [12] Based on Disparity Theory of Evolution [13]......Page 27
4.5…Summary......Page 28
References......Page 29
3.4…Evaluating Artificial Chemistry Systems......Page 30
Column 3: The Disparity Theory of Evolution [13, 31 -- 33]......Page 31
1.3.2.1 Two Parallel Processing Architectures......Page 32
1.3.2.2 Two Migration Methods......Page 33
1.3.2.3 Performance Results......Page 34
1.3.3 Information Processing Model Based on Gene Duplication [15]......Page 35
References......Page 36
Column 4: Theory of Gene Duplication [16 -- 18, 34]......Page 37
Column 5: Sexual Selection [35 -- 38]......Page 39
1.3.4.6 Steps in Simulation......Page 42
1.3.4.8 Results of Experiment......Page 43
1.3.4.9 Search Process......Page 44
1.4.1.1 Mechanisms of Cell Metabolism Generated in the Early Stages of the Evolutionary Process......Page 45
1.4.1.3 GA Evolvability (See Fig. 1.39)......Page 47
Biological Functions for Information and CommunicationTechnologies......Page 3
Contents......Page 8
4.3.1 Temporal Dynamics of Signal Transduction Networks......Page 10
Abstract......Page 11
1.1.2 Nature’s Hierarchy......Page 12
5.2.1.2 Network Analysis Indicators......Page 14
1.2.2 Neural Networks Modeling Brain Function......Page 16
Column 8: Applying Complex Networks [19--22, 31]......Page 18
1.2.3 Time-Delay Neural Networks Suitable for Processing Sequential Information and Their Expansion [4--8]......Page 19
5.2.3.1 Organization Network Strategy......Page 20
3.3.4.0 Random-Walk Simulation of Hard Spheres......Page 26
1.3.4 Information Processing Model Based on Sexual Selection [19]......Page 38
1.3.4.4 Sexual Selection......Page 41
1.4.1.2 CGA Generation Cycle (See Fig. 1.38)......Page 46
1.4.1.5 Performance Comparison Among SGA, CGA and PfGA......Page 49
1.4.2 Chemical Genetic Programming (CGP) [23]......Page 52
1.4.2.1 Example of Application 1: Symbolic Regression Problems [23]......Page 54
Column 8: Amorphous Computing......Page 56
References......Page 57
2.1…Introduction......Page 60
Column 1: Molecular Communication......Page 61
2.2.1 Passive Transport-Based Molecular Communication......Page 63
3.6.2.0 Execution Operations......Page 64
2.2.2 Active Transport-Based Molecular Communication......Page 65
Column 3: Communication in Our Body......Page 66
2.3…Molecular Communication Architecture......Page 68
2.3.2 Molecular Communication Processes......Page 69
2.3.2.1 Encoding......Page 70
1.3.4.1 Constructing a Computational Model......Page 40
Column 6: Genetic Programming......Page 53
1.4.2.2 Example of Application 2: Behavioral Strategy of Agents [24]......Page 55
Abstract......Page 59
Column 2: Potentials of Molecular Communication......Page 62
Column 4: Intracellular Material Transport......Page 67
2.3.2.3 Propagation......Page 71
2.3.3.2 Large Communication Delay......Page 72
2.3.3.3 Molecule Based Coding......Page 73
Column 5: Communication Model......Page 74
Column 6: How Many Bits of Information can be Transmitted via Molecular Communication?......Page 75
2.4.1.1 Synthetic Biological Cells......Page 76
2.4.1.2 Artificial Cells......Page 77
Column 7: Engineering Nanomachines I......Page 78
Column 8: Engineering Nanomachines II......Page 80
2.5.1.1 Free-diffusion Based Molecular Communication......Page 81
2.5.1.2 Gap Junction Mediated Reaction--Diffusion Based Molecular Communication......Page 82
2.5.2.1 Molecular Motor-based Molecular Communication......Page 84
2.5.2.2 Bacterial Motor-based Molecular Communication......Page 85
2.6…Engineering of Communication Mechanisms......Page 86
Column 9: Pattern Formation......Page 88
Column 10: A Molecular Communication System......Page 89
Column 11: DNA Molecules Walk......Page 90
Column 12: Recent Activities and Future Challenges......Page 92
2.7…Summary......Page 93
References......Page 94
Abstract......Page 97
3.1…Introduction......Page 98
3.2.1 Basic Elements of Design in Artificial Chemistry......Page 99
3.2.2 Requirements for Artificial Chemistry System’s Design: From the Perspective of Evolution and Emergence......Page 100
Column 1: Von Neumann’s Self-reproducing Automata......Page 108
3.3…Topological Properties of Intermolecular Interactions......Page 109
3.3.1 Intermolecular Forces and Chemical Reaction Velocity Theory......Page 110
Column 2: Chemical Reaction Velocity Theory......Page 112
3.3.2 Topological Conditions on Molecular Movement......Page 117
3.3.3 Intermolecular Distance and the Molecular Network......Page 118
3.3.4 Topological Properties of the Molecular Network......Page 119
Column 3: Small-World Network......Page 120
3.3.4.0 Random-Walk Simulation of Hard Spheres......Page 122
Column 4: Parameter Setting for Hard Sphere Random-Walk Simulations......Page 123
3.3.4.0 Simulation Results......Page 125
3.4…Evaluating Artificial Chemistry Systems......Page 126
3.5.1 Basic Concept......Page 134
3.5.2.0 Complementary Matching......Page 135
Column 6: Data-Flow Machine......Page 137
3.5.2.0 Basic Model......Page 138
3.5.2.0 Mathematical Folding of Node Chains......Page 139
3.5.2.0 Operation of Data-Flow Clusters......Page 140
3.5.2.0 Replication of Node Chain......Page 142
3.5.3 Passive Rewiring Rule Based on Energy Minimization......Page 143
3.5.3.0 Experimental Results......Page 145
Column 7: Formulation of Energy-Based NAC Edge Rewiring......Page 148
3.5.4 Organization of Network Structure by Active Node Program......Page 150
Column 8: Amorphous Computing......Page 152
3.5.4.0 Model......Page 153
3.6.1 Concept......Page 156
3.6.2 Formation and Splitting of Hydrophilic Cluster by Molecular Agents......Page 157
3.6.2.0 Graph Elements......Page 159
3.6.2.0 Execution Operations......Page 160
Basic Setting......Page 161
3.7…Future Prospects......Page 162
3.7.1 Application to the Graph Coloring Problem......Page 164
3.7.2.0 The Academic Frontier, Intelligent Information Science Project......Page 165
References......Page 166
4.1…Introduction......Page 172
Column 1: Network Motifs......Page 174
4.2.1 Some Preliminaries of the Biochemistry of Signal Transduction......Page 175
4.2.2 Graphic Representation for Signal Transduction......Page 176
Column 2: Signaling Pathway Network......Page 177
Column 3: Michaelis--Menten Kinetics......Page 178
4.2.3 Example of Pathway: The MAPK Cascade......Page 179
4.3.1 Temporal Dynamics of Signal Transduction Networks......Page 181
4.3.2 Fixed Point for Pathways with Feedbacks......Page 182
4.3.2.1 The Model for the Simulation......Page 183
4.3.2.2 Simulation......Page 185
4.3.3 Robustness......Page 186
4.3.3.1 Basic Concepts......Page 187
4.3.3.2 Stability Analysis: From an Example of the Mos-p MAPK Pathway for Explanation of Stability......Page 188
Column 5: Error-Correcting Code......Page 192
4.4.1 Molecular Coding from Molecular Communication......Page 194
4.4.2 LDPC Coding for Pathways......Page 195
Column 6: Low-Density Parity-Check Code (LDPC)......Page 198
4.5…Summary......Page 199
References......Page 200
Abstract......Page 201
Column 1: Hierarchy in Nature and Society and Pascal’s ‘‘Pensées’’ [3, 4]......Page 202
Column 2: Einstein and the Theory of Relativity [2, 5--9]......Page 203
Column 3: Darwin’s Theory of Evolution and Motoo Kimura’s Neutral Theory of Evolution......Page 206
5.1.2 3.8 Billion Years’ Stream of Life......Page 208
Column 4: Phylogenetic Tree and Molecular Clocks......Page 209
5.2…Solution by Complex Networks Toward the Problems in the Real World......Page 211
5.2.1.1 Phenomena, Structures, Laws, and Characteristics in Complex Networks......Page 212
5.2.1.2 Network Analysis Indicators......Page 214
5.2.1.3 A Network Architecture Resistant to Both Random Failure and Targeted Attack [36--38]......Page 215
5.2.2 Application Fields of Complex Networks......Page 216
Column 7: Application of Slime Mold to Maze Search......Page 217
Column 8: Applying Complex Networks [19--22, 31]......Page 218
5.2.3.1 Organization Network Strategy......Page 220
5.2.3.4 Distribution Field......Page 221
Column 10: Emergent Network Mechanism [48--50]......Page 222
5.3…Summary......Page 224
Epilogue......Page 227
Index......Page 229