Crossing in Complexity: Interdisciplinary Application of Physics in Biological and Social Systems

CROSSING IN COMPLEXITY: INTERDISCIPLINARY APPLICATION OF PHYSICS IN BIOLOGICAL AND SOCIAL SYSTEMS......Page 4
CONTENTS......Page 6
FOREWORD......Page 8
1. “ZIP Filing the World”......Page 10
2. The Folding Problem......Page 12
3. Radical Emergence: Pyrococcus Furiosus......Page 14
Acknowledgments......Page 17
References......Page 18
Brief History of Atomism......Page 20
Necessity of the New Ontology......Page 21
Philosophical Viewpoint from Substance to Function......Page 22
Process and the Cyclic Ontology......Page 23
Mathematical Formalism of Cyclic Ontology......Page 24
The Heisenberg Equation......Page 25
References......Page 28
Introduction......Page 30
Hodgkin and Huxley......Page 31
Warren McCulloch......Page 32
Brains, Machines and Mathematics......Page 34
The Automata-Theoretic Approach to Brain Theory......Page 35
Below the Neuron......Page 36
Population Coding and the Ergodic Hypothesis......Page 37
Cooperative Computation in Neural Fields......Page 38
Regularization......Page 39
Schema Theory......Page 40
Space, The Final Frontier......Page 42
Information Theory and Statistical Mechanics......Page 46
Nonlinear Dynamic Systems......Page 48
Bringing in Plasticity: Hebbian, Error-Based and Reinforcement......Page 49
Bridging the Levels: From Behavior to Neurochemistry......Page 51
Self-Organization......Page 53
Brain Evolution......Page 54
From Brain to Mind: Psychology and Linguistics......Page 55
The Brain Doing Mathematics......Page 58
Against Platonism......Page 59
References......Page 61
Abstract......Page 66
1. Introduction......Page 67
A. Destabilizing Effect of Liouville feedback......Page 71
B. Emergence of Randomness......Page 73
C. Emergence of Entanglement......Page 75
D. Summary......Page 78
A. Information Potential......Page 79
B. Negative Diffusion......Page 80
A. General Model......Page 82
B. Simplified Model......Page 83
D. Variation Principle......Page 85
A. Mathematical Viewpoint......Page 86
B. Physical Viewpoint......Page 87
γ. Decoherence......Page 88
C. Biological Viewpoint......Page 89
D. Psychological Viewpoint......Page 91
E. Neuro-Science Viewpoint......Page 92
γ. Mirror Neural Nets......Page 93
δ. Link to Quantum Entanglement......Page 96
F. Social and Economic Viewpoint......Page 97
G. Language Communications Viewpoint......Page 98
A. Measure of Survivability......Page 100
B. Mental Complexity via Reflection of Information......Page 101
C. Image Dynamics: What Do You Think I Think You Think…......Page 103
α. Attractors in Motor Dynamics......Page 107
β. Attractors in Mental Dynamics......Page 108
E. Hierarchy of Higher Mental Abstractions......Page 109
F. Abstraction and Survivability......Page 110
G. Activation of New Levels of Abstractions......Page 111
H. Summary......Page 112
B. Intelligent Control in Livings......Page 113
β. The Model......Page 118
γ. Decision Making Process......Page 122
δ. Decision via Choice of Attractors......Page 123
ε. Decision via Phase Transition......Page 125
D. Emergent Intelligence......Page 127
8. Data-Driven Model Discovery......Page 129
A. General Remarks......Page 132
B. Model Extension......Page 133
Acknowledgment......Page 139
References......Page 140
1. Introduction......Page 142
2.1. Charge-Transfer in DNA......Page 143
3.1.a. Inclusion of the Details on Differences in Mass of Bases in Watson-Crick Pairs......Page 144
3.1.b. Inclusion of the Details on Differences in Frequencies of Base RotationalOscillations in Phase and Out of Phase......Page 146
3.1.c. Inclusion of the Details on Interactions between Bases in Watson-Crick Pairs......Page 148
3.2. Tendency to Simplify DNA Models Up to the Model of Englander......Page 149
3.2a. Englander’s Model Applied to Study Effects of Dissipations......Page 150
3.2.b. Englander’s Model Applied to Study Effects of External Field......Page 151
3.2.d. Englander’s Model Applied to Study DNA Kink Propagation through theBoundary between Two Homogeneous Regions......Page 152
4. Conclusive Remarks......Page 154
References......Page 155
Abstract......Page 160
1.1.Analyzing and Optimizing in Biotechnology......Page 161
2.Modeling Gene-Expression Data......Page 162
2.2.1.A Quasi-Linear, Multiplicative Model......Page 163
2.3.Gene Regulation— An Example......Page 164
2.3.1.Nonlinear Model with Quadratic or Higher Degree Polynomials......Page 165
2.4.The Extended Model......Page 166
3.1.Runge-Kutta Method......Page 168
3.2.Algebra of Matrix Products......Page 170
3.3.Stability Analysis of a Set of Matrices......Page 173
3.4.Modeling Gene Regulatory Networks with Piecewise Linear Differential\rEquations......Page 174
3.5.1.Introduction......Page 176
3.5.3.Estimation Equations for Additive Models......Page 177
3.5.4.Penalized Regression Problems and Inverse Problems......Page 178
3.5.6.Stochastic Differential Equations......Page 179
3.6.Related Topics and Future Projects......Page 182
4.Conclusion......Page 183
References......Page 184
Introduction......Page 190
Results and Discussion: A Tale of Formalization......Page 192
References......Page 198
Abstract......Page 200
References......Page 205
Introduction......Page 208
From the Pleistocene to the Internet......Page 209
The Leading Eight......Page 210
A Model of Conflict and Cooperation......Page 211
Results......Page 214
Prompt Forgiving and Implacable Punishment......Page 215
The Emergence of Good and Evil......Page 216
Discussion......Page 217
Methods......Page 218
References......Page 220
1.Evolution of Cooperative Behaviors......Page 222
2.Description of Games as Dynamical Systems......Page 223
3.The Lumberjack’s Dilemma Game......Page 225
4.Review of Akiyama & Kaneko 2002......Page 227
5.Dynamics of Coupled Players......Page 230
5.1.The Effect of the Environmental Coupling......Page 231
5.2.The Effect of the Player’s Coupling......Page 232
5.3.Strategy Space for Productive Dynamics......Page 233
Acknowledgment......Page 234
References......Page 235
Introduction......Page 238
Notions of Time......Page 240
Levels of Description: The Endo and Exo-Perspective......Page 243
Simultaneity, Succession, Duration and the Now: Physical Theories are Secondary Constructs of Our Primary Experiences of Time......Page 244
B. Succession......Page 245
C. Duration and the Now......Page 246
Fractal Time......Page 247
Temporal Natural Constraints......Page 252
Observer Perspectives: The Fractal Temporal Interface......Page 254
Participation: Temporal Embedding......Page 256
TNCs Revisited: Embodiment......Page 257
Conclusion......Page 259
References......Page 260
INDEX......Page 264