The introduction outlines the flow of the book and how to make best use of it. It provides a summary of each chapter as well and details where to find the code and how to run it.

Two basic characteristics of adaptation, plasticity and robustness, are discussed. The former concerns itself with changeability – how a system changes its internal state in response to environmental changes, and the latter concerns itself with robustness – how most internal states are unaltered by environmental changes. Although such changes which occur as part of the adaptation process have been explained as an evolved signal transduction system, a generic adaptation mechanism without it is strongly requested, considering the genericity of adaptation. Here, it is shown that adaptation, that is, the selection of an attractor with a higher growth rate, can occur without specific signaling circuits, by considering the dilution of each component by cell growth, the homeostatic process in which components are synthesized to compensate for this dilution, in the presence of noise in the reaction process. Constructive experiments and simulations demonstrating such attractor selection are presented. This attractor selection can occur even when the adaptive attractor is not prepared in advance. Although direct experimental verification of attractor selection has not yet been achieved, it is a strong candidate to explain observed spontaneous adaptation. Besides the abovementioned adaptation with significant state change, the experimental evidence for a passive adaptation mechanism by fluctuation is also presented.

The band theory of solids is developed and used to explain the properties of conductors, insulators, and semiconductors (both pure and doped). Type n and p semiconductors are introduced and combined to form the p-n junction or diode. Analysis of diode circuits is introduced, followed by several applications of diodes. As a lead-in to power supply circuits, rectification, filtering, and regulation are discussed. Zener diodes are introduced and applications are given. The silicon-controlled rectifier and some applications are presented. Photodiode operation and the resulting circuit analysis are given, along with a discussion of optimization. An introduction to switching power supplies (boost, buck, and buck-boost) is presented.

This chapter introduces the fundamental concepts and rules of quantum computing. In parallel, it develops an initial, easy-to-understand Python code base for building and simulating small-scale quantum circuits and algorithms. The chapter details single qubits, superposition, quantum states with many qubits, operators, including a sizable set of important single-qubit gates and controlled gates. The Bloch sphere and the quantum circuit notation are introduced. Entanglement follows, that fascinating “spooky action at a distance,” as Einstein called it. The chapter then discusses maximally entangled Bell states, the no-cloning and no-deleting theorems, local and global phases, and uncomputation. The quantum postulates are discussed briefly as preparation for the discussion on measurements.

A variety of digital devices and circuits are introduced. The use of binary numbers in digital electronics is discussed. The AND, OR, XOR, NOT, NAND, NOR, XNOR, and buffer logic gates are presented, followed by a discussion of implementing logical functions. The Karnaugh map and Boolean algebra are introduced. Different ways of constructing logic gates are presented. Half- and full-adder circuits are developed. Several types of flip-flops are discussed. Building on this foundation, we introduce counters, decoders, shift registers, D/A and A/D converters, multiplexers, demultiplexers, memory arrays, automated processing, programmable logic devices, and digital EM communications.

During development, cells sequentially lose their ability to differentiate into other cell types and become committed to different cellular states. This process can be described as a landscape in which the valleys are canalized one by one. This process of canalization is understood in terms of dynamical systems of interacting cells. In fact, as cells with oscillating gene expression proliferate and interact with each other, they differentiate into other expression states. Cells with oscillatory gene expression have pluripotency, either to replicate the same state or to differentiate into other cellular states, whereas cells that differentiate and lose their oscillations of expression simply replicate themselves, that is, they are committed. The proportion of each cell type is robust to changes in initial conditions and noise perturbations. Differentiation by protein expression dynamics is further stabilized by a feedback process of epigenetic modifications, such as DNA modification. The irreversibly differentiated cell state can be initialized to a pluripotent state by restoring an oscillatory state by forcing the expression of multiple genes from the outside, known experimentally as reprogramming.

Oscillator circuits, categorized into relaxation and sinusoidal types, are introduced. Three examples of relaxation oscillators are given and analyzed: the SCR sawtooth, the transistor astable, and the 555 astable. Monostable operation of the 555 timer is also discussed. For sinusoidal oscillators, examples include a transistor RC, an op-amp Wien bridge, a Hartley, and a Pierce oscillator. Oscillator stability is discussed. Electromagnetic communications (AM and FM) are discussed as applications of oscillators.

Capacitors and inductors are introduced, along with their equivalent circuit laws. Switched RC circuits are thoroughly analyzed. The response of an RC circuit to a sinusoidal drive voltage is analyzed and leads to a discussion of high- and low-pass filters, phase shifters, integrators, and differentiators. The use of complex numbers in circuit analysis is introduced and applied to sinusoidally driven series RC, LR, and LRC circuits as well as the switched LRC circuit. Fourier analysis and its meaning are presented. The operation of transformers is introduced.

This chapter presents an overview of the goals of universal biology. It is noted that biological systems are generally hierarchical as molecules-cells-organisms, where the components of each level are quite diverse. How such diversity arises and is maintained is discussed. We then discuss the possibility of understanding such biological systems with diverse components, and explore the possibility of macroscopic theory to reveal and formulate universal properties in living states, noting that robustness, plasticity, and activity are essential to life. Recalling the spirit (not the formulation) of thermodynamics, we explore the possibility of formulating a theory for characterizing universal properties in life, emphasizing macroscopic robustness at each level of the hierarchy and the importance of macro-micro consistency.

Cells reproduce under nonequilibrium conditions. By noting that a cell contains enzymes that drastically increase the equilibration process, it is shown that a cell is an apparatus that reveals the nonequilibrium property of the environment and accelerates equilibration. As a consequence, the entropy generation rate per cell growth is minimized at a finite growth rate, not in the adiabatic limit as in the Carnot cycle. General statistical properties of cells are then presented, including the power law in abundances and the lognormal distribution of cell-to-cell variation. The transition from exponential growth to the dormant state (where cell growth is arrested) is shown to be a general consequence of the accumulation of waste (non-autocatalytic) components, which leads to a jamming of the reaction. Related experiments using single-cell measurements elucidate the distribution of cell-to-cell variation in protein concentrations and growth rates. How cell reproduction and molecular replication achieve consistency is also a fundamental question for constructing protocells and understanding the origin of life. The relationship between minority molecules and genetic information, the synchronization of minority molecular replication and cell division, the separation of genetic information and catalytic function, and the acquisition of evolutionary potential are discussed as universal properties that must be satisfied for all cell reproduction systems.

Consider the evolutionary process under fixed environmental conditions, where genetic change leads to phenotypic change, and fitness is given as a function of phenotype. In this case, the variance Vip of the fluctuation of the phenotype due to noise is proportional to the rate of evolution of the phenotype, termed as evolutionary fluctuation–response relationship. It then implies that Vip is proportional to Vg, the variance due to genetic variation, as derived theoretically under the assumption of evolutionary robustness: the acquisition of phenotypic robustness to noise through evolution also leads to robustness to genetic variation. Here, as the mutation rate increases (or the noise level in the dynamics decreases), a phenotypic error catastrophe occurs, where it is no longer possible to maintain the fit phenotype. While phenotypic variance and evolvability decrease under fixed environmental and fitness conditions, they rise and fall repeatedly as environmental conditions are varied over generations. Phenotypic plasticity and evolvability are maintained under environmental variation. Strong selection under fixed evolutionary conditions can lead to the appearance of mutants with increased phenotypic variance. This may be due to over-optimization to obtain the fit phenotype, which may break consistency with other processes and reduce robustness.