Life Origin
A Scientific Approach
Edited for the Non-ScientistGLOSSARY
Abiogenesis—the belief that life emerged spontaneously from non-life through natural process.
Adjacent other—the wonderfully inviting, mystical, poetic notion of Stuart Kauffman describing his belief in a spontaneously arising formal capability of physicodynamics (the inanimate mass/energy interactions, forces and laws of motion that are the subject of physics). Unfortunately, such imagination is purely metaphysical, never once observed, unfalsifiable, and has never logged a single prediction fulfillment. It can best be described as superstition or fairy tale—certainly not science.
Agency—the ability to choose from among real options and to voluntarily pursue goals such as formal utility. Agents are able to program logic gates, steer courses of action through long strings of decision nodes, and assemble and organize objects and events to create potential function—function not yet existent at the time choices must be made. Agency is invariably associated with life. Life itself is utterly dependent upon cybernetic programming—a phenomenon never observed independent of agency.
Algorithm—a step-wise, discrete process or procedure—often computational—leading to future utility. Algorithms require wise choices at decision nodes, logic gates and configurable switches prior to the realization of any function. Algorithms cannot be generated by after-the-fact natural selection of the fittest computational result or already-programmed species.
Animate—living.
Arbitrary—unconstrained by initial conditions or cause-and-effect determinism. As used in the context of cybernetics, arbitrary means more specifically choice-contingent, not chance-contingent. Arbitrary does not mean that the chooser flips a coin to decide, or that the chooser does not care what is chosen. Symbol systems, for example, require purposeful, choice-contingent assignment of certain symbolic “strokes of pen” to represent specific meaning. By convention, arbitrary rules of interpretation are followed that allow sender and receiver to communicate the same meaning and function from those symbols and symbol syntax.
Artificial Selection—change brought about by the purposeful choice contingency of agents selecting from among real options at bona fide decision nodes. Change induced by choice-contingent causation and control (CCCC). Selection FOR POTENTIAL fitness—something that natural selection cannot do.
Axiom-a deductively underivable, and empirically and logically unprovable, propositional statement that is tentatively assumed to be true, or self-evident, and which serves as the basis for a whole deductive system of thought and inference.
Bijection—a mapping, correspondence, or translation, usually one to one, of one symbol system to another. When Hamming redundancy block-coding is used to reduce noise pollution in the Shannon channel, mapping can be many to one (e.g. triplet codons prescribing each amino acid).
Blueprint—a two-dimensional picture, or composite of signs, representing the plans of a building or other physical structure. The term blueprint is often misapplied to genetic and genomic instruction. Genomics does not employ signs or blueprints. Codons serve only as block codes of symbols in a formal linear digital material symbol system (MSS). No direct physicochemical interaction is involved in the polycodonic prescription of polyamino acid sequencing that determines which protein is produced in ribosomes.
Chance contingency—non-willful, non-steered independence from apparent “necessity” (cause-and-effect determinism). Possibilities and options are not purposefully chosen, but result from “the roll of the dice.” Chance contingency gives rise to random variation—“noise.” The Brownian motion caused by the heat agitation of molecules is an example of seeming chance contingency. “Just how random is randomness?” remains an open question. Many have argued that seemingly random events are actually the result of thus-far unknown causes, and highly complex interactions between multiple known physicodynamic causes.
Chaos—disorganization, not disorder! Abundant highly-ordered dissipative structures of Prigogine’s chaos theory form momentarily out of chaos in nature. No spontaneous dissipative structure shows any evidence of formal organization. In fact, most self-ordered dissipative structures such as hurricanes and tornadoes only destroy organization.
Chemoton—Tibor Ganti’s abstract model of the simplest all-or-none unit of life. It consists of three non-living, autocatalytic chemical components: a motor, boundary, and prescriptive information system. The stable motor is capable of self-reproduction and synthesis of everything needed for the other two subsystems. The chemical boundary is envisioned to be semipermeable and to allow transport in of needed nutrients and the excretion of wastes. The prescriptive information must be capable of self-replication and must control, not just constrain, metabolism, growth, and reproduction. The chemoton model lacks enzymes and genetic code. The problems with Ganti’s model are many, starting with the fact that no one has ever observed such a minimal unit of life short of the cell itself. The mechanisms provided in the model are entirely inadequate to explain the derivation of most of this unit’s attributes and capabilities.
Choice contingency—freedom from determinism involving a purposeful selection from among real options. Choice contingency is exercised by agents with intent for a reason and purpose. The goal of choice contingency is almost always some form of utility that is valued by the chooser.
Choice-Contingent Causation and Control (CCCC)—the steering of physical events and the organizing of physical entities into potential usefulness. CCCC can generate extraordinary degrees of unique functionality that have never been observed to arise from randomness or law-described necessity. Neither physicodynamics nor evolution can pursue potential utility (e.g., the programming of computational success prior to its realization). CCCC does. CCCC is the only known cause and governor of formalisms.
Code—a representational symbol system used to assign associations (e.g. via a codon table) or to convey meaningful messages (e.g., messenger molecules). In an everyday connotation, coding signs and symbols are usually substituted for letters or words. Most codes (e.g., ASCII, Zip code) are "open," (non-encrypted) with arbitrary meaning to communicate between two independent worlds. The codon/amino acid code is the most widely known code in life, but more than 20 other biosemiotic codes have been discovered in the past decade, each with no known physicochemical "cause." In molecular biology, genetic code is specifically used for:
♦ instantiation of formal, immaterial programming choices into physicality;
♦ efficiency in translation between two different material symbol systems where molecules serve as “physical symbol vehicles” (tokens) in two different material symbol systems (MSS) rather than being mere physicochemical interactants/reactants;
♦ ease-of-transmission;
♦ noise pollution prevention in the Shannon channel (e.g., redundancy block coding);
♦ proof reading and error correction (e.g. the processing of parity bit coding to detect noise pollution).
Complexity—the opposite of regularity, order, redundancy, and pattern. Complexity does not lend itself to algorithmic compressibility. Maximum complexity corresponds to randomness which contains no order, pattern or compressibility. Complexity is at opposite extremes with order on a bidirectional vector. Combinatorial complexity itself has nothing to do with functionality or the choice-contingent causation and control (CCCC) that generates nontrivial utility. The only relation of complexity to positive formalism is the mathematical probabilism used to measure complexity’s negative uncertainty.
Composome—a hypothesized “metabolism-first” model referred to as an “ensemble replicator” or “compositional genome.” The model imagines a self-reproducing assembly of different molecular species that manifests protometabolic “networks.” The model was advanced because of serious problems with 1) template replication, 2) non-enzymatic biopolymer synthesis, and 3) a lack of Prescriptive Information (PI) source to program functional sequencing in RNA-World related models. No explanation has ever been provided for how protometabolic cybernetic networks could have spontaneously organized from physicodynamics alone, or how an ensemble of molecular species could have reliably reproduced themselves. Recent work by well-known and respected investigators has shown that the replication of compositional “information” is so inaccurate that fitter composomes could not possibly have evolved into metabolism-first life forms.
Configurable Switch—a purely physical device designed specifically to record (instantiate) nonphysical, formal choices into physical reality without any influence of physicodynamic forces, laws and constraints. Configurable switch settings are physicodynamically indeterminate (inert, decoupled, incoherent).
Configurable Switch (CS) Bridge—the one-way bridge that spans The Cybernetic Cut. Choice contingency causation and control (CCCC) traverses the vast ravine known as The Cybernetic Cut allowing traffic only from the formal far side to the physicodynamic near side. All formal meaning, function and bona fide organization enters the physical realm via this one-way bridge. Through “configurable” switch settings, formal choice contingency can become a source of physical causation. The setting of these configurable switches and logic gates constitutes the building of the CS Bridge. Nonphysical formalism itself can never be physical. In addition, the chance and necessity of physicality cannot steer objects and events towards formal utility. Chance and necessity cannot compute or make programming choices. Mere constraints cannot control or regulate. The inanimate environment does not desire or pursue function over nonfunction. So how does physicality ever get organized into usefulness of any kind? How does stone and mortar ever become a building? The answer lies in our ability to build a CS Bridge from the far side of The Cybernetic Cut—the formal side of reality—to the near side—the physicodynamic (physical) side of the ravine. The scaffolding needed to build this bridge consists of devices that allow instantiation of formal choices into physical recordations of those choices. This is accomplished through the construction of physical logic gates—the equivalent of Maxwell’s demon’s trap door. The gate can be opened or closed by agent choice at different times and in difference contextual circumstances. The open or shut gate corresponds to “yes” vs. “no,” “1” vs. “0.” Because the gate can be opened or closed by the operator at will, we call it a “configurable” switch. Another means of crossing the one-way CS Bridge across The Cybernetic Cut is to select physical symbol vehicles (tokens) from an alphabet of tokens available in a material symbol system. Assembling components into a holistic Sustained Functional System (SFS) or machine is another example of the one-way traffic flow across the CS Bridge from formalism to physicality.
Computational halting—a program finishes running rather than going on forever. Computational “success” is usually implied with the term halting, meaning that the program does what it is supposed to do within a finite period of time.
Constraints—a restriction or limitation of possibilities caused by initial (starting) conditions or by the regularities of nature described by physical law. Constraints themselves play no role in steering, controlling or regulating events to achieve formal function. Constraints are blind to formalisms. However, constraints can constitute barricades and bottlenecks for agent-pursued goals.
Contingency—in a past-tense context, contingency means that an event could have occurred other than how it happened. In a present and future context, contingency means that events can unfold in multiple ways despite both local and seemingly universal law-like constraints. Contingent behavior is not forced by physicodynamic necessity. Contingency embodies an aspect of freedom from physicochemical determinism.
Control—to purposefully steer toward the goal of formal function and pragmatic success. To regulate. To select for potential usefulness.
Cybernetic Cut—the most fundamental dichotomy of reality. The dynamics of physicality (“chance and necessity”) lie on one side of a great divide. On the other side lies the ability to choose with intent what aspects of ontological being will be preferred, pursued, selected, rearranged, integrated, organized, preserved, and used (formalism). Life is unique from inanimate physics and chemistry in that life’s control and regulation arise from the far side of The Cybernetic Cut.
Cybernetics—the study of control and of various means of programming, organizing, steering, and regulating physicality. Mere physicodynamic constraints are blind and indifferent to formal success. Only controls, not constraints, steer events toward pragmatic goals such as being alive and staying alive.
Decision nodes—bifurcation points which cannot be traversed by a mere “flip of the coin,” at least not if one expects pragmatic results or reliable escape from danger. Decision nodes, as the name implies, require wise purposeful choices to achieve goals. A classic example is the purposeful setting of a “logic gate” in computing in order to integrate circuits or achieve computational success.
Decision theory—the study of various outcomes resulting from purposeful decisions at bona fide decision nodes. Decision nodes are more than mere “bifurcation points,” which could be traversed using a fair coin flip to determine which way to go at each “fork in the road.” When decision nodes are replaced with mere bifurcation points, universal experience shows a rapid deterioration of formal function potential.
Decode—to decipher the meaning of a message through mapping representational symbols to meaningful language or computation. The interpretation of symbols and symbol syntax in a symbol system.
Decrypt—to decode, but with the connotation that the original encoding was not “open,” but written with the intent to make decoding very difficult by an enemy at war, for example.
Descriptive Information (DI)—positive background semantic information coming from an external source that serves to reduce uncertainty and to educate one’s knowledge. DI provides valued common-sense knowledge to human beings about the way things already are. Thus, being can be described to provide one form of Functional Information (FI: intuitive and semantic information). However, the DI subset of FI is very limited and grossly inadequate to address many forms of instruction (Prescriptive Information (PI) and “how to” information for design, creativity, engineering, control and regulation.
Dissipative Structures of Chaos Theory—spontaneously self-ordered, momentary phenomena usually occurring in rapid succession so as to give the impression of a sustained structure (e.g., a candle flame; a tornado). Dissipative structures occur naturally out of mass/energy interactions alone. They require no choice-contingent causation and control (CCCC). Dissipative structures are often mistakenly viewed as evidence of self-organization in nature when in fact they example nothing more than spontaneous self-ordering with no formal components and no attention to the goal of functionality of any kind.
Edge of Chaos—the wonderfully inviting and mystical notion of complexity pursued by Christopher Langton, Doyne Farmer, J.P. Crutchfield, Melanie Mitchell, Stuart Kauffman and others that loosely describes a state of spontaneously realizable formal capability and self-organization arising out of physicodynamics alone. Melanie Mitchell has since questioned the validity of this notion. Such imagination is purely metaphysical, unobserved in inanimate nature, unfalsifiable, and no record exists of a single prediction fulfillment. It can best be described only as superstition or fairy tale, except where formalism is smuggled in through the back door to illegitimately redefine such terms as “phase transitions” and “constraints” (e.g., using the word “constraints” to mean formal “controls,” where the constraints of inanimate cause-and-effect determinism are illegitimately granted the ability to purposefully steer events toward formal functionality or pragmatic success).
Emergence—the spontaneous occurrence in nature of more complex patterns arising from multiple simpler interactions. The spontaneous formation of symmetrical patterns in snowflakes during atmospheric precipitation is an example of emergence arising from purely physicodynamic self-ordering. Candle flame shapes, vortices of swirling water at bathtub drains, tornadoes and hurricanes all self-order spontaneously into rapid successions of momentary dissipative structures (the subject of chaos theory). Poorly understood is that no known cases of emergent self-ordering have anything to do with organization, and especially not “self-organization.” Organization is formal and always arises through choice contingent causation and control (CCCC) from the far side of The Cybernetic Cut. No instance of bona fide “self-organization” has ever been observed; only unimaginative, redundant, lo-informational, self-ordering occurs spontaneously in inanimate nature out of chaos (which means disorganization, not disorder!).
Encode—to use a symbol system to represent, record and communicate meaningful messages. Molecular biology stores and passes along into progeny Prescriptive Information (PI, of which linear digital cybernetic programming is a major component) needed for organization and metabolic function. Encoding involves conversionary algorithms that biject or translate one symbol system into another.
Encrypt—to encode using a symbol system not easily deciphered and purposefully inaccessible to unwanted decoders.
Entropy—energy not available for formally useful work; the progressing formal disorganization observed in nature that is so often erroneously confused with increasing “disorder.” Evidence of the 2nd Law is regularly observed with simultaneous increases in order, as with crystallization. Clearly, increasing entropy is not synonymous with increasing disorder. Physicodynamic entropy is not the same as informational entropy, which is a measure of epistemological uncertainty associated with a random variable. Informational entropy is a purely formal concept which, being nonphysical, has nothing to do with mass or energy, and everything to do with mathematical probabilism.
Epigenetic—the study of variation in heritable gene expression that is not caused by variation in nucleotide sequence of the genes. Histone deacetylation and DNA methylation are classic examples of gene suppression that does not affect nucleotide sequencing. Such alterations continue to alter gene expression throughout multiple future generations. Differentiation of the zygote (fertilized egg) into different cell types during development involves still other aspects of epigenetic control.
Epigenomics—the study of factors such as epigenetic DNA methylation, histone protein modifications, and chromatin structure on overall genomics and upper-level DNA structural (three-dimensional) Prescriptive Information (PI).
Falsifiability—the possibility that a claim, particularly a universal assertion, can be evaluated and potentially refuted by empirical testing showing results incongruous with that claim. The capability of disproving a proposition, hypothesis or theory by showing logical contradiction , or by finding, through experimentation, repeatable contradictory exceptions.
Fits—functional bits. The measurement of Functional Sequence Complexity,denoted as z , is defined as the change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)), or z = ∆ H (Xg(ti), Xf(tj)). The resulting unit of measure is defined on the joint data and functionality variable. The unit Fit thus defined is related to the intuitive concept of functional information, including genetic instruction and, thus, provides an important distinction between functional information and Shannon information.
Formal—relating to Plato’s forms and Aristotle’s appreciation of general classes of form and function that transcend particular physical structure and shape. Formal behavior is abstract, mental, arbitrary, nonphysical, and choice-contingent. The cognitive behavior of agents is typically goal- and function-oriented.
Formalism—a system of rules of thought or action typically involving symbol systems and requiring choices to be made at decision nodes, logic gates or configurable switch settings. Formalisms employ conceptual representationalism, mathematics, language, and/or categorical groupings of related ideas. Formalisms arise out of uncoerced choices in the pursuit of function and utility. Formalisms are typically computationally successful, integrated-circuit producing, and/or algorithmically optimizing. Formalisms require bona fide decision nodes, not just “bifurcation points. Language, mathematics, programming, and logic theory are all formalisms. Formalisms are governed by arbitrary rules, not laws. Listed below are aspects of reality that are all formalisms. None of these formalisms can be encompassed by a consistently held naturalistic worldview that seeks to reduce all things to physicodynamics:
♦ Mathematics;
♦ Language;
♦ Inferential and deductive logic theory;
♦ The sign/symbol/token systems of semiosis;
♦ Decision theory;
♦ Cybernetics (including computer science);
♦ Computation;
♦ Integrated circuits;
♦ Bona fide organization (as opposed to mere self-ordering in chaos theory);
♦ Semantics (meaning);
♦ Pursuits of goals ;
♦ Pragmatic procedures and processes ;
♦ Art, literature, theatre, ethics, aesthetics;
♦ The personhood of scientists themselves;
All of the above formalisms depend upon choice contingency rather than chance contingency or necessity. Formalism also entails choices made in pursuit of potential function. Natural selection (NS) cannot select for potential function. NS can only favor the fittest already-programmed, already-existing, already living phenotypic organisms.
Formalism > Physicality (F > P) Principle—the most fundamental axiom of science states that Formalism not only describes, but preceded, prescribed, organized, and continues to control, regulate, govern and predict physicodynamic reality and its inter-actions. The F > P Principle is an axiom that defines the ontological primacy of formalism. Formalism is the source of all aspects of reality, both nonphysical and physical. Formalism organized physicality before the fact of physicality’s existence. Formalism gave rise to the equations, structure and orderliness of physicality rather than to chaos (disorganization, not disorder!). This alone explains why the scientific method must be conducted in a rational manner, why the applicability of mathematics to physical interactions is reasonable rather than unreasonable, and why formalism can reliably predict physical interactions. The quest for a mathematical unified field of knowledge presupposes the F > P Principle. The F > P Principle further states that reality is fundamentally arbitrary—rule and choice-contingency based, not indiscriminately forced by an infinite regress of cause-and-effect determinism. Physicality cannot even spawn a study of itself—physics—because physics is a formal enterprise. Nothing within the “chance and necessity” of physicality itself is capable of generating formal logic, computation, mathematical relationships, or cybernetic control. Only formalisms can measure, steer, manage, and predict physicality. Physicodynamics constrains; formalism controls.
Function—usefulness; utility; contributing to productivity and efficiency. “A function is a goal-oriented property of an entity," Says Voie. "Functional parts are only meaningful under a whole, in other words it is the whole that gives meaning to its parts" [ 3 ].
Functional Sequence Complexity (FSC)—a sequence of subunits that produces utility in some larger context, as a string of amino acids performing a protein function of importance and value in a larger metabolic scheme. Also, a linear, digital, cybernetic string of symbols representing syntactic, semantic and pragmatic prescription; each successive symbol in the string is a representation of a decision-node configurable switch setting---a specific selection for potential function. FSC prescribes or produces usefulness, usually via algorithmic processing.
Functional Information (FI)—Intuitive semantic information that serves some purpose such as educating prior uncertainty, or instructing how to accomplish some goal. FI technically has two subsets: Descriptive (DI) and Prescriptive (PI), each discussed in this glossary.
Genetic Code—the arbitrary representational symbol system used by life to assign associations (e.g. via a codon table) or to convey meaningful messages (e.g., messenger molecules). In an everyday connotation, coding signs and symbols are usually substituted for letters or words. The codon/amino acid code is the most widely known code in life, but more than 20 other biological semiotic codes have been discovered in the past decade, each with no known physicochemical "cause." In molecular biology, genetic code is specifically used for:
♦ instantiation of formal, immaterial programming choices into physicality ;
♦ efficiency in translation between two different material symbol systems where molecules serve as “physical symbol vehicles” (tokens) in two different material symbol system (MSS) rather than being mere physicochemical interactants/reactants ;
♦ ease-of-transmission ;
♦ noise pollution prevention in the Shannon channel (e.g., redundancy block coding) ;
♦ proof reading and error correction (e.g. the processing of parity bit coding to detect noise pollution) ;
Genetic Selection (GS) Principle—states that biological selection must occur at the point when the sequencing of monomers is established. Nucleotides must be selected at the molecular-genetic level of 3'5' phosphodiester bond formation. After-the-fact differential survival and reproduction of already-programmed, already-living phenotypic organisms (natural selection) does not explain polynucleotide sequence prescription and coding.
Genetics—the study of the prescription of form, function and metabolic contribution by the arbitrarily programmed material symbol system of polynucleotide sequencing in DNA. Triplet codon sequence in coding regions is translated into amino acid sequence in ribosomes which in turn determines minimum Gibbs-free-energy folding into three-dimensional protein globular structure. Genetics includes not only the study of coded genetic control through the inheritance of discrete units called genes, but variation through mutations, environmental factors, and the effects of many non-coding regulatory RNAs and epigenetic elements that affect biomolecular structure, function, metabolism and phenotypic expression.
Genomics—a more holistic study than genetics that investigates the interactions of all of the various networks of the entire genome, mRNA transcriptome, and proteome. Genetics tends to focus more on the effects of individual gene knock-outs. Genomics includes a study of pleiotropy (where one gene affects multiple phenotypic traits), epistasis (where additional modifier genes affect a single main gene), and heterosis (where outbreeding leads to hybrid vigor).
Hamming Block Code—an error-correcting redundancy code using a fixed or constant number of multiple loci comprising each “block” of a linear string of symbols to represent each prescribed unit of instruction. Triplet codons in coding regions of DNA, for example, always consist of a block of three nucleotides in a row to prescribe each amino acid. Discounting the stop codons, 61 ways exist to prescribe formally 20 amino acid options in the ribosomes. Catastrophic “frame shift” errors can result if decoding is not begun at the correct starting locus in the string, or if the number of loci in each block does not remain constant, or if additional amino acids are added to the code through time (each of which needing a new triplet codon block of representational symbols). The latter realities make the notion of gradual evolution of the genetic code from purely physicodynamic factors fraught with seemingly insurmountable problems.
Hypercycle—an autocatalytic cycle induced by circular constraints that lead to redundant self-replication. Hypercycles are envisioned to generate formal self-organization and progressively higher levels of formal organization. The model suffers from the confusion of formal programming and organizational controls with mere circular physicodynamic constraints. In the real world, these self-reinforcing loops lead only to the consumption of all resources in the production of the same few redundant products. The result is the depletion of the tremendous phase space that would be needed for any other theoretically contributing players to “evolve” into a legitimate protometabolism. Like all molecular evolution models of life origin, it suffers from a lack of organizational directionality and pursuit of formally useful interactive products. Empirical support for Eigen and Schuster’s original notion of spontaneous hypercycles and their ever-increasing protometabolic competence has never accumulated.
Inanimate—non-living.
Instantiate—to insert or infuse aspects of one category into another normally separate and distinct category. In the context of cybernetics, the term is used to denote incorporating programming choices into physical computational devices. Nonphysical formalisms can only be instantiated into physical reality through the setting of configurable switches, the selection of “physical symbol vehicles” (tokens) from an alphabet of tokens, or though the design and engineering of physical devices (e.g., sophisticated machines, robots). In object-oriented analysis, design and programming, creating an object from a class is called instantiating the class. A class has certain aspects that are “infused”, or become aspects of the object. Therefore, the word “instantiate” in this context involves not a “separate and distinct” category, but an “instance” of the category (class).
Law of Organizational and Cybernetic Deterioration/Decline (OCD Law)—The OCD Law states that, absent the intervention of formal agency, any nontrivial organization or cybernetic/computational function instantiated into physicality (e.g., integrated circuits; programmed computational success) will invariably deteriorate and fail through time. This deterioration may not be continual. However, it will be continuous (off and on, but overall consistently downhill). Computers, robots, all forms of Artificial Intelligence and Artificial Life, messages instantiated into material symbol systems or electronic impulses, will invariably progress toward dysfunction and fail. The OCD Law is not to be confused with the Second Law of Thermodynamics. The OCD Law is not concerned with the entropy of statistical mechanics or the “entropy” or “mutual entropy” of Shannon’s probabilistic combinatorial uncertainty. Heat exchange, heat dissipation, phase changes, order and disorder are not at issue. The OCD Law addresses only the formal organization and utility already instantiated into physical media and environments. Only purposeful choice contingency at bona fide decision nodes can rescue from deterioration the organization and function previously programmed into physicality.
Law of Physicodynamic Incompleteness—an axiomatic proposition stating that physicochemical interactions are inadequate to explain the mathematical and formal nature of physical law relationships. Physicodynamics cannot generate formal processes and procedures leading to nontrivial function. Chance, necessity and mere constraints cannot steer, program or optimize algorithmic/computational success to provide desired nontrivial utility. nanimate physicodynamics is completely inadequate to generate, or even explain, the mathematical nature of physical interactions (the laws of physics and chemistry). The Law further states that physicodynamic factors cannot institute formal processes and procedures leading to sophisticated function. Chance and necessity alone cannot steer, program or optimize algorithmic/computational success to provide desired nontrivial utility. As a major corollary, physicodynamics cannot explain or generate life. Life is invariably cybernetic. Inanimate physics and chemistry are inadequate to explain the spontaneous self-organization of even a protometabolism, let alone the generation of life from non-life (abiogenesis.)
Laws—generalized reduction algorithms, extracted and derived from observed regularities in reams of data, describing and predicting different aspects of regular physical interactions in nature despite varying initial conditions.
Linear digital symbol system—A system of recordation, transmission, and communication of messages between sender and receiver made possible by both following the same set of arbitrarily assigned rules of formal symbolization. Messages consist of a succession of discrete symbols and symbol syntax having arbitrarily assigned meaning and communicative function. Language, computer programs consisting of a succession of 0’s and 1’s, and polycodonic prescription of amino acid sequence in proteins by coding DNA are examples of linear digital symbol systems.
Liposomes—artificially produced vesicles designed to deliver drugs and other agents to various locations within living cells, and used to mimic hypothesized protocells in life-origin studies.
Logic gates—a type of cybernetic configurable switch that can be set to either open or closed in a binary programming mode. Logic gates allow formal purposeful choices to be instantiated into physical computational systems and integrated circuits.
Machine—a physical device, often a relatively independent functioning contrivance, that utilizes mass and energy to accomplish a nonphysical formal function. The classical definition of machine involved the forces of motion and power to accomplish some desired task referred to as “work.” Such “work” is far more than the mere transfer of energy. Even the “simple machines” are used by agents to transform the direction or magnitude of a force in order to accomplish a desired goal. Physicodynamics do not pursue goals. The advent of electronics and computers broadened our definition of “machine” no longer to require moving parts. Molecular biology has opened our eyes further to a vast array and coordinated interplay of the most sophisticated machines of all—molecular machines.
Macroevolution—the belief that evolution can spontaneously give rise to ever more sophisticated genetic and genomic PI programming, and to increasing conceptual complexity in organisms, giving rise to “higher” families, orders, classes, and phyla. No observations or prediction fulfillments exist in support of macroevolution. Falsification is not possible, raising the question of whether the notion of macroevolution is a scientifically respectable theory.
Material Symbol System (MSS)—A symbol system that formally assigns representational meaning to physical objects (tokens, physical symbol vehicles). The Game of Scrabble employs physical symbol vehicles, wood block tokens with inscribed symbols, that can be resorted to spell meaningful words and messages.
Meaning—Aboutness; function; the sense, importance, significance, implication, value, consequence, import or purpose of a message; the reason for sending a communication. In molecular biology, “meaning” is usually defined in terms of contribution to biofunction and holistic metabolism.
Mechanism—a means, directed process, programmed procedure, technique, system, or component of a machine that achieves some pragmatic goal. “Mechanism” is a formal term, not a physicodynamic term. “Mechanism,” like the term “useful work,” has no place in a consistently held naturalistic physics and chemistry context. The etiology of “mechanism” from both Latin and Greek derives from the word “machine.” Metaphysical naturalism has never demonstrated the ability of physicodynamics and so-called “natural process” to produce nontrivial machines or sophisticated pragmatic mechanisms.
Message—a signal that contains interpretable meaning, and that manifests or fosters functionality at its destination. A signal that conveys Descriptive (DI) and/or Prescriptive Information (PI), both of which are subsets of Functional Information (FI).
Metabolism-First World—a model of life-origin that proposes that a protometabolism spontaneously self-organized, probably in a vesicle, without the aid of any Prescriptive Information contained in a material symbol system (such as DNA nucleotide or codon sequence) or RNA memory or catalysis. Variations include the Garbage-First model, Clay Life and other Mineral First models, Chemoton World, Peptide World, Lipid World, and Protein world.
Micelle—a spherical aggregate of surfactant molecules containing often containing a liquid colloid. In water, the surfactant molecules spontaneously self-order (NOT formally organize) with the hydrophilic (water-loving) “heads” aimed outward towards the aqueous solvent, and the hydrophobic (water-hating) tails aimed into the center of the sphere. A micelle is a crudely self-ordered structure similar to an oil-in-water droplet.
Microevolution—the universally acknowledged, spontaneously acquired, change in heritable phenotypic traits within a species, possibly within a family, but never extending to evolutionary transition to a more conceptually complex (“higher”) order, class or phyla.
Molecular evolution—as used in this volume, molecular evolution pertains mostly to prebiotic evolution from inanimate molecules into a living state—abiogenesis. Of prime interest is how ordinary molecules could have self-organized, in a formal sense, under the influence only of physicochemical forces and attractions, to produce so many integrated biochemical pathways, cycles, highly tailored “parts” or components, and such goal-oriented holistic metabolism. All of these are needed to organize and sustain even the simplest conceivable life form.
Multiverse—the purely metaphysical rather than scientific notion that this Universe is only one of countless universes.
Mutations—alterations in genomic nucleotide sequencing, including the ribonucleotide sequencing of RNA viruses. A special case of mutation is when protein structure “mutates” (misfields) in prions in a way that affects the folding of other protein molecules in that family. Prion misfoldings are contagious and are subject to natural selection. Replication errors, mutagenic chemicals, radiation, transposons and deliberate hypermutation in immune cells are common causes of mutations. Mutations can be neutral (having no selective advantage, and no immediate apparent deleterious phenotypic effect), deleterious (most mutations), or in extremely rare instances, beneficial, at least in some very indirect way (e.g., sickle cell anemia rendering erythrocytes more resistant to the malaria parasite). The very recent discovery of vast new areas of functionality performed by non-coding DNA and non-mRNAs raises the question of whether most supposedly neutral mutations are really neutral. Far more likely is the progressive accumulation of noise pollution of what were highly refined regulatory instructions, the effects of which will only become apparent through time as our knowledge of molecular biology and microRNA regulation grows.
Natural selection—differential survivability and reproduction of the best already-programmed, already-living phenotypic organisms. Natural selection (NS) has no creative programming ability at the genetic or genomic level (See The GS Principle). NS is purely eliminative of less fit phenotypes. It cannot program genomes or other material symbol systems at the molecular level. Natural selection results only in the differential preservation and reproduction of the fittest already-existing organisms.
Necessity—a term often used almost synonymously with Law, as in Monod’s Chance and Necessity, referring to the physicodynamic cause-and-effect determinism of inanimate nature. Necessity refers to regular physical interactions in nature that are so dependable, despite varying initial conditions, that the outcomes seem unavoidable, completely predictable, or “necessary.”
Neural net—originally, the central nervous system consisting of circuits of neurons and their interconnections. Artificial neural networks are mathematical and computational models of the central nervous system and are used to model information processing and artificial intelligence. Neural networks are formal cybernetic constructs, not just physicodynamic “buttons and strings.”
Noise—chance-contingent, meaningless, non-functional, unwanted disturbances or perturbations that corrupt meaningful, functional, desired, choice-contingent messages and Prescriptive Information (PI) commands.
Order—regularity, recurring pattern, redundancy, algorithmic compressibility. Order is antithetical to complexity and at opposite extremes with complexity on a bidirectional vector. Maximum complexity corresponds to randomness, which contains no order or compressibility. Order contains very little information, whereas organization typically contains high Prescriptive Information (PI) content from instantiated choice contingent causation and control (CCCC).
Ordered Sequence Complexity (OSC)—a linear string of linked units, the sequencing of which is patterned either by the natural regularities described by physical laws (necessity) or by statistically weighted means(e.g., unequal availability of units), but which is not patterned by deliberate choice contingency (agency). OSC is marked by repetition or redundancy, or recurring pattern in its sequence. Reuse of programing modules or structures needed for construction can create the illusion of OSC when in fact the recurring pattern is generated by choice contingency (FSC). The more highly ordered (patterned) a sequence, the more highly compressible that sequence becomes, the less Shannon uncertainty, and the less potential prescriptive information that can be instantiated into that sequence.
Organization—the choice-contingent association, categorization, configuring, steering, controlling, arranging or integrating of ideas or physical parts into a productive scheme, system or device that accomplishes formally useful work. Organization should never be confused with low-informational “order” or “pattern.” Organization typically arises only out of high Prescriptive Information (PI) and sophisticated choice-contingent causation and control (CCCC).
Organization (O) Principle—Nontrivial formal Organization can be produced only by Choice-Contingent Causation and Control (CCCC). See Chap 12, Sec 9.
Panspermia—the belief that life originated elsewhere in the Universe and was spread to earth, probably by meteoroids or asteroids. This same definition applies to exogenesis. Panspermia suggests that life is more generalized throughout the Cosmos, whereas exogenesis does not necessarily make this claim. The notion of panspermia does nothing to help explain how life could have spontaneously self-organized out of nothing but physicodynamics. It does little to extend the time available for molecular evolution since the Big Bang, since the age of the cosmos is believed to be only three times that of the earth.
Pattern—predictable, regular or repetitive form. A recurring, compressible order that reduces Shannon uncertainty and the ability to instantiate functional choices (semantic information) into that medium. Patterns can arise, however, in meaningful messages and programs from deliberate reuse of linguistic elements and programming modules.
Peptide World hypothesis—the belief that life arose as a metabolism-first self-organization from interactions between short peptides and polypeptides. Adherents to this model point to the near impossibility of spontaneous ribonucleotide formation in a prebiotic environment, activation problems of ribonucleotides, difficulties of polymerization bond formation in water, short half-lives, etc.
Phenotype—the already-programmed, already-organized, already-living, holistic physical organism.
Physical symbol vehicle—a token; a physical object employed as a formal representational symbol. Meaning is consciously assigned arbitrarily to each physical object, thereby making possible the instantiation of choice contingency into the physical world. The physical token then functions as a formal meaningful and functional symbol in a material symbol system rather than as a physical interactant. The blocks of wood with inscribed letters in a Scrabble game, or the nucleotides in genes serve as physical symbol vehicles.
Physicodynamic determinism—cause-and-effect physicochemical interactions that lead back in an infinite regress of determinism to some physical first cause. Physicodynamic determinism, often referred to as “necessity,” does not explain the reality of choice contingency—the freedom to choose from among real options to achieve choice-contingent causation and control (CCCC). It also does not explain the rational, mathematical and formal nature of reality.
Physicodynamically indeterminate—contingent; undetermined by cause-and-effect determinism; could have happened other than it did; having multiple possible options despite initial constraints and the laws of physics and chemistry.
Physicodynamically inert—physicodynamically indeterminate; contingent; undetermined by cause-and-effect determinism; could have happened other than it did; having multiple possibilities or options of occurrence despite initial constraints under the laws of physics and chemistry.
Physicodynamically incoherent—physicodynamically indeterminate; contingent; undetermined by cause-and-effect determinism; could have happened other than it did; having multiple possibilities or options of occurrence despite initial constraints under the laws of physics and chemistry.
Physicodynamic discontinuity—physicodynamically indeterminate; contingent; undetermined by cause-and-effect determinism; could have happened other than it did; having multiple possibilities or options of occurrence despite initial constraints under the laws of physics and chemistry.
Potential function—formal function not yet existent, which, when nontrivial, only comes into existence through advanced planning, assembling of component parts or processes, programming and engineering choices. Physicodynamics alone is incapable of producing sophisticated formal function. Natural selection (NS) cannot select for potential function at the genetic programming level (The GS Principle). NS can only prefer existing fittest phenotypic organisms.
Pragmatic—functional, useful, helpful, utilitarian, productive, contributory to a larger or higher organization or goal.
Prebiotic—referring to the inanimate physical environment (nature) that existed prior to the origin of life.
Prescriptive Information (PI)—a subset of Functional Information (FI) that either instructs or indirectly produces nontrivial formal function. PI is semantic “how to” information. PI provides the instructions required to organize and program sophisticated utility. Potential formal function and computational success must be prescribed in advance by PI programming prior to halting, not just described after the fact. PI requires anticipation and “choice with intent” at bona fide decision nodes. PI either tells us what choices to make, or it is a recordation of wise choices already made. PI is positive, as opposed to negative uncertainty. Prescriptive information (PI) does far more than merely describe (Descriptive Information [DI])). We can thoroughly describe a new Mercedes automobile, providing a great deal of DI in the process. However, this functional DI might tell us almost nothing about how to design, engineer and build that Mercedes. PI provides the instructions required to organize and program sophisticated utility. PI designs, creates, engineers, controls and regulates. The inanimate physical environment is incapable of participating in such formal pursuits. So-called “natural” physicodynamics cannot generate nonphysical PI. PI can perform nonphysical “formal work.” PI can then be instantiated into physicality to marshal physical work out of nonphysical formal work. Cybernetic programming is only one of many forms of PI. Ordinary language itself, various communicative symbol systems, logic theory, mathematics, rules of any kind, and all types of controlling and computational algorithms are forms of PI. Neither chance nor necessity has been shown to generate PI. Choice contingency, not chance contingency, prescribes nontrivial function. PI typically is recorded into a linear digital symbol system format. Symbols represent purposeful choices from an alphabet of symbol options. Symbol selection is made at bona fide decision nodes.
ProtoBioCybernetics—the study of the derivation of control and regulation in the first life forms. Cybernetics incorporates Prescriptive Information (PI) into various means of steering, programming, communication, instruction, integration, organization, optimization, computation and regulation to achieve formal function. “Bio” refers to life. “Proto” refers to “first.” Thus, the scientific discipline of ProtoBioCybernetics specifically explores the often-neglected derivation through “natural process” of initial control mechanisms in the very first theoretical protocell.
Protobiont—a hypothesized initial precursor of living organisms, usually thought to have been a protocell with some semblance of a vesicular-like phospholipid or bilayer “membrane.” Contained within this vesicle is believed to have been the minimal unit of protolife or life. Tibor Ganti’s minimal unit of life, the chemoton, includes the vesicular or membrane-like barrier.
ProtoBioSemiotics—the study of meaningful or functional messaging and how it arose within and between the first protobionts.
Protocell—a hypothesized initial “cell” with a vesicular-like phospholipid or bilipid “membrane” in which life is imagined to have spontaneously self-organized.
Protometabolism—the hypothesized first semblance of integration of biochemical pathways and cycles into a holistic, organized, functional metabolic system.
Random Sequence Complexity (RSC)—a linear string of stochastically linked units, the sequencing of which is dynamically inert, statistically unweighted, and is unchosen by agents; a random sequence of independent and equiprobable unit occurrence. RSC is the most complex of the three kinds of sequence complexity, the reason being that a random sequence contains no algorithmically compressible order. Its sequence cannot be enumerated using any representational string shorter than itself. RSC manifests the absence of any order or pattern. RSC represents maximum uncertainty, and therefore contains the maximum number of Shannon bits. Although maximally complex, RSC does nothing functional, emphasizing that complexity is not an explanation for utility or pragmatic worth.
Regulation—the choice-contingent steering, controlling, adjusting and fine-tuning of some formal process, procedure, or reaction sequence. To regulate presupposes freedom from law sufficient to manage events by formal choice-contingent causation and control (CCCC).
RNA analogues—Molecules similar in structure to RNA, but having the phosphate, ribose or nucleobase replaced with some alternative. Alternate nucleobase Molecules similar in structure to RNA, but having the phosphate, ribose or nucleobase replaced with some alternative. Altering nucleobases (e.g. fluorophores) typically result in altered base pairing and stacking properties. Peptide nucleic acid (PNA) is a phosphate-sugar backbone analogue. Other backbone analogues include threose nucleic acid (TNA), glycol nucleic acid (GNA), Morpholino or locked nucleic acid (LNA). Originally, it was hoped that RNA analogues might solve the many problems of prebiotic RNA chemistry that threatened the RNA World hypothesis. However, the Pre-RNA World hypothesis has encountered many roadblocks of its own.
RNA World hypothesis—the belief that initial life consisted primarily of RNA rather than the DNA and protein necessary for current life. RNA can potentially retain nonphysical information in its physical matrix and self-replicate. RNA can act as a crude catalyst compared to proteins. Numerous biochemical hurdles in a prebiotic environment have rendered the RNA World hypothesis highly suspect. The PreRNA, RNA analog, and RNA World models probably remain the most favored models in life origin theory today. Ribonucleoprotein enzymes such as ribosomes are thought to have arisen from molecular evolution prior to DNA-protein life.
Rules—Choice-contingent guidelines intended to guide procedures, competing interests, and ethical behavior. Rules are nonphysical, formal, mental constructions. Rules are not laws. Laws describe and predict deterministic physicodynamic interactions. Loss of formal utility usually accompanies the disobedience of rules unless a pragmatically superior rule system is being explored. Rules can also be arbitrarily agreed-upon conventions that govern language and voluntary behavior. Rules exist to guide choices. Rules can be broken at will, often at the expense of efficiency or efficaciousness in accomplishing some pragmatic goal.
Semantic—meaningful or functional.
Semiotics—the study of symbolization using sign and symbol systems, meaningful message generation, language, programming, and the communication methods employed. The three main branches of semiotics are 1) semantics—the meaning generated by how symbols are arbitrarily assigned to represent objects and ideas, 2) Syntactics—the sequencing and relation of symbols to one another to create higher meaning, and 3) Pragmatics—the usefulness of symbol system applications and their communication.
Sign—a two-dimensional picture or drawing conveying representational meaning to one’s senses. The picture or drawing is self-explanatory because we recognize by sight physical objects that are being depicted from our every-day empirical world. A visual image of real world objects is delivered by the sign. Our consciousness links the two-dimensional picture with our experience of and with that object. A picture of an automobile with two wavy lines emanating from behind its rear tires is a street sign conveying the message of slippery road conditions.
Signal—a transmission of mass/energy from one location to another, as a pulsating emission of light from a distant star. A signal need not have any meaning or function, and should be carefully distinguished from “message.” Messages always contain formal meaning, and can only be instantiated into physicality through choice contingent causation and control (CCCC) from the far side of The Cybernetic Cut. Signals, on the other hand, can be entirely physicodynamic.
Stoichiometry—the branch of chemistry dealing with the relative quantities of reactants and products. Whole numbers usually represent the ratio of reactants to products.
Structure—a recognizable framework of categorization, pattern or order in an entity or relationship between entities. The manner in which the parts of a whole are assembled. Primary structure refers to the sequencing of monomers in a linear polymer. Secondary structure refers to the two-dimensional representation, at least, of alpha helices and beta strands (in proteins) and helices and stem-loops (in nucleic acids) due to base pairing and base stacking. Tertiary structure refers to the three-dimensional globular shape of folded proteins, ribozymes, and chromatin.
Sustained Functional Systems (SFS)—any device, machine, network or system that both 1) continues on in time (is a non-dissipative structure in the sense of Prigogine’s chaos theory) and that 2) generates sustained non trivial functionality. Prescriptive Information (PI) and Organization alone make Sustained Functional Systems (SFS) far from equilibrium possible. Maxwell’s Demon’s choice contingency of when to open and close the trap door so as to accomplish the goal of a sustained energy potential represents the very first true decision-node instantiation into physicality. The Demon’s first choice is the birth of engineering and the artificial intelligence movement. Deciding when to open and close the trap door is the very first logic gate—the very first configurable switch-setting. The Demon’s voluntary (arbitrary) trap-door operation represents the birth of integrated circuits, computational cybernetics, and life’s regulatory mechanisms. No natural mechanism exists that can choose with intent to deliberately design, engineer and maintain a SFS. Yet without SFS’s, life is impossible. SFS’s predate and produced Homo sapiens. They therefore cannot be attributed solely to human mentation and creativity.
Symbol—an arbitrarily-shaped/generated character representing some assigned meaning by definition. The meaning of these “strokes of pen” is just arbitrary assigned by the sender and agreed to by the recipient. Otherwise, the message will not have meaning or function at its destination. A symbol, unlike a sign, conjures no meaning from one’s sight memory of physical objects. The letters of most language alphabets are not signs, but symbols. Strings of such symbol characters spell words leading to lexicons of words. Hierarchies of phrases, clauses, sentences, and paragraphs can be constructed from the lexicon of words according to syntactical rules. Sometimes only one letter symbol, such as “H” or “C” on a faucet handle, conveys meaning. Mathematical symbols such as π, Ω, ξ, ∆, = , and ≠ are symbols, not signs. We cannot ascertain the meaning of these symbols from the symbol itself, except that we sometimes become so familiar with a certain symbol’s assigned meaning that it begins to take on a function similar to a picture or drawing, thereby having a sign-effect from our sight memory (e.g., the symbol “ = ” begins to be recognized visually as the a physical sign of equality). Codons function as symbols in molecular biology, not as direct physicochemical reactants or pictorial signs. Genes are not blueprints (two-dimensional pictures).
Symbol Systems—a means of recordation or communication that employs symbols to represent and encode meaning. Symbol systems allow recordation of deliberate choices and the transmission of linear digital prescriptive information. Formal symbol selection can be instantiated into physicality using physical symbol vehicles (tokens). Material symbol systems (MSS) formally assign representational meaning to physical objects. Even the analog perturbations of verbal semiosis can be symbolized with numerical representations in voice recognition software.
Token—a physical symbol vehicle. A physical object on which a symbol has been inscribed or to which symbolic meaning has been ascribed.
Transcribe—in molecular biology, to synthesize meaningful/functional RNA sequences containing Prescriptive Information (PI) using RNA polymerase enzymes from a DNA template.
Translate—to map one symbol system onto another in an effort to decode the initial system.
Turing machine and tape—a thought experiment imagining a device that can algorithmically process a string of successive symbols on a linear tape according to a table of rules. An infinite memory is afforded by an infinite tape. Each symbol represents not only meaning, but also arbitrary choice contingency rather than chance and/or necessity. The rules are also choice- contingent. The thought experiment can simulate the function of modern computers and their computational limits.
Undecidable—a decision problem that is impossible to always answer with a “Yes” or “No” using a single algorithm. The term is most applicable to computational complexity theory. Alan Turing, for example, proved that the halting problem is undecidable for Turing machines. A verbal statement can also be considered “undecidable” with relation to Gödel's incompleteness theorems when that statement is neither provable nor refutable within a certain deductive axiomatic system.
Universal Probability Bound (UPB)—a quantifiable limit to an extremely low probability resulting from the limitation of probabilistic resources in that context. Statistical prohibitiveness cannot be established by an exceedingly low probability alone. Rejection regions and probability bounds need to be established independent of (preferably prior to) experimentation in any experimental design.
Universal Plausibility Metric—a numerical value measuring the plausibility (not probability) of extremely low probability events in view of the probabilistic resources in each context. The UPM employs the symbol ξ (Xi, pronounced zai in American English, sai in UK English, ksi in modern Greek) to represent the computed UPM according to the following equation:
wheref represents the number of functional objects/events/scenarios that are known to occur out of all possible combinations (lower case omega, ω) (e.g., the number [f] of functional protein family members of varying sequence known to occur out of sequence space [ω]), and LΩA (upper case Omega, Ω) represents the total probabilistic resources for any particular probabilistic context. The “L” superscript context of Ω describes which perspective of analysis, whether quantum (q) or a classical (c), and the “A” subscript context of Ω enumerates which subset of astronomical phase space is being evaluated: “u” for universe, “g” for our galaxy, “s” for our solar system, and “e” for earth. Note that the basic generic UPM (ξ) equation’s form remains constant despite changes in the variables of levels of perspective (L: whether q or c) and astronomic subsets (A: whether u, g, s, or e).
Universal Plausibility Principle—states that definitive operational falsification of any chance hypothesis is provided by the inequality of:
ξ < 1
where ξ is the measured UPM for that context. This definitive operational falsification holds for hypotheses, theories, models, or scenarios at any level of perspective (quantum or classical) and for any astronomical subset (Universe, galaxy, solar system, and earth). The UPP inequality’s falsification is valid whether the hypothesized event is singular or compound, independent or conditional. Both UPM and UPP pre-exist and are independent of any experimental design and data set. No low-probability hypothetical plausibility assertion should survive peer-review without subjection to the UPP inequality standard of formal falsification (ξ < 1)" [ 1-3 ].
Utility—formal usefulness or functionality, usually as decided or evaluated by agents with reference to their desires and goals. A more objective concept of “utility” might be found in the biofunctionality of molecular machines, for example, with reference to the holistic metabolic goals of cells and organisms.
Vesicles—a complex version of the micelle containing one or more phospholipid bilayers that can enclose, transport and digest other substances. Cellular vacuoles, lysosomes, transport and secretory vesicles in living organisms have attracted much attention as models of possible protobionts (protocells) with crude “membranes.” Phospholipids can form bilipid layer walls of artificially prepared liposomes.
1. Abel DL. The Universal Plausibility Metric (UPM) & Principle (UPP). Theor Biol Med Model. 2009;6(1):27 Open access at https://tbiomed.biomedcentral.com/articles/10.1186/1742-4682-1186-1127 [Last accessed: August, 2016] Also available at lifeorigin.academia.edu/DrDavidLAbel.
2. Abel DL. The Universal Plausibility Metric (UPM) & Principle (UPP). Theor Biol Med Model. 2009;6(1):27 Open access at https://tbiomed.biomedcentral.com/articles/10.1186/1742-4682-1186-1127 [Last accessed: August, 2016] Also available at lifeorigin.academia.edu/DrDavidLAbel.
3.The Universal Plausibility Metric and Principle. In: Abel DL, ed. The First Gene: The Birth of Programming, Messaging and Formal Control. New York, N.Y.: LongView Press--Academic; 2011:305-324 Also available from http://lifeorigin.academia.edu/DrDavidLAbel