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ch10- The Cascade Model Of Morphological Flows - Unifying Material, Biotic and Social Morphogenesis- Flow Oriented Thinking, using it as an analytical tool to address scientific, social and personal dilemmas

We saw how energy flowed out of the progenitor of our space-time bubble (Zero Point) and coalesced in a morphological flow continuum  that gave rise to material morphologies, biotic morphologies and our social morphologies in a continuum of hierarchical complexity. In the process we covered our own morphological evolution, our bodies, our minds, our societies and cultures. We discovered the we have an expanding aperture of perception into the Inherent Reality that we are a part of and in its perception we create our own perceived reality that may vary substantially from person to person and culture to culture. We discovered that Inherent Reality is by definition abstract, from our perspective it is made up of dynamic flows that coalesce to bear morphologies, hence morphological flows.
Fully acknowledging our limited aperture of perception of Inherent Reality, are there any common patterns in the flow continuum? How about these observations:

1- Polar, opposing forces and attractor sets- we saw electric positive and negative charges, magnetic poles, strong forces binding nuclei, weak forces breaking them apart, we saw gravity in action, and recently apparently we have discovered something with anti-gravity property pushing galaxies apart. Right from the get go we saw these forces acting as attractor sets for matter, pulling and pushing and thus inducing flows. We saw atoms and molecules acting similarly, spreading their electromagnetic fields in their surrounding space, pushing and pulling each other in a geometrically specific manner. 
In the biotic domain we saw new attractor sets form. Predator prey relationships push and pull, inducing flows. Sexual drives push and pull, induce flows. And towards the end when we examined the evolution of the brain we discovered that there is this evolutionary layering of control networks pushing and pulling on individuals (yes humans included), inducing flows. In fact when we covered our development it turned out that our own morphological evolution is induced by our attractor sets that emanate from and effect our brain circuitry. We even saw push and pull of (and on) ideas where they are absorbed (or rejected) by societies, thereby inducing cultural flows.

2- Chaotic flow dynamics, creation and destruction in a hierarchy of complexity- these attractor sets induce chaotic flows. Therein entities mix and match in every which way. They interact, sometimes constructively, creating new entities thereby increasing the order of complexity, and sometimes destructively thereby decreasing the order of complexity. The stable entities perpetuate and the non-stable ones breakdown to their constituent morphologies. And, everything seems to have a lifetime.

3- Full spectral hierarchy- if you consider the hierarchy of complexity as a spectrum, say with photons at the bottom of the spectrum and, for the sake of argument, our global social structures at the high end, the spectrum appears to be full. Some of the entities bind to create complexity, some stay put on their spectral spot, some decay down the spectral slide.

As academically interesting as these observations may be (assuming you agree with them), they come in handy analytically, as we will see later when we apply the morphological flow discipline to our own dilemmas.

So the flows act in a continuum giving rise to material, biotic and our social morphologies. Is there a common process that applies across the board?  I see a common pattern that is deceptively simple.

Anywhere along the above continuum, there are one or more entities that go through some sort of reaction giving rise to one or more entities.This would be a single step reaction. The resultant entities could be more complex, less complex, or have the same level of complexity. Now we know there is a floor to complexity, i.e. the least complex entity which is a photon. If you add in more steps you'll end up with cascade processs. So what are the possibilities of these cascade processes? They could go down the complexity chain. They could not change the complexity picture, or they could give rise to a hierarchy of complexity. So, in time, as more and more steps are added to the cascade chain, with the complexity floor being fixed, the ceiling of complexity hierarchy gets pushed upwards.  

We'll call this the Cascade Model of Morphological Flows. Lets look at it in more detail, starting with a single cascade step where initial entities X (set) go through a construction reaction giving rise to resultant entities Y (set):

A cascade process could involve a series of steps and if modeled deterministically it could look something like:
Entity Set==(constructor)==>Entity Set==(constructor)==>Entity Set==(constructor)==>Entity Set [so on]

We mapped the cascades in the Chapter Key section of each chapter [Chapter Key: Morphological Flows, entities going through functional constructs thereby creating more complex entities with more complex functionalities], so lets assemble them:

Ch1- Creation of Elementary particles and the Cosmos
Zero Point == construct? ==> Photons == construct? ==> particles (electron-proton-neutron) == construct (Electro-Magnetism) ==> hydrogen, helium clouds == construct (Gravitation) ==> galaxies, stars and planets

Ch2- Creation of Atoms

Stellar Nuclei == nuclear fusion (strong nuclear force) ==> more complex nuclei up to iron == super/hyper nova compression ==> yet more complex nuclei == atomic orbital constructors (Electro-Magnetism) ==> atoms in the periodic table of elements

Ch3- Creation of Molecules

atoms == molecular orbital constructors (valent, covalent bonds - Electro-Magnetism) ==> molecules  == molecular orbital constructors (valent, covalent bonds - Electro-Magnetism) ==> more complex molecules

Ch4- Creation Proto-Biota

base organic molecules  == chemical reactive constructors (Electro-Magnetism) ==> intermediate organic molecules  == chemical reactive constructors (Electro-Magnetism) ==> biotic organics

biotic organics == constructor? ==> biotic aggregates manifesting structural functions

biotic organics == constructor? ==> biotic aggregates manifesting metabolic functions

biotic organics == constructor? ==> biotic aggregates manifesting replicative functions

biotic organics == constructor? ==> biotic aggregates manifesting sensory/motor functions

biotic organics == constructor? ==> biotic aggregates manifesting signaling (communication) functions

structural aggregates + replicative aggregates == accretion constructor? ==> alpha proto-biota (proto viruses)

alpha proto-biota+ motor/sensory aggregates +  signaling (communication) aggregates + metabolic aggregates+ other functional aggregates == accretion/mutation constructor? ==> beta proto-biota (prototype extremophile archaea cells)

beta proto-biota+ other cellular functional aggregates == accretion/mutation constructor? ==> common cells

Ch5- Creation of Biota - Bio-Molecular (Genetic) mechanism of evolutionary creation

DNA-(t+m)RNA-Protein functional aggregates == accretion mechanisms (Electro-Magnetism) ==> coalesced DNA-(t+m)RNA-Protein functional groups

DNA-(t+m)RNA-Protein functional aggregates == mutation mechanisms (various) ==> mutated DNA-(t+m)RNA-Protein functional groups

DNA-(t+m)RNA-Protein functional groups + supporting material in the environment == constructor (accretion?) ==> functioning cell

functioning cell == replication and differentiation ==> functioning cell clusters and groups (organs)

functioning cell clusters and groups (organs) == cell-cell signaling, communication and transport ==> functioning organism

functioning organisms == natural selection + genetic accretion/mutation ==> functional speciation 

Ch6- Evolutionary Creation of the Tree of Life - constructors are mutation and natural selection - follow the blue blocks till it reaches us

 Ch7- Evolution of Central Nervous System and the Brian

Cell Stimulus-Response == cell differentiation ==> sensory and motor neurons

sensory neurons +motor neurons +controller neurons == life actions ==> instinctive behavior

Sensory neurons + neural memory circuits +affirming neurons == training ==> learning

Sensory neurons + memory circuits + integrator/arbitrators + controllers + motor cells == life actions ==> heuristic behavior

Inherent Reality [abstract entities and phenomenon] + heuristic networks == imprinting ==> Perceived Reality [abstractions and an internal notion of what is physical]

Up until this point everything we covered has been within our external domain of attention (external to us), i.e. we have attempted model the morphological flows as we see it within the domain of Inherent Reality. From next chapter on, we are modeling the domain of our internal attention, i.e. model our evolutionary morphologies. It turns out that the cascade model renders our personal, social and cultural evolution as well.

Ch8- Evolution of Knowledge

fore,mid, hind brain == evolution ==> triune brain

Inherent Reality: Abstract == perception, affirmation, memorizing ==> abstraction (knowledge node)

atomic knowledge nodes == classification ==> super, subclass knowledge trees (knowledge genres)

knowledge trees == personal and social corroboration/agreement ==> beliefs, truths and facts

knowledge trees == memetic evolution ==> societal and cultural absorption, advancement and expansion

Ch9- Our Social Evolution

societal knowledge tree: religion + governance == social evolution ==> tribal cultures, societies and governments

societal knowledge tree: science == scientific evolution ==> technological societies and cultures

societal knowledge tree: economics == economic evolution ==> national wealth, trans-national economic alliances

societal knowledge tree: democratic governance == evolution of free societies ==> global coalition of free societies

societal knowledge tree: military arts and sciences == military evolution ==> empires, international military alliances

The above cascade processes map the morphological flows, from zero point, through our current social evolutionary processes. And we discovered that the model applies to the evolution of logic as well. All mathematical constructs are cascade constructs. We can build mathematical (functional) constructs with it. A general cascade step can be written as: X=O(Y), where Y is the initial set, X the final set and O the operator. In one dimension that gives you basic functions x=f(y). Or in multi-dimensions it'll produce a vector equation, or you may construct differential, integral, or balance equations, depending on the construct of the operator (shown below in order):

Or, models (mathematical or otherwise) may not be functional, they could be algorithmic (e.g. computer program), or structural constructs. You can have ladder constructs (e.g. seen in chemical reactions):

You can model tree structures (e.g. seen in everything from tree of life to organizational charts), or create graph constructs (e.g. seen in workflow models, flowcharts, feedback controls etc.), as depicted below:

You can also have any combination thereof.

Of these models, fractal models can have spectacular visual results. Here is a fractal model called an L System (source: http://www.i-a-s.de/IAS/botanik/virtuallaboratory/TableOfContents.html):

And if you iterate through you'll get:

And when fully rendered and effects added (drooping induced by gravity, shading etc.) you'll end up with realistic pictures. The same model and it's variation can form leaves, flowers, roots (I haven't seen any fruit yet, but I'm sure they can be rendered too). You could put in internal and external control mechanisms. External control mechanisms can be availability of sunlight, external plant pathogens (competition from surrounding plants), or even internal plant pathogens (e.g. one branch suppressing other branch formations in its surrounding area). The rendered pictures can be quite amazing:

In this example we have built an abstract construction process to simulate the real one. Why does it work so well? Because we clued in to the underlying process which is an abstract cascade construct. We have constructed a seemingly pretty accurate model of the Inherent Relality of plant formation.

In the above discussions we depicted the cascade process as a deterministic one, it isn't. Cascade processes are invariably probabilistic. Such a model will look like (the dotted lines represent the possible but unrealized processes, and the solid lines represent the actualized process):

While deterministic cascades model the dynamics that define the forward flow in time, the probabilistic cascades model the possible evolutionary paths that processes might take under various conditions. One can argue that any flow, before it is actualized, is always inherently probabilistic. It is only after it is established that its form takes a deterministic shape. So entities go through cascade constructs to create more complex entities and if you can create a movie of this construction process you'll see a flow of creation, a morphological flow if you will!

There are all manners of flows. Some influence each other indirectly, some influence one another directly, and some flows spawn from other flows.
As an example of indirect but significant influence, consider our dependence on the ozone layer. The ozone layer of the atmosphere is created in its own morphological cascades. The layer interferes with the photon flow that pours out of the sun and hits the earth; namely it filters out the ultraviolet rays. Those rays are harmful to us, specifically the cascade flows that make up our bodies. We discovered the criticality of our dependence once it became clear that some of our products were destroying the ozone layer and directly endangering us.
As an example of flows that directly influence one another, I'll give you a classic example from bio-mathematics (without the math): predator-prey population dynamics of mice and (wild) cats. Each species governs its own flow from one generation to the next, depending upon how many breeding pairs there are in a given generation. Bigger populations result in more babies. But they directly influence one another as well; more cats eat more mice, dropping the number of mice (less baby mice), resulting in less food for the cats, resulting in less baby cats. The converse is true as well. When there are few mice and few cats, the mice can have a lot of babies, meaning more food for the cats, resulting in more baby cats. Models show and observations verify that predator-prey populations go through these cycles, sometimes very dramatically. This is a classic example of dynamic, chaotic flow. The system, consisting of predator and prey populations is said to be stable if the population cycles go on perpetually. If the populations get too low, and say a calamity happens at that point of the cycle, say water flow slows (a third flow), resulting in very little vegetation (a fourth flow), then the mice could go extinct, then the cats would become extinct. There, the system is said to have reached an unstable point, resulting in the catastrophic extinction of the species.
One example of flows spawning other flows is in biological speciation where due to mutations and/or natural selection one species spawns from a parent species. Take the case of selective breeding in agriculture. Our domestic wheat species are very different from their wild parents due to 10,000 years of selective breeding. During each planting cycle the larger, higher yield varieties were selected and others cast off. After multiple generation the planted wheat became larger and larger. By now the domestic wheat looks so different from the wild varieties that untrained eyes wouldn't necessarily see any relation between the two. And finally, to complete the act of manmade speciation, we went in deep and genetically re-engineered the wheat.

So, many, many cascade flows exist and they insert all manners of influence upon one another, from very little, to direct spawning and everything in between. In that sense the flow picture is fundamentally chaotic. What emerges out of the chaotic environment is what we see. So the order that I presented the cascade flows, deterministic cascades, probabilistic cascades and chaotic cascades, is actually backwards. There are all manners of cascades, interacting chaotically. When we focus on one we can see how probabilistic it is, and once one dominant flow emerges we can model it procedurally and it looks deterministic.

The morphological flows and the resultant processes of evolutionary creation require all three types. Positive cascades result in the creation of higher order entities (higher complexity). Negative cascades result in the destruction of entities into their constituent parts, providing fodder for new constructions. The three work in tandem, constructing various possible evolutionary pathways and completing the chaotic picture. The unstable constructs die off (deconstruct into their constituents) and the stable ones perpetuate.
Now if you look at the construct of the final entity X in the above picture, all of its constituent entities in its construction tree have their own flow lines (all the way down to particles, the spectrum is full). So any entity is then the coalescence of the flow lines of its constituents. This morphological deconstruction looks deterministic when we apply it backwards in time. The morphological flow construction of any given entity (forward in time) follows the rules of chaotic dynamics, i.e. the stable entity X is the emergent property of the dynamical interactions of its constituents.

As stated previously, technically the morphological flow tree make up of an entity within Inherent Reality is a GRAPH, i.e. any node can connect up to any other node so long as the constructor is in effect.

In the morphological flow model everything is dynamic and abstract. When we mentally map any set of entities within Inherent Reality we internalize what we have perceived as knowledge trees (graphs):

Ideas go through the same cascade construction process as do molecules, cells, bodies. The construction of knowledge trees follow the cascade model. That is why mathematical models, and mental models in general work, if they are accurate abstractions representing the abstract entities that they are to render to begin with. Even in pure mathematical form (not representing anything in the energy domain) logical constructs (entities) form the building blocks of further logical constructs (entities) in cascade processes that create hierarchies of logical complexity (evolution of pure mathematics).

As we have seen personal knowledge trees coalesce to render our perceived reality. These personal knowledge trees, over generations, then amalgamate to render societal knowledge trees, that is the biological manifestation of our culture.

Cascade flow processes naturally display self-similarity as shown. For example let's look at the tree of life where we branch off:

But the actual evolutionary steps happen as the result of mutations that occur at specific nodes within the lineage tree of the root species. So, you can lay out the lineage tree within the tree of life and look at the effected individuals: (M=mail, W=femail):

But, then again, the actual mutation effects specific functions of specific organs of the effected body. So you can look at yet another layer of detail, i.e. morphogenesis of the given mutant body to define the actual mutations of body morphology and function. So you lay out the developmental cascade of the body and look at the specific constituents:

You can yet take it a level further and look at the actual mechanisms of the specific genetic mutation within the effected organs. But why don't I stop here. In the above example you have body plan tree within the lineage tree within the tree of life. As we delved down in the evolutionary problem, we saw these cascading structures that are hierarchically imbedded and look alike (tree structures).

One last look at the chaotic nature of the cascade flow model and the stable and unstable outcomes that they produce. We are, for the most part, linear, procedural thinkers. It's just harder for us to think probabilistically, harder even to think about dynamical, chaotic systems and stable outcomes that emerge out of those chaotic collectives. So lets go around and give some examples, starting from the micro and work our way up to the macro scale.

Starting with elementary particles, we have a whole host of them that can mix and match in a variety of ways. Out of those permutations the proton-neuron-electron combination present the stable combinations that go on to form the atoms that we see today. Same thing with molecules, in the Miller experiment, which produces organic materials from simple gases, a flask is filled with gases and subjected to electrical sparks. Chemical reactions occur in a chaotic manner. Molecules form and then disintegrate and reform again, creating a vast array of arrangements. Of those, the stable organic materials remain. Moreover, lipids, nucleic acids, proteins and sugars can be mixed in a variety of ways, but only certain configurations can lead to stable cells. In biotic morphogenesis, genetic mutations can occur in a variety of ways leading to all manners of design changes to the body (both in terms of appearance and functionality). So the designs radiate out in all manners of directions but only the stable, successful ones go on to survive.

Finally we see the same thing with the evolution of knowledge. Consider democracy, how do bills get passed in Congress? There are many ideas that get discussed and debated, some emerge and coalesce. Eventually after much wrangling, arm-twisting and horse trading, some of the ideas become the laws and rules that we live by. But even then, how many times have we seen bad ideas? Ideas evolve in all manners of directions too. Only the ones that get applied successfully (are stable) go on to survive.

We now have enough information to frame (morphological) Flow Oriented Thinking:
1- Within our domain of external attention, i.e. our focus on entities and phenomenon within the domain of Inherent Reality- If we look at any entity or phenomenon and ask how it emerged, we can deconstruct its evolutionary path and come up with a deterministic model (assuming that we actually can model its evolutionary path). The reason, of course, is that we are looking backwards in time. There we see the outcome of the flow process as determined after the fact. However, if we look at an entity or phenomenon and ask how it is going to proceed forward in time, then we are forced to face the chaotic/probabilistic nature of morphological flows, i.e all the possible permutations of reactions that may happen. And as we have seen throughout our discussions, the forward paths may be fairly solidly fixed by physical laws, or they can be probabilistic with several possible outcomes, or we may have to face a chaotic dynamic that may or may not have any predictive possibilities (stable outcomes). 
This would constitute the analytical tool for problem solving, creativity and invention, planning, building and implementation.

2- Within our domain of internal attention, i.e. our focus on personal and societal dilemmas- Our personal knowledge trees render what we personally know and how we functionally behave. Our societal knowledge trees render our culture and our social behavior. When attempting to effect personal and social behavior we are attempting to modify personal and societal knowledge trees. From a morphological flow perspective these knowledge trees are readily definable. Further these knowledge trees exist within the triune brain model where there is a hierarchy of control: reptile, emotional and cerebral brains, in that specific order. The reptile brain circuits trump the emotional and cerebral circuits, and the emotional brain circuits trump the cerebral brain circuits, as a rule. Reptile brain circuits and emotional brain circuits (the mainly subconscious domain), and cerebral brain circuits (the mainly conscious domain of knowledge trees), together define our personal and cultural domains of behavior. As we will see in the sustainable growth section of this exercise, using this line of flow oriented thinking, we can analyze and effect personal and social dilemmas with precision.

The Dynamical Systems and Technology Project at Boston University - good introductory site for college and advanced high school students with plenty of interactive applets and introductory technical papers on dynamical systems, chaos and fractals.