=Paper=
{{Paper
|id=Vol-1638/Paper75
|storemode=property
|title=On reverse engineering of human body system
|pdfUrl=https://ceur-ws.org/Vol-1638/Paper75.pdf
|volume=Vol-1638
|authors=Jochen Mau
}}
==On reverse engineering of human body system ==
https://ceur-ws.org/Vol-1638/Paper75.pdf
Data Science
ON REVERSE ENGINEERING OF HUMAN BODY
SYSTEM
Jochen Mau
Heinrich Heine University Düsseldorf, Germany
Abstract. From a holistic perspective, functional body can be decomposed into
functional core body of vital functions and functionally extended body of phys-
ical productivity activity; operational body stands for cognitive and volitive
functionality that expresses as a person's interactions with environment and so-
cial settings and become perceived as behavior. A factory interpretation sug-
gests to see human body as a bioautomaton, operationally utonomous but func-
tionally non-autarkic. Analogies with complex organizations suggest distinction
of functional levels, which are concatenated top-down in a "knitting" way, with
an interpretation of emergent properties as next-lower level interactions.
Keywords: System biology, molecular biology, mathematical modeling, human
bogy system
Citation: Mau J. On Reverse Engineering of Human Body System. CEUR
Workshop Proceedings, 2016; 1638: 622-635. DOI: 10.18287/1613-0073-2016-
1638-622-635
1 Introduction
1.1 Molecular Biology Perspective
Relevance of a holistic top-down approach in exploration of highly complex struc-
tures is quickly understood: an edifice will be composed from raw materials like con-
crete, steel, mortar, plastic tubes, metal cables, wood, glass, etc., but to understand its
functionality or even only its statics, one has to start with the whole and then - pictori-
ally speaking - to dig deeper. This also holds for the human whole-body system
(HWBS). Citing [1], a biological system is an "interactive and dynamic web in which
the properties of a single molecule are contingent on its relationship to other mole-
cules and the activities of those other molecules within the network"; it is appropriate
to understand "web" as an interwoven structure and network as total context. This
total or overall context may also be referred to as system context, more specifically as
an internal context contrasting any concomitant external context of a system's life
surroundings. How does activity of the whole may then arise from activity of mole-
cules?
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By "the Central Dogma tenet" [8] - because genes express DNA code (information)
into an intermediate messenger RNA from which it is translated into proteins, and
because proteins are "key building blocks of cells" and "play a critical role in cellular
regulation" - DNA encoded information will not only influence proteins but also tis-
sue function and next give insight into causes of disease and hint to ways of their
avoidance if not elimination. The logical aw is denounced as lack of education in
engineering as "by analogy, if one were provided with the raw material list for an
aircraft (sheet metal, nuts, bolts, rivets, etc.), it would be an impossible leap to con-
clude anything about the principles of aerodynamics" [8] the argument being tanta-
mount to a reference of properties of the plane in any flight condition. As properties
of aircrafts, or water vessels for that purpose, are not for the many one may add
acoustics in a concert hall as a more commonly understood example.
Though reservations based on practical limitations, "the physiologically relevant func-
tions of the majority of proteins encoded in most genomes are either poorly under-
stood or not understood at all" [27] may be overcome with even more computational
power – the prevailing trend, - there also seem to be some fundamental biological
reasons: "beyond genetic determinants, diseases are characterized by a perturbed
physiology, and methods providing a wider and deeper window into physiological
states will be instrumental to acquire an integrated view of human disease" [18]. And
indeed, "all facets of physiology, including contributions from the microbiome and
environment (must be integrated), thus adopting an even wider scope than the ge-
nome-wide paradigm" [18].
However, such demands may reach out too far today.
To understand the function logic of a major airport, for example, one would not need
complete structuralphysical characteristics of each stone neither to record its vibration
behavior and heat ow under operating conditions in real-time. Similarly, the function
logic of a big organization's staff will not open up from brain wave recordings or con-
current physiological data of every person – it may rather be simpler principles of
individual social behavior that can explain behavior of the whole fabric.
The importance of molecular-biological research – and its extraordinary funding in
the last decades – must not be disdained; nevertheless, it should be judged in relation
to what is achievable: The predictive value of genetic information with respect to a
person's physical course of life should be regarded with utmost skepticism as long as
the body's life history cannot be read from genes in retrospect.
Already 45 years ago, a comparable upsurge of hopes had been connected with tech-
nology of the living – methods of cybernetics [5] that lost its vigor in "digging deeper"
because cellular feed-back control was not sufficiently well understood. This deficit is
now at the point of dwindling.
1.2 Systems Biology
In human body, control loops of feed-back have been described at cellular level [4],
exist by thousands at physiological level [11], and are present as well in clinical con-
text [28] and in human behavior [14]; some authors [7] then extend the idea to inter-
woven controls across all levels even from DNA to social organization, and see hu-
man body as a complex adaptive system in its life sphere context [19]. Understanding
controls from genes via proteins, cells, and organs [24], to organ systems and whole
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body, and backwards, is far ahead, and most current research is said to be absorbed in
addressing within-level interactions [10].
2 Kybernetik
2.1 Functional Physiology Perspective
Taking a functional perspective means to disregard material realization for a while
and to study the rules by which components of a system interact, instead: This will
involve exploration of their hierarchies, competences and roles in fulfillment of whole
system's mission. A functional perspective of human body system then puts focus on
structural aspects of function and less on anatomical, physiological or biochemical
ways of how functions are carried out.
When the human body is seen as a production system, its similarity with a factory
opens up. Exactly this interpretation has actually been laid out systematically for
whole body and some of its parts in a five-volume collection of lay-press illustrations
between 1912 to 1930 [13] in Germany and then in USA, prepared by German physi-
cian Fritz Kahn [12], see [6] for a comprehensive presentation of Kahn's works as
pieces of arts. Control and regulation loops were represented as engineered systems in
pictorials instead of block diagrams, without any mathematical formulation.
This perspective then found its way into the seminal concept of cybernetics as infor-
mation and control in machine and in animal written by Norbert Wiener [29], [30]
who united control theory and information theory in the late 1940's.
The ancient Greek word κυβeρνητης means 'helmsman' and appears in Latin as 'gu-
bernator', which is still visible in 'governor'. Since the complexity met in human life
context could not yet be addressed computationally, enthusiastic exploration of the
control aspect faded away about 50 years ago, such that only the information aspect
survived; to now avoid the modern digital interpretation of cybernetics, I suggest the
term' (theory of) automation' in English, instead; to mark the distinction I prefer ky-
bernetik.
2.2 Terminology
The purpose of this subsection is to introduce the reader to the way of thinking and
familiarize with the concepts used below without explanations; by intent, the formula-
tions are general.
2.2.1 Systems
1. A system is a class of elements that are mutually interconnected by relations; their
interconnectedness distinguishes elements of the class from other elements out-
side.[25]
2. The set of all relations is called the system's structure.[25]
3. A sub-system is a sub-class of elements of the system that are mutually intercon-
nected by a subset of relations which distinguishes elements of the sub-class from
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other elements within the system; the set of relations between sub-class elements is
called a sub-structure.
4. A sub-system is called a functional sub-system if the set of relations of all its ele-
ments with all other elements of the system can be represented as the set of rela-
tions of all other elements of the system with the sub-system's sub-structure.
5. A functional sub-system is called a functional unit if its sub-structure does not
overlap with other functional sub-systems' sub-structures.
Now, look at the system as a whole, again.
6. An effectuation system1 is a system of mutually interacting elements; interaction
means transfers of energy (mass, information) and these transfers may be direct or
indirect.[25]
7. The set relations among elements of an effectuation system is called its set of cou-
plings.
8. The formal configuration of an effectuation system's set of couplings is called
structure of couplings or shaltgefüge for terminological clarity.[25]
The central tenet of kybernetik is that the structure of couplings is independent of its
physical realization [25], its wiring. It makes the
Axiom 1 (Sachsse)
The role of kybernetik is the representation of an effectuation system's structure of
couplings independent of their physical realization.
Corollary 1 (The Kybernetic Paradigm)
Effectuation systems of equivalent functional structures will have the same
shaltgefüge.
2.2.2 Functional Activity
Functional activity denotes transfers of energy (matter, information) between compo-
nents of a system; it is then an internal or within-system activity.
1. A functional process is a set of task-oriented transfers of energy (matter, infor-
mation) between functional components.
In systems context, the fundamental concepts are steering2, control3, and feed-back
control 4 each based on information as common concept, cf. [19] for more detail.
Some definitions are useful:
2. Automation is a superordinate term which combines control and feed-back control.
3. Feed-back control consists in maintenance of a dynamic equilibrium that guaran-
tees functional capability and autonomous compensation of random or in-built var-
iations and minor random disturbances by external forces.
4. Control of a functional process consists of activating and influencing the process in
order to attain a set target, as well as deactivating it.
1
in German: Wirkungsgefüge
2
in German: Lenkung
3
in German: Steuerung
4
in German: Regelung
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5. Functional steering is integrated control and monitoring of functional units (as-
sembly groups, subsections) with distributed tasks, each of which controls its as-
signed technical processes and the set points of pertinent feed-back loops which
serve to maintain the dynamic equilibria that are necessary for good operating
conditions; in engineering, it is typically the task of human operator.
2.2.3 Operational Activity
Operational activity is an interactive partaking in system's outside world; it is a be-
tween-systems activity.
1. An operational process is any goal-oriented partaking in outside world; the con-
cept applies to effectuation systems.
2. An operational system is an effectuation system5 combined from functional units
required for realization of operational processes.
3. Systems steering is pursuit of an operational goal in due consideration of the sys-
tem's current or expected operational capacity, and adaptation to varying demands
of partaking in outside world; this is a typical commander's role.
(a) An operational capacity is limited by extent of operational self-sufficiency; this
concerns primarily self-sufficient energy (matter, information) exchange with
outside world to sustain functional activity, and then any supplemental amount
required in operational activity.
(b) On the other hand, demands of partaking in outside world concern a manifold
of tasks in interacting with surroundings, communication, processing of infor-
mation, decision-making for the purpose of effective and efficient achievement
of objectives; it includes consideration of operational rules, state of the art, and
other ambient conditions [19].
4. An operational system with an in-built functional unit for operational steering is
called operationally autonomous, otherwise operationally non-autonomous.
Principle 1
An operationally autonomous or self-steering operational system is an automaton.
2.2.4 Autarky
This concept refers to self-su_ciency with regard to resources; separate resources will
be needed that a system needs for functional and for operational activities.
1. Effectuation systems without interface modules for exchange of matter (energy, in-
formation) with system's outside world are closed systems, otherwise open systems.
2. Closed systems operate autarkically, open systems do not and their operational ca-
pacity then depends on ambient conditions.
5
in German: Wirkungsgefüge
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Fig. 1. Order of Effectuation Dynamics of Controls
2.2.5 Stochasticity
Depending on their degree of complexity, systems exhibit stochasticity in their re-
sponse to unexpected endogenous or exogenous impact - despite complete knowledge
of structures and command of all controls and feed-back controls:
1. intrinsic stochasticity denotes internal, or endogenously arising random uctuations
of dynamic equilibrium of internal energy transfers,and
2. extrinsic stochasticity denotes external, or exogenously arising random variations
in matter (energy, information) exchanges with outside world.
Energy transfer dynamics are generally prone to random variation while the formal
structure of their controls (couplings) will not.
Principle 2
Schaltgefüge is not affected by stochasticity.
2.3 Examples
Here are some examples of operational systems with autonomous steering; the discus-
sion applies to systems in designated service.
2.3.1 Space Ship
Self-sufficiency is the core property for space missions; energy, communications with
outside world, productive functionality as required by mission objectives, in-system
security and safety, and a command stand are among the building blocks; the system
is closed, but operationally autonomous due to its very limited operational capacity
imposed by laws of physics, and tight ground control.
2.3.2 Nuclear Submarine
Such vessels are built to cruise at deep water for months, if not years, unnoticed; they
are functionally self-sufficient to largest extent, and their commanders are well-
trained to operate autarkically as supervision by superior authorities may be impossi-
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ble. As warship it is subject to high extrinsic stochasticity, while intrinsic stochasticity
can be assumed to be less due to small, highly selected and - because of facing un-
derwater loss of ife - very compliant crew, and straigtforward arsenal.
2.3.3 Aircraft Carrier
Nuclear carriers may cruise for years but their productivity tools, fighter planes, will
need fuel from outside, depend on ambient air for combustion, etc. while vessel, the
"vital core" may be shut from ambient resources totally when protection against nu-
clear, chemical or biological contamination is needed. The commander-at-sea as
"master next God" is autarkic in functional activities, and can be as well in operation-
al activities, if needed. Intrinsic stochasticity is much higher because of thousands of
crew and wider range of hazardeous weaponry and equipment; extrinsic stochasticity
corresponds primarily to vulnerability under attack but also from the elements.
2.3.4 Cruise Liner
These vessels equally have a commander-at-sea who enjoys comparable competences,
while the vessel is an open system in some respects, and a closed system in other
respects: fuel, water, food, residuals and waste are carried for self-sufficiency while
fresh air and combustion residuals of man and machine are exchanged with surround-
ing environment. Functional self-sufficiency by large and operationally autonomous
only when needed, otherwise in pursuit of a booked journey. Because of thousand(s)
of passengers, not crew, relatively high intrinsic stochasticity must be supposed, while
extrinsic stochasticity may mainly be ascribed to the elements.
2.3.5 Steel Works, Chemical Plants etc
As in all preceding examples, huge industry plants appear as a "world of their own",
in particular when their size is perceived as unmeasurable and their structures as un-
scrutable. As industry production plants, they are open systems which "import" raw or
semifinished products and export finished ones. They will typically depend on per-
manent in-ow of energy and out-ow for disposal of residuals, actually also of their
work force. Management will enjoy functional autarky with respect to in-system ac-
tivities, and more or less also in operational activities, subject to company hierarchies.
With their characteristics – circumscribed site, dedicated (and clearly identifiable)
structures for energy, internal transportation services, on-site "homeland"-type securi-
ty, communications with off-site "world", manufacturing facilities and production
lines – they can make not plausible, but an intuitionally understood model of formal
structures of functional control in human body.
2.3.6 Human Body
Human body is an open system vitally depending on food and permanent supply with
oxygen for combustion from environment, and correspondingly disposing residuals
into its habitat. In this way it is like a machine; its "tools" – feet, legs, arms, hands –
can precisely master complicated physical tasks due to sophisticated movement con-
trol and fine-motor skills combined with a complex sensory sub-system and well-
coordinating brain motor functions. Mastering the more demanding cognitive tasks is
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less widely available as it requires longer training in childhood and adolescence. Hu-
man body is functionally dependent on ambient conditions though it can care for self,
and equipped for operational autonomy, cautiously speaking.
Principle 3
Human body system is hence a non-autarkic bioautomaton.
3 Physio-functional Model
3.1 Function Levels
Viewing human body as a system for production - in solving either physical or cogni-
tive tasks - is the perspective of ergonomics [21]. From a functional viewpoint, one
can decompose the body system into three function groups with dedicated tasks [19]:
vital functions, productivity functions, and operational functions. From a physiologi-
cal viewpoint, each involves functional activity in body system; from a functional
systems viewpoint their respective tasks are not overlapping: vital functions of body
system keep the human body's 1014 cells alive, productivity functions engage limbs or
sexual organs for any physical or reproductive activity6, and the operational functions
are bundled in the body's capability in receiving and processing information from
outside world and enacting made decision in order to return "a message" of any form.
In any complex system there is typically a hierarchy of function levels each composed
of specific function components; for example, consider structural built-up of a large
edifice (level 0) with several floors (level 1) each with multiple corridors, that lead to
rooms (level 2) used for many purposes; rooms are separated by walls (level 3) set up
with bricks (level 4) that had been made from sand (level 5). Compare this with whole
human body (level 0), decomposed into aforementioned three function groups and
cellular material [19] (level 1), and their functions and operational aggregates (level
2) composed of organs (level 3) that consist of (different kinds of) tissue (level 4)
formed from cells (level 5) that compose a fourth function group, body's cellular ma-
terial7. Each function level will consist of function components of diverse nature, e.g.
rooms for different purposes on the same floor, which motivates
Definition 1 [20] Function aggregates are composed of function units that were con-
ceived to work together and are coordinated to form a dedicated subsystem for a
distinct functional task within the whole system.
3.2 Function Aggregates
For human body vital functions group and physical productivity group, function ag-
gregates are easily identified from a generic factory model analogue:
M: management and control of functional activity,
6
Of course, any operational process - cf. 2.2.3.(1) - will involve more parts of the body, but the
point here is that these "tools" are strictly necessary for productive activity, and they may even
be activated by functional body's autonomous nervous system as reflexes, i.e. without opera-
tional control.
7
The cellular system represents living nature's material option [19].
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E: energy,
H: 'homeland'-type security, safety, integrity of functional processes,
T: transportation logistics ('nutrients' supply and residuals removal),
K: communication with outside world, a 'signal corps' role,
P: physical productivity,
in site context Z provided by human body cellular system Z and other structures.
(Note, that a comprehensive representation of human body function aggregates will
need some supplements that do not fit in the generic factory context.)
For example, vital functions group, V say, consists of function aggregates M, E, T, H
in context of Z, symbolically V = {M, E, T, H|Z} 8 . On the other hand, physical
productivity functions group, P say, will involve function aggregate P in context of Z,
M, E, T, H, symbolically P = {P | V, Z}. The operational functions group, O say, will
involve function aggregate K in context of Z, V and also – because of limitations of
operational options – P, symbolically O = {K | Z, V, P}; note however, that operation-
al functions without physical productivity functions, i.e. {V, O | Z}, are also possible9.
Next, describe some function aggregates, cf. [11] for physiological details, and see
their function units, in brief.
3.2.1 Function Aggregate T (Logistics)
Life and function of cells must be maintained permanently. Hence, logistics in deliv-
ery of nutrients and oxygen to cell membranes and in removal of residuals from cells
are an important issue when studying functional body. Transportation pathway is the
hydraulic pumping system of two separate vascular parts, the arterial for delivery and
the venous for removal; both do not serve at the "door", i.e. the cell membranes, but
only to the "gate" of cell 'surroundings', the interstitial space filled with 11 L10 fluids;
that gate for logistics – pictorially speaking – is the walls of close-by capillaries. The
distance of generally < 50𝜇𝑚 from "gate" to "door" is covered by 'shaking' in a few
seconds, while complete logistic distribution in the vascular system takes 30 seconds11
of 'stirring' in rest. Function units are heart, vessels, and blood plasma and blood cells
(as vehicles for oxygen).
3.3 Function Aggregate E (Energy)
For intra-cellular adenosine triphosphate (ATP) energy production, body cells con-
sume amino acids, fatty acids, glucose from intestinal tract and liver and oxygen from
lungs for combustion; combustion residuals, water and carbon dioxide, and others are
disposed of from cells to kidneys and lungs (as appropriate) on same passage ways.
Function units of energy sub-system are alimentary tract, respiratory tract, liver, bile,
8
Clinically, V represents the functional condition of a person's body system reduced to keeping
its cellular system Z of 1014 cells alive, without any communication with its outside world
outside, activity only as reexes, and thus totally dependent on 24-hrs care – in clinical terminol-
ogy, in vegetative state – cf. [22], [23], [2] for appropriate clinical definition.
9
The disease is called amyotrophic lateral sclerosis (ALS).
10
Applies to 70 kg male [11].
11
For a blood "round-trip" of 60 seconds [11].
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kidney, bladder, urinary tract; their functions are coordinated by function aggregate M
for management and control of all functional activity.
Fig. 2. Structural "Hydraulic" Token Ring Logistics
3.4 Function Aggregate M (Management and Control of Functional Activity)
Main function units of M are nervous systems and hormone or endocrine system; the
latter releases chemical messengers into blood vessels for delivery to cell's target
receptors; some of the former can do as well (neuroendocrines), though most nerves
use faster and very specifically targeted point-to-point transmission of chemical (neu-
rotransmitters) or electrical signals along nerve fibers; see [19] for more information
close to the present context and [11] for detailed physiology.
Fig. 3. Complexity of Controls in Liver
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4 Kybernetic Modeling
I suggest a top-down approach that builds on analogies with engineered systems at
each level and properties that emerge from structures of interaction among next level
functional components.
4.1 Foundations
The approach rests upon the distinction of material science and organizational sci-
ence, in other words, the separation of functional logic – or logical structure of func-
tional processes – in a multi-level design from physical realization at material level.
By analogy, consider multi-level network systems structure in computer science [15]:
well-known are two models, the ISO reference model and IBM's System Network
Architecture (SNA), both designed for distributed computer systems, both with seven
though not completely matching layers and different definitions, and in particular,
both models refer all physical transfers to a lowest-level physical layer. Correspond-
ingly, one may refer all physical realizations to human body system's basic layer, its
cellular system [20].
Principle 4
The cellular system, considered as material, can be disregarded in design of logical
'wiring' plan.
This is actually a paraphrase of the kybernetic paradigm, cf. Corollary 1; one will
therefore try to model schaltgefge within each functional level by analogy with a
functionally similar engineered system.
It is well-known, that complex adaptive systems (CAS) are characterized by highly
interwoven control structures across all levels of hierarchy and non-linear energy
transfer dynamics between components; this creates emergent properties of the sys-
tem – in parts or in whole – that cannot be explained by component properties, cf.
[17] for an interesting introduction to the subject. As this is not helpful in kybernetic
modeling, emergence is interpreted as interaction between same-level function units;
it then expresses as property of the function aggregate composed from these function
units.
Principle 5
Consider [20] any function aggregate; interactions of its function units express as
emergent property of the function aggregate. The emergent property becomes visible
in interactions between function aggregates.
4.2 With-in Level
As an example, consider function aggregate T (logistics); it actually connects all
function aggregates listed in 3.2, including itself. This connectivity exists in material
and in logic; the latter because of its physical realization (supplying all cells). It close-
ly corresponds to IBM's Token RingTM computer network hardware: tokens are sent
along a functional ring and every computer attached can read tokens and will either
ignore or take the message up depending on whether it is named recipient or not. In
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human body system, it is not electrons and wire but hydraulic movement of a liquid
medium, the blood, in pipes.
4.3 Between Levels
Consider any fixed functional level n in 3.1, n > 1, and assume there are kj function
units, Bj,1, …, Bj,kj , that combine to function aggregate Aj , and assume j = 1, …, m.
Then, properties of Aj emerge from interactions among respective Bj,1, …, Bj,kj and
become visible at level n - 1 in interactions between A1, …, Am. In this way, properties
visible in interactions at level n – 1 are binding in the sense of reducing the degrees of
freedom for interactions at level n. Though emergent properties that arise from inter-
action of function units at lower level then express at upper level, such properties are
only 'contextual' or 'relative' properties and not absolute properties that would apply
irrespectively of upper level 'neighborhood' settings. This implies that bottom-up
modeling may produce inconsistent results for different levels.
4.4 Realization Path
Development of a coherent control 'documentation' for HWBS may follow engineer-
ing suggestions for plantwide control [9] that start with a distinction of process mod-
els, physical models and procedure control models and different control types as basic
control, procedural control and coordination control; for each of these concepts its
correlate in the HWBS setting only sketchily described above - has to be found.
Re-engineering human body system controls specifically implies the control require-
ments definition (CRD) that covers process operating conditions (POD), control con-
cept, and control strategy [9]. The POD will describe operating states like routine
activities, exception handling, primary control objectives, performance information; it
shall be written in a top-down manner, for each logical unit at every level [9]. The
control concept will specify the control requirements for every logical unit; cf. [9] for
more detail and an almost complete worked example.
4.5 Empirical Testing
While physical realization of couplings is not an issue for kybernetik modeling of
management and control structures, any such modeling still requires a 'proof of con-
cept': it is to be demonstrated that dynamic subsystem performance is close to target
values. This can be achieved in mainly two ways, mathematical modeling of compo-
nent interaction dynamics (e.g. [3], or in silico experimentation with agent-based
modeling (ABM) [26]. For example, with functional aggregates of Level 2 in Fig. 3 as
'agents', develop a management and control concept for their Level-2 interactions
from the Token Ring model in 4.2, and then test it in silico under adequate scenarios
for Level-2 dynamic interaction.
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5 Conclusions
Re-engineering human body system controls holistically can be assumed to be viable
in top-down modeling with functionally defined levels: it permits to test models and
hypotheses in clinical settings before one proceeds to next lower functional level not
possible in the bottom-up approach that is prone to confuse cause and effect.
The commonly invoked 'genetic dogma' suggests viable bottom up modeling of hu-
man body system from molecules, genes and proteins to cells, tissue and organs [16];
however, desert dunes are shaped by wind, not by sand particles which are ground
finer and finer by their wind-enforced interaction though chemical and physical prop-
erties of sand particles limit options for wind-driven shapes, still. Similarly in living
systems shaped by evolution, bottom-up modeling is not advised as principles that can
guarantee consistency at upper levels are lacking.
Therefore, top-down modeling is appropriate and it must start from Level-1 functional
groups and a kybernetic model of their within-level interaction that can explain the
emergent properties which express at Level 0 of a person's whole-body system
(HWBS); such level-0 expression is called 'clinical' or 'behavioral', depending on
context of observation.
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