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Living Systems

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System Concepts

System Description: System

System Patterns

Natural Systems

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Living Systems

This document contains abstract system descriptions for use as a set of Living System patterns.

The following system descriptions are included in this document:

Additional system descriptions may be added as these system descriptions are used.

PDF:: System Description: Person (Human Being), Version 2.4, 04-April-2023

PDF:: System Description: Social System, Version 0.10, 03-November-2020

PDF:: System Description: Ecological System (Ecosystem), Version 0.4, 06-November-2023

Living Systems Conceptual Model


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Living Systems Conceptual Model


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System Concepts

System Description: System

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Abstract System: Living System

View: System Name and Class

Name:  Living System

Based on: Natural System

Abstract System: This system has been identified as an abstract system that cannot be implemented directly. The abstract system establishes a shared pattern of characteristics that any system can use to describe its unique characteristics when referenced in the 'based on' list above. These references are described using a generalization association in UML.

The following are definitions used in this system description

  • Life
  • Metabolism
  • Autopoiesis
  • Health

View: System Purpose

A living system is a system that is alive. An autonomous autopoietic system.

The purpose of this system is:

  • to create and sustain a living system.
  • to live fully in a context or environment suitable for the system to sustain life
  • to acquire and consume energy, matter and information at a level to sustain life.
  • to maintain balance far from equilibrium

This living system may be a part of another system (A holon).

View: System Properties

System Quantity Properties

These variables will be identified for a specific living system using this abstract class. Common quantity variables might be:

  • Quantity and quality of Inflow of energy, matter and information
  • Quantity and quality of the outflow of energy, matter and waste.

Systemic Quality Properties

These variables will be identified for a specific living system using this abstract class. Common quantity variables might be:

  • Health Aliveness
  • Closed operationally (organizationally)

Systemic Measurable Variables

These variables will be identified for a specific living system using this abstract class. Common variables might be:

  • Health of the living system (to the best extent possible)

Systemic Capabilities or Functions

These capabilities will be defined for a specific type of living system using this abstract class

  • These capabilities or functions are necessary to fulfil the purpose of the living system.
  • These form the basic building blocks of the living system

System States

The various defined states that the system-of-interestcan be in.

  • Conception
  • Viable living system (from conception)
  • Healthy Living System. (in a state of healthy dynamic balance)
  • Living system Off-Balance (with illness)
  • Dying Living System (unable to sustain life fully)
  • Death.

View: System Stakeholders and Concerns

The Living System:

  • Am I developing?

  • Am I able to fulfill my purpose?

  • Am I able to acquire sufficient energy, matter and information? Is my environment safe?

Other stakeholders as appropriate for the living system.

View: System Environment (Context)

The environment and the potential impacts on the Living System will be included for a specific living system. .

The living system is structurally coupled to its environment through a boundary / membrane of its own making.

this section may include interactions in the areas of:

  • Transactional
  • Contextual
  • Regulatory
  • Physical environment
  • Flow of energy and matter (items needed to sustain life)

View: Pattern of Organization

The characteristic pattern of organizaiton for a living system is an autonomous autopoietic system typically consisting of::

  • a network pattern of elements within a membrane
    • Consisting of information elements
    • Transformation elements
  • A self-generating network of production processes
  • Open to the flow of energy, matter and information
  • a set of Dissipative structures to manage the flow of energy, matter and information.
  • Closed organizationally within a boundary of its own making.
  • A whole system may be a part (component) of another system (holon)
  • a boundary or membrane of its own making.

Living System Top Level Model

Grier Miller has identified 20 types of elements in a living system.

James Grier Miller Living System

Each of the elements identified by Grier Miller will be translated into specific system elements based upon the type of system-of-interest being explored.

View: Structural Changes

The Behavior (Structural Changes) section describes a specific instance (configuration of components) of a system structure that results in systems behaviour. The system behavior includes descriptions of the following as needed:

  • a specific configuration or embodiment of a system structure (pattern of organization) (e.g. specific system elements or components, their relationships)
    • including any mathematical methods or characteristics of specific interaction types
  • the triggers arising from a meaningful disturbance
  • the process steps or sequence and any interaction in response to a specific trigger
  • any models or data supporting the response along with any mathematical methods used.
  • Any behavioral system or focused models (UML Diagrams, or Causal Loop Diagrams, etc.)

Configuration / Scenario:

Describes any configuration / scenario attributes for a specific system-of-interest. This may not be appropriate for all system descriptions (e.g. patterns or abstract systems).

The living system is structurally coupled to its environment and responds cognitively to disturbances from the environment. The cognitive response may ignore or take action on the disturbance. This response triggers a specific type of structural change.

  • The structural changes are constrained by structural determinism. These structural changes preserve the pattern of organization of the living system.
  • This cognitive response allows the system to learn and adapt through these structural changes. The structures change their state or process abilities through these changes. As a result, the living system is a cognitive, learning, adaptive system.
  • This set of structural changes provides for a self-organizing and self-generating through a network of feedback and emergence.

Cyclical (Repeating / Regular) Processes

Triggers initiate a specific process within the self-generation or self-renewal network of production processes

Cyclical autopoietic processes occur.

Development Life Cycle Processes

Triggers initiate a specific process within the life cycle set of processes. These processes govern the development of the living system from conception to death. These will be unique to the living system.

These tend to be self-organizing or emergent types of processes. These may change the structure (pattern of organization) and may introduce new or novel abilities of the living system. Mechanisms for this type of innovation or emergence depend upon the type of living system and the environment.

.

References

The following references support this type of system-of-interest.

Book References

The Systems View of Life, Fritjof Capra and Pier Luigi Luisi



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https://en.wikipedia.org/wiki/Living_systems

Living systems are life forms (or, more colloquially known as living things) treated as a system. They are said to be open self-organizing and said to interact with their environment. These systems are maintained by flows of information, energy and matter. Multiple theories of living systems have been proposed. Such theories attempt to map general principles for how all living systems work.

Context

Some scientists have proposed in the last few decades that a general theory of living systems is required to explain the nature of life.[1] Such a general theory would arise out of the ecological and biological sciences and attempt to map general principles for how all living systems work. Instead of examining phenomena by attempting to break things down into components, a general living systems theory explores phenomena in terms of dynamic patterns of the relationships of organisms with their environment.[2]

Theories

Miller's open systems

James Grier Miller's living systems theory is a general theory about the existence of all living systems, their structure, interaction, behavior and development, intended to formalize the concept of life. According to Miller's 1978 book Living Systems, such a system must contain each of twenty "critical subsystems" defined by their functions. Miller considers living systems as a type of system. Below the level of living systems, he defines space and time, matter and energy, information and entropy, levels of organization, and physical and conceptual factors, and above living systems ecological, planetary and solar systems, galaxies, etc.[3][4][5] Miller's central thesis is that the multiple levels of living systems (cells, organs, organisms, groups, organizations, societies, supranational systems) are open systems composed of critical and mutually-dependent subsystems that process inputs, throughputs, and outputs of energy and information.[6][7][8] Seppänen (1998) says that Miller applied general systems theory on a broad scale to describe all aspects of living systems.[9] Bailey states that Miller's theory is perhaps the "most integrative" social systems theory,[10] clearly distinguishing between matter–energy-processing and information-processing, showing how social systems are linked to biological systems. LST analyzes the irregularities or "organizational pathologies" of systems functioning (e.g., system stress and strain, feedback irregularities, information–input overload). It explicates the role of entropy in social research while it equates negentropy with information and order. It emphasizes both structure and process, as well as their interrelations.[11]

Lovelock's Gaia hypothesis

Main article: Gaia hypothesis

The idea that Earth is alive is found in philosophy and religion, but the first scientific discussion of it was by the Scottish geologist James Hutton. In 1785, he stated that Earth was a superorganism and that its proper study should be physiology.[12]: 10 The Gaia hypothesis, proposed in the 1960s by James Lovelock, suggests that life on Earth functions as a single organism that defines and maintains environmental conditions necessary for its survival.[13][14]

Piast's self-maintainable information

According to the theory of self-maintainable information, entities can be ranked by how alive they are, gaining the ability to evolve and maintaining distinctness.

All living entities possess genetic information that maintains itself by processes called cis-actions.[15] Cis-action is any action that has an impact on the initiator, and in chemical systems is known as the autocatalytic set. In living systems, all the cis-actions have generally a positive influence on the system as those with negative impact are eliminated by natural selection. Genetic information acts as an initiator, and it can maintain itself via a series of cis-actions like self-repair or self-production (the production of parts of the body to be distinguished from self-reproduction, which is a duplication of the entire entity). Various cis-actions give the entity additional traits to be considered alive. Self-maintainable information is a basic requirement - a level zero for gaining lifeness and it can be obtained by any cis-action like self-repair (like a gene coding a protein that fixes alteration to a nucleic acid caused by UV radiation). Subsequently, if the entity is able to perform error-prone self-reproduction it gains the trait of evolution and belongs to a continuum of self-maintainable information - it becomes part of the living world in meaning of phenomenon but not yet a living individual. For this upgrade, the entity has to process the trait of distinctness, understood as an ability to define itself as a separate entity with its own fate. There are two possible ways of reaching distinctness: 1) maintaining an open-system (a cell) or/and 2) maintaining a transmission process (for obligatory parasites). Fulfiling any of these cis-actions raises the entity to a level of living individual - a distinct element of the self-maintainable information's continuum. The final level regards the state of the entity as dead or alive and requires the trait of functionality.[15] This approach provides a ladder-like hierarchy of entities depending on their ability to maintain themselves, their evolvability, and their distinctness. It distinguishes between life as a phenomenon, a living individual, and an alive individual.[15]

Morowitz's property of ecosystems

A systems view of life treats environmental fluxes and biological fluxes together as a "reciprocity of influence,"[16] and a reciprocal relation with environment is arguably as important for understanding life as it is for understanding ecosystems. As Harold J. Morowitz (1992) explains it, life is a property of an ecological system rather than a single organism or species.[17] He argues that an ecosystemic definition of life is preferable to a strictly biochemical or physical one. Robert Ulanowicz (2009) highlights mutualism as the key to understand the systemic, order-generating behaviour of life and ecosystems.[18]

Rosen's complex systems biology

Main article: Complex systems biology

Robert Rosen devoted a large part of his career, from 1958[19] onwards, to developing a comprehensive theory of life as a self-organizing complex system, "closed to efficient causation". He defined a system component as "a unit of organization; a part with a function, i.e., a definite relation between part and whole." He identified the "nonfractionability of components in an organism" as the fundamental difference between living systems and "biological machines." He summarised his views in his book Life Itself.[20]

Complex systems biology is a field of science that studies the emergence of complexity in functional organisms from the viewpoint of dynamic systems theory.[21] The latter is also often called systems biology and aims to understand the most fundamental aspects of life. A closely related approach, relational biology, is concerned mainly with understanding life processes in terms of the most important relations, and categories of such relations among the essential functional components of organisms; for multicellular organisms, this has been defined as "categorical biology", or a model representation of organisms as a category theory of biological relations, as well as an algebraic topology of the functional organisation of living organisms in terms of their dynamic, complex networks of metabolic, genetic, and epigenetic processes and signalling pathways.[22][23] Related approaches focus on the interdependence of constraints, where constraints can be either molecular, such as enzymes, or macroscopic, such as the geometry of a bone or of the vascular system.[24]

Bernstein, Byerly and Hopf's Darwinian dynamic

Main article: Evolutionary dynamics

Harris Bernstein and colleagues argued in 1983 that the evolution of order in living systems and certain physical systems obeys a common fundamental principle termed the Darwinian dynamic. This was formulated by first considering how macroscopic order is generated in a simple non-biological system far from thermodynamic equilibrium, and then extending consideration to short, replicating RNA molecules. The underlying order-generating process was concluded to be basically similar for both types of systems.[25][26]

Gerard Jagers' operator theory

Gerard Jagers' operator theory proposes that life is a general term for the presence of the typical closures found in organisms; the typical closures are a membrane and an autocatalytic set in the cell[27] and that an organism is any system with an organisation that complies with an operator type that is at least as complex as the cell.[28][29][30][31] Life can be modelled as a network of inferior negative feedbacks of regulatory mechanisms subordinated to a superior positive feedback formed by the potential of expansion and reproduction.[32]

Kauffman's multi-agent system

Stuart Kauffman defines a living system as an autonomous agent or a multi-agent system capable of reproducing itself or themselves, and of completing at least one thermodynamic work cycle.[33] This definition is extended by the evolution of novel functions over time.[34]

Budisa, Kubyshkin and Schmidt's four pillars

Definition of cellular life according to Budisa, Kubyshkin and Schmidt

Budisa, Kubyshkin and Schmidt defined cellular life as an organizational unit resting on four pillars/cornerstones: (i) energy, (ii) metabolism, (iii) information and (iv) form. This system is able to regulate and control metabolism and energy supply and contains at least one subsystem that functions as an information carrier (genetic information). Cells as self-sustaining units are parts of different populations that are involved in the unidirectional and irreversible open-ended process known as evolution.[35]

See also

References

  1. Budisa, Nediljko; Kubyshkin, Vladimir; Schmidt, Markus (22 April 2020). "Xenobiology: A Journey towards Parallel Life Forms". ChemBioChem. 21 (16): 2228–2231. doi:10.1002/cbic.202000141. PMID 32323410.

Further reading

  • Kenneth D. Bailey, (1994). Sociology and the new systems theory: Toward a theoretical synthesis. Albany, NY: SUNY Press.
  • Kenneth D. Bailey (2006). Living systems theory and social entropy theory. Systems Research and Behavioral Science, 22, 291–300.
  • James Grier Miller, (1978). Living systems. New York: McGraw-Hill. ISBN 0-87081-363-3
  • Miller, J.L., & Miller, J.G. (1992). Greater than the sum of its parts: Subsystems which process both matter-energy and information. Behavioral Science, 37, 1–38.
  • Humberto Maturana (1978), "Biology of language: The epistemology of reality," in Miller, George A., and Elizabeth Lenneberg (eds.), Psychology and Biology of Language and Thought: Essays in Honor of Eric Lenneberg. Academic Press: 27-63.
  • Jouko Seppänen, (1998). Systems ideology in human and social sciences. In G. Altmann & W.A. Koch (Eds.), Systems: New paradigms for the human sciences (pp. 180–302). Berlin: Walter de Gruyter.
  • James R. Simms (1999). Principles of Quantitative Living Systems Science. Dordrecht: Kluwer Academic. ISBN 0-306-45979-5

External links

Systems science

See also

Autonomous Agency Theory

Biological organisation

Earth system science

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