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ФИЗИКО-ХИМИЧЕСКИЕ ОСНОВЫ НАНОТЕХНОЛОГИИ. Профессор Н.Г. Рамбиди. 13. самоорганизация. Самоорганизация или вынужденное формирование ?. Самоорганизация или вынужденное формирование ?. Самоорганизация ?. Matched: common in homoepitaxy, sometimes in heteroepitaxy . Самоорганизация ?.

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ФИЗИКО-ХИМИЧЕСКИЕ ОСНОВЫ НАНОТЕХНОЛОГИИ

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1166514

ФИЗИКО-ХИМИЧЕСКИЕОСНОВЫНАНОТЕХНОЛОГИИ

Профессор Н.Г. Рамбиди


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13. самоорганизация


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Самоорганизация или вынужденное формирование?


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Самоорганизация или вынужденное формирование?


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Самоорганизация?

  • Matched: common in homoepitaxy, sometimes in heteroepitaxy


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Самоорганизация?


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Самоорганизация?

micelle

cross section

reverse

micelle

cross section


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Самоорганизация в природе


Systems self organization in natural

Systems Self-Organization in Natural

  • What are the mechanisms for integrating subunits activity into a coherently structured entity?

    • From simple neurons to the thinking brain

    • From individuals to the society

    • From molecule to pattern


Self organization in natural systems

Self-Organization in Natural Systems

  • What are the mechanisms for integrating subunits activity into a coherently structured entity?

    • From simple neurons to the thinking brain

    • From individuals to the society

    • From molecule to pattern

C3H4O4

NaBr

NaBrO3

HSO3

C12H8N2SO2Fe

Malonic acid

Sodium bromide

Sodium bromate

Sulfuric acid

1,10 Phenanthroline ferrous sulfate


Definitions

Definitions

  • What is Chaos ? [Poincarré] [Lorenz] [Prigogine]

    disorder, confusion, is opposed to order and method

    “Chaos” define a particular state of a system that is characterized by the following behaviors:

    • Do not repeat

    • Sensible to initial conditions: sharp differences can produce wide divergent results

    • Moreover, ordered and characterized by an unpredictable determinism

      • When moving away from equillibrium state => high organization

      • Non equillibrium phasis: bifurcations

      • Amplification => Symetry break


Definitions1

Definitions

  • What is Self-organization in natural systems?

    Self-organization is a process in which pattern at the global level of a system emerges solely from numerous interactions among the lower level components of the system. [Deneubourg 1977]

    Moreover, the rules specifying interactions among the system’s components are executed using only local information, without reference to the global pattern

    In other words, the pattern is an emergent property of the system, rather than a property imposed on the system by an external influence


Definitions2

Definitions

  • What is an emergent property ?

  • Many Agents

  • Simple rules

  • Many interactions

  • Decentralization

  • Emergent properties

  • Unreductibility

  • Macro-level (odre magnitude difference)

  • Feed-back effect on the micro-level

Conditions

Observations


Non living pattern formation

Non-living pattern formation

  • Based on physical and chemical properties

    • Belousov-Zhabotinsky reaction

    • Bénard convection cells

    • Sand dune ripples

    • Glass cracks

    • Mud cracks


Non living pattern formation1

Non-living pattern formation

  • Based on physical and chemical properties

    • Belousov-Zhabotinsky reaction

    • Bénard convection cells

    • Sand dune ripples

    • Glass cracks

    • Mud cracks


Non living pattern formation2

Non-living pattern formation

  • Based on physical and chemical properties

    • Belousov-Zhabotinsky reaction

    • Bénard convection cells

    • Sand dune ripples

    • Glass cracks

    • Mud cracks


Non living pattern formation3

Non-living pattern formation

  • Based on physical and chemical properties

    • Belousov-Zhabotinsky reaction

    • Bénard convection cells

    • Sand dune ripples

    • Glass cracks

    • Mud cracks


Non living pattern formation4

Non-living pattern formation

  • Based on physical and chemical properties

    • Belousov-Zhabotinsky reaction

    • Bénard convection cells

    • Sand dune ripples

    • Glass cracks

    • Mud cracks


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Формообразование в живых объектах


Pattern formation in biological systems

Pattern formation in biological systems

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerization

    • Occular dominance stripes


Pattern formation in biological systems1

Pattern formation in biological systems

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerization

    • Occular dominance stripes


Pattern formation in biological systems2

Pattern formation in biological systems

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerization

    • Occular dominance stripes


Pattern formation in biological systems3

Pattern formation in biological systems

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerization

    • Occular dominance stripes


Pattern formation in biological systems4

Pattern formation in biological systems

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerisation

    • Occular dominance stripes


Pattern formation in biological systems5

Pattern formation in biological systems

  • Most of those patterns are in fact fixed states of reactions that have occurred long time ago…

  • Patterns characterizing individuals

    • Giraffe coat

    • Zebra

    • Leopard

    • Vermiculated rabbitfish

    • Cone shells

    • Finger prints

    • Morel

    • Metamerisation

    • Occular dominance stripes

… or process is still running.

Mechanisms ?


Pattern formation in biological systems6

Pattern formation in biological systems

  • Patterns occurring during collective movement

    Microorganisms

    Insects and Crustaceans

    Social insects

    Fishes

    Birds

    Mammalians


Pattern formation in biological systems7

Pattern formation in biological systems

  • Patterns occurring during collective movement

    Microorganisms

    Insects and Crustaceans

    Social insects

    Fishes

    Birds

    Mammalians


Pattern formation in biological systems8

Pattern formation in biological systems

  • Patterns occurring during collective movement

    Microorganisms

    Insects and Crustaceans

    Social insects

    Fishes

    Birds

    Mammalians

Those patterns results from a permanent reorganization…

…mechanisms ?

  • No leader

  • No preexisting tracks

  • High sensitivity to heterogeneities

  • Based on the nearest neighbor perception


Activation inhibition mechanism

Degradation

Degradation

Slow diffusion

ACTIVATOR

ACTIVATEUR

INHIBITOR

INHIBITEUR

Quick diffusion

+

+

-

Activation-inhibition mechanism

autocatalyzis

Inspired by equations of reaction-diffusion [Turing1949]

inhibition

The activator autocatalyzes its own production, and also activates the inhibitor. The inhibitor disrupts the autocatalytic process. Meanwhile, the two substances diffuse through the system at different rates, with the inhibitor migrating faster. The result: local activation and long-range inhibition


Activation inhibition mechanism1

Activation-inhibition mechanism

Activation-inhibition and self-organization share a common mechanism

Starting point: a homogeneous substrate

(lacking pattern)

Positive feedback

(short-range activation, autocatalyzes)

Negative feedback

(long-range inhibition)


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Формообразованиев сложных системах


Pattern formation in colonies activity

Pattern formation in colonies activity

  • Patterns resulting from the activity of a society of…

    social insects

    • Ants

    • Bees

    • Wasps

    • Termites

      Mammalians

    • African Mole-rats

    • Humans


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Pattern formation in colonies activity

  • Patterns resulting from the activity of a society of…

    social insects

    • Ant

    • Bees

    • Wasps

    • Termites

      Mammalians

    • African Mole-rats

    • Humans


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Pattern formation in colonies activity

  • Patterns resulting from the activity of a society of…

    social insects

    • Ant

    • Bees

    • Wasps

    • Termites

      Mammalians

    • African Mole-rats

    • Humans


Attraction repulsion mechanisms

Attraction-repulsion mechanisms

Relations between Activation-inhibition mechanisms and attraction-repulsion mechanisms

They share a common mechanism

Starting point: a homogeneous substrate (lacking or different pattern)

Positive feedback (local activation or attraction rate to aggregates size)

Negative feedback (long-range inhibition, depletion in individuals)

Degradation

Degradation

Slow diffusion

ACTIVATOR

ACTIVATEUR

INHIBITOR

INHIBITEUR

Quick diffusion

+

+

+

+

-

-

Short range effect

ATTRACTION

STRENGTH

Long range effect

CONSUMPTION of FREEPARTICLE


Self organization in natural systems1

Self-Organization in Natural Systems

  • Definitions

  • Pattern formation

    In living and non-living systems

  • Social systems

    Sociality and gregarism

  • Cellular systems

    Cells build animals

  • Properties of self-organized systems


How cells build the animal

How cells build the animal ?

  • From one cell to the next generation…

  • From one cell to the thinking brain…

  • Planed mechanisms:

    • Expression of the genetic program

  • Scale changes

    • And long range communication

  • Self-organizing mechanisms

    • Reaction-diffusion (activation-inhibition)

    • Cells migrations (Aggregation-repulsion)


How cells build the animal1

How cells build the animal ?

  • Cell proliferation

  • Cell differentiation

  • Cell communication

  • Cell memory

  • Regenerative potential


How cells build the animal2

How cells build the animal ?

Strict genetic program

Complex triggering

  • Cell proliferation

  • Cell differentiation

  • Cell communication

  • Cell memory

  • Regenerative potential


How cells build the animal3

How cells build the animal ?

Amplification of a behaviour (metabolism)trigger: cell environment

  • Cell proliferation

  • Cell differentiation

  • Cell communication

  • Cell memory

  • Regenerative potential


How cells build the animal4

How cells build the animal ?

  • Cell proliferation

  • Cell differentiation

  • Cell communication

  • Cell memory

  • Regenerative potential

Contact

Mechanical

Direct

Indirect

Secretion diffusion

At different range and time


How cells build the animal5

How cells build the animal ?

Nucleus (DNA)

  • Cell proliferation

  • Cell differentiation

  • Cell communication

  • Cell memory

  • Regenerative potential

Cytoplasm

  • RNA

  • Proteins

    • toxins

  • Controled exchanges

    Internal state, memoryof previous events (environments)


    How cells build the animal6

    How cells build the animal ?

    • Accidental changes in cell environment

      • Backward differentiation

    • Not all animals

      • Global communication (blood circulationand nervous system)

    • Not all cells

    • Wounds should respect

      • Gradients

      • Periods of sensibility

    • Cell proliferation

    • Cell differentiation

    • Cell communication

    • Cell memory

    • Regenerative potential


    How cells build the animal7

    How cells build the animal ?

    • Low dynamic : STRUCTURES

    • High dynamic : FUNCTIONING

      • Neural activity

      • Immune system answer

    • Cell proliferation

    • Cell differentiation

    • Cell communication

    • Cell memory

    • Regenerative potential


    1166514

    Самоорганизация поведения


    1166514

    Ants

    • Organizing highways to and from their foraging sites by leaving pheromone trails

    • Form chains from their own bodies to create a bridge to pull and hold leafs together with silk

    • Division of labour between major and minor ants


    Social insects

    Social Insects

    • Problem solving benefits include:

      • Flexible

      • Robust

      • Decentralized

      • Self-Organized


    Interrupt the flow

    Interrupt The Flow


    The path thickens

    The Path Thickens!


    The new shortest path

    The New Shortest Path


    Adapting to environment changes

    Adapting to Environment Changes


    Four ingredients of self organization

    Four Ingredients of Self Organization

    • Positive Feedback

    • Negative Feedback

    • Amplification of Fluctuations - randomness

    • Reliance on multiple interactions


    Web clustering

    WEB CLUSTERING

    Why?

    The size of the internet has doubling its size every year. Estimated 2.1 billion as of July 2001

    Organizing and categorizing document is not scalable to the growth of internet.

    Document clustering?

    Is the operation of grouping similar document to classes that can be used to obtain an analysis of the content.

    Ant clustering algorithm categorize web document to different interest domain.


    Ant colony models for data clustering

    Ant Colony Models for Data Clustering

    Data clustering?

    is the task that seek to identify groups of similar objects based on the value of their attributes.

    • Messor sancta ants collect and pile dead corpses to form “cemeteries” (Deneubourg et al. )

    f: fraction of items in the neighborhood of the agent

    k1, k2: threshold constants


    Ant colony models for data clustering1

    Ant Colony Models for Data Clustering

    The model later extend by Lume & Faieta to include distance function d, between data objects .

    • c is a cell, N(c) is the number of adjacent cells of c, alpha is constant


    Experimental results

    Experimental Results

    • t = 0


    Experimental results1

    Experimental Results

    • t = 50,000


    Experimental results2

    Experimental Results

    • t = 200,000


    Experimental results3

    Experimental Results

    • t = 300,000


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