#### THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)

##### Guy Lakeman

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Supply Demand Strategy

- 3 years 4 months ago

#### Food Chain

##### Ta Wanda Woody

- 1 year 9 months ago

#### BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

##### Guy Lakeman

F(t) = 1 - e ^ -λt Where • F(t) is the probability of failure • λ is the failure rate in 1/time unit (1/h, for example) • t is the observed service life (h, for example)

The inverse curve is the trust time

On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.

This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.

A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime,

B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

**Early Life**If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

**Useful Life**

The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.

**Wearout**

The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period.

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Risk Failure Strategy

- 2 years 2 months ago

#### Prey&Predator

##### Tsogbadrakh Banzragch

**Physical meaning of the equations**The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.2. The food supply of the predator population depends entirely on the size of the prey population.3. The rate of change of population is proportional to its size.4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.5. Predators have limitless appetite.As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

**Prey**

When multiplied out, the prey equation becomesdx/dt = αx - βxy The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

PredatorsThe predator equation becomes

dy/dt = -

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.

- 4 months 3 days ago

#### FORCED GROWTH INTO TURBULENCE

##### Guy Lakeman

**FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION**

**BEWARE pushing increased growth blows the system!**

**(governments are trying to push growth on already unstable systems !)**

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Strategy Weather

- 5 years 4 weeks ago

#### OVERSHOOT GROWTH INTO TURBULENCE

##### Guy Lakeman

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Strategy Weather

- 2 years 2 months ago

#### Yo-yo Learning and Teaching Strategy

##### Geoff McDonnell ★

Nested multilevel inquiry across multiple levels of organization of biology concepts. Adapted from Knippels (2002) PhD Thesis at http://bit.ly/GGcKo1 . Note the similarity to the nested adaptive cycles of socio-ecological systems in IM 1169

- 3 years 10 months ago

#### E coli growth model

##### Edythe ★

- 5 months 3 weeks ago

#### Rock Platform Food Web

##### Elyse Balzer

- 1 year 9 months ago

#### Plant, Deer and Wolf Population Dynamics

##### leah c

- 1 year 7 months ago

#### Arctic Populations

##### Fathima Amanat

- 1 year 1 month ago

#### Wolves vs. Moose Populations

##### Fathima Amanat

- 1 year 1 month ago

#### honeybee hive population model

##### Jonathan Sandoe

- 2 years 9 months ago

#### Plant, Deer and Wolf Population Dynamics - ISD OWL

##### Kevin Collins

- 4 months 1 week ago

#### E coli life cycle model

##### Edythe ★

Exponential Growth Collapse Bacteria Biology Microbiology Science

- 3 years 4 days ago

#### Plant, Deer and Wolf Population Dynamics G-IV Intro

##### Kevin Collins

- 8 months 1 week ago

#### Bipolar II dynamics

##### Eduardo Enrique Escamilla

In this simulation an afflicted individual with Bipolar II disorder is put to treatment after 20 months the calibration of the medicine or treatment he recieves is such that it simulates the natural cycles of a "normal being". You can note by manipulating the parameters that sometimes too much treatment disrupts equilibria. Also note that in the state diagrams there are 2 limit cycles, the lower one being the healthiest as there are less changes.

- 4 years 11 months ago

#### Disease Dynamics

##### Fathima Amanat

- 1 year 1 month ago

#### Biology levels and genetics

##### Geoff McDonnell ★

- 1 year 8 months ago

#### Functional dimensions of behavior

##### Geoff McDonnell ★

- 3 years 2 months ago

#### chordata

##### Jed Brown

- 2 years 8 months ago

#### Evolution extended synthesis

##### Geoff McDonnell ★

From Fig 1.1 p11 Pigliucci M and Muller GB (2010) **Evolution: The Extended Synthesis**. This is a shift in emphasis from statistical correlation to mechanistic causation (p12), including the conditions for the origin and innovation of traits (p13). It overcomes the** gradualism, externalism and gene centrism** of the Modern Synthesis. Non-gradual change is a property of complex dynamical systems. EvoDevo processes generate particular forms of change rather than others.Genes are followers in the evolutionary process that capture the emergent interactions among environment, development and inheritance into genetic-epigenetic circuits, which are passed to and elaborated on in subsequent generations (p14).

- 6 months 2 days ago

#### biome

##### charles johnson

- 1 year 4 months ago

#### Koein en Reuzenvogels en blumentjens Dio 5V prey predator

##### Dionijs Burmeister

Prey Predator Abiotic Factors Dynamic Model Biology Population

- 2 years 8 months ago