Een dynamisch model over een prooi predator relatie tussen verschillende populaties onder invloed van abiotische factoren.
Een dynamisch model over een prooi predator relatie tussen verschillende populaties onder invloed van abiotische factoren.
Un modello per l'effetto di alcuni fattori (T, pH, aW, conservanti) e della competizione/amensalismo sulla crescita di una comunità microbica semplificata (Listeria monocytogenes, Latilactobacillus sakei) negli alimenti.  Lo scopo del modello è illustrare concetti come:  a. la crescita in assenza o
Un modello per l'effetto di alcuni fattori (T, pH, aW, conservanti) e della competizione/amensalismo sulla crescita di una comunità microbica semplificata (Listeria monocytogenes, Latilactobacillus sakei) negli alimenti.
Lo scopo del modello è illustrare concetti come:
a. la crescita in assenza o in presenza di competizione/amensalismo
b. l'effetto delle interazioni microbiche
c. l'effetto di alcuni fattori ambientali e tecnologici
Il sistema potrebbe ragionevolmente rappresentare un insaccato fermentato durante la produzione. Tuttavia non ho inserito quelli che potrebbero essere effetti di declino delle popolazioni dovuti alle condizioni avverse durante la stagionatura e conservazione.
32 6 months ago
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION  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 compon
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

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)

Een dynamisch model over een prooi predator relatie tussen verschillende populaties onder invloed van abiotische factoren.
Een dynamisch model over een prooi predator relatie tussen verschillende populaties onder invloed van abiotische factoren.
A simple and easy to follow model of how fertility and mortality affect a population, using ferns as an example.
A simple and easy to follow model of how fertility and mortality affect a population, using ferns as an example.
This model is a basic model on how the glucose level in blood is maintained.
This model is a basic model on how the glucose level in blood is maintained.

From NIMH Research Domain Criteria  website  and BMC  paper  and 2013  series  on current controversies in psychiatry.
From NIMH Research Domain Criteria website and BMC paper and 2013 series on current controversies in psychiatry.
Bipolar II treatment modeling using Van der Pol-like oscillators.  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 ca
Bipolar II treatment modeling using Van der Pol-like oscillators.

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.
 for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu     Description:    A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination
for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu

Description:

A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination in each generation as well as the overall average height by generation.

Adjust all sliders before beginning simulation. Make sure the A1A2 parameters are equal to the A2A1 parameters.
4 months ago
Questo modello usa un'altra ipotesi per la natura (e durata della fase lag). La popolazione N è composta da una frazione di cellule che non crescono NG e una di cellule che crescono immediatamente alla massima velocità, G. Il rapporto fra le due frazioni determina la durata della fase lag
Questo modello usa un'altra ipotesi per la natura (e durata della fase lag). La popolazione N è composta da una frazione di cellule che non crescono NG e una di cellule che crescono immediatamente alla massima velocità, G. Il rapporto fra le due frazioni determina la durata della fase lag
Simulation of MTBF with controls   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
Simulation of MTBF with controls

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.