GSD simulation

The limits to growth structure is based on the basic growth structure. And, as should be obvious, nothing grows forever as growth requires resources. Those required resources become a limits to growth.

High altitude environments challenge the physiology of mammals mainly due to hypoxic conditions. As a response to this, many mammals show molecular adaptations e.g. by mutations in the genes encoding the hemoglobins. This can result in an increase O2 affinity (and thereby a leftshifted O2 dissociation curve) which will enhance the pulmonary loading of O2. However, the shift can also hamper the O2 unloading process to the metabolic tissue. To elucidate this trade-off between loading and unloading a numerical computer model was made in the program Insigt maker based on the organism, deer mouse (Peromyscus maniculatus). The numerical solution was calculated by the Runge-Kutta method. A time step (dt) of 0.00001 was chosen, as the results were independent of dt at this value. This was tested by investigating the residual values of an interval of dt around 0.00001. The model showed how the trade-off is expressed at different altitudes and how the degree of advantages/disadvantages varies. Based on the model it can be suggested that the trade-off is beneficial, when the hypoxia is severe at high altitude. This is consistent with previously findings. 

 

Launchpad for insights related to Systems and Complexity in general and Systems Science for Health in particular. Current key participants are public health researchers, health service managers, clinicians, and mental health policy makers and practitioners

Enabling a Happy Tomorrow - EaHT (Gene Bellinger Model)

See Gene's excellent explication at 

Book Summary based on Terry Sampson's summary of Philip Ball's May 2024 Royal Society presentation. A causal loop scaffolding using Gene Bellinger's mc and mr AI prompts for Gemini added in Jan2026. See also Philip Ball's article summary insight

A simple rookie pro workforce supply chain like Gene's insight with optimal intake policy taking into account the target for professionals and the trainees already in the pipeline. See also Gene's insight for data patterns

 Learning THread for hybrid models including Grimm's ODD and Nate Osgood's ABM Modeling Process and Courses

WIP Summary of Cell Systems 2024 article Versatile system cores as a conceptual basis for generality in cell and developmental biology

As part of becoming familiar with InsightMaker, the purpose of this model is to merely replicate Gene Bellinger's completed "Moose_Wolves" model.  

All credit needs to be given to Gene.   Thank you InsightMaker.com for making it so easy to rebuilt and model and provide details on equations, algorithms.  

Adapted from Fig.1.from Ana V Diez Roux (2011) Complex Systems Thinking May Help Us Transcend Current Impasses in Health Disparities Research Am J Public Health 2011;101 1627-1634 http://ajph.aphapublications.org/cgi/content/abstract/101/9/1627?etoc

The calorie reduction by Gene, copied so I can include stress, high intensity exercise, sleep and carb restriction.

Causal loop diagram illustrating how evolution, in the form of small incremental change (realized through random genetic mutation) paired with natural selection, serves to evolve species.

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We want to know the estimated projected Earnings before tax of a 5 year project. For this we have modeled Sales Growth, Cost of goods sold and Admin. expenses applying sensitivity testing by using probability distributions.