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Clone of Logística de chontalpa
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SM4
5 months ago
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CIVE: Progress Report 1
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System Modeling 4: Mapping Protein formation Instructions
5 months ago
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Modified from Sterman (2006) and Gene Bellinger's Assumptions IM-351 by Dr Rosemarie Sadsad UNSW See also Complex Decision Technologies IM and IM-63975

Clone of Virtual Experiments
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Protein Formation
5 months ago
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Unfolding causal loop story of Chris Argyris' famous Harvard Business Review article inspired by Gene Bellinger's AI assisted kumu summary  
Teaching smart people how to learn
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Week4M
5 months ago
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From Fig 12.2 p317 Pigliucci M and Muller GB (2010) Evolution: The Extended Synthesis
Clone of Development dynamic interactions
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WK 4
5 months ago
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The Moran process: the simplest possible selection process in a population of two traits A and B. In each generation, a random part of the population is chosen to reproduce at the expense of the opposite trait.

The take-home message is this: random genetic drift always leads to one species supplanting another, but only if the drift is sufficiently particulate. As the drift becomes more and more continuous, so the duration of the fixation process approaches infinity.

To test this, start with mu=1 and notice that the simulation quickly runs to fixation (either A or B equal to 10). mu is the quantity of population that mutate between A and B in a single generation. For mu=1, this means all individuals in either the A or B population transfer to the other side in the first generation, so clearly fixation occurs in the first generation.

But now reduce mu to 0.5, and notice that fixation takes a little longer. Then try mu = 0.25, 0.2, 0.1, 0.05 and 0.01 and notice how long fixation takes.

This was Gregor Mendel's great insight: genes are particulate. If they were not, traits would not fixate, but would instead smear over time into averaged trait values.
Moran
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​This working Simulation outlines the current impact the Koala population is undergoing to certain disease, enironmental impacts and human redevelopment and involvement, and then the actions which will need to be taken if the current trend is to improve. 

In the study we used a control group of 1000 individuals with a better then average birth to death ratio so the population with no outside influences or negative impacts would gradually grow. Then we introduced the current major dangers to the Koala with the current statistic trend of a 10% decline in population every year over a 20 year period. With this we then introduced measures and plans to reverse this trend and put the Koala population back on track. Of course figures are only speculative however there is a marked improvement over the 20 year period for the small koala population. 
Amber M N8840105
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Abstract
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. 

 

Clone of Model af O2 transport under hypoxi
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Causal loop summary of Belluz and Hall's 2025 Book, combined with Macronutrient metabolism and key biochemical metabolic cycles web article, based on my gemini interaction using Gene Bellinger's AI prompts
Food intelligence book summary
2 months ago
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This model depicts the current understanding of how I am managing my content across all the various web repositories.
@LinkedInTwitterYouTube
Content Management Process
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Causal Loop Diagram explanation of perceptual control theory (PCT), behavioral learning, allostasis and homeostasis based on my Gemini interaction using Gene Bellinger's AI prompts
Self and Context
4 months ago
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Michael Mann (climate change) and Peter Hotez' (infection) book Science under Siege causal loop diagram summary, aided by Gene Bellinger's AI scripts December 2025
Science under siege book summary
3 months ago
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Unfolding Causal Loop Diagram narrative of  Hospital Congestion based on my Gemini interaction Feb 2026 using Gene Bellinger's AI prompts
Overview of Hospital Congestion
4 months ago
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Causal loop diagram  using Gene Bellinger's mc and mr AI prompts added in Feb2026 based on gemini interaction around Philip Ball's 2023 article What distinguishes the elephant from E. coli: Causal spreading and the biological principles of metazoan complexity. See also How life works book summary insight

How Life Works Article Summary
4 months ago
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Causal loop diagram summary of Real Progressives Macro N Cheese episode 368 Socialism Unmade: Confronting Five Centuries of Capital with Ali Kadri, based on my interaction with Gemini Feb2026 using Gene Bellinger's AI prompts
Arab socialism unmade
4 months ago
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Causal loop diagram summary of Fadhel Kaboub's Global South substack post Sri Lanka's 17th IMF Debt Trap based on my Gemini interaction using Gene Bellinger's AI prompts
The IMF Debt Trap Sri Lanka
4 months ago
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A basic production model showing negative and positive loops, often called a balancing model.
Thanks
Gene.
Clone of Balancing loop model