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Simulate

Explore powerful simulation algorithms for System Dynamics and Agent Based Modeling. Use System Dynamics to gain insights into your system and Agent Based Modeling to dig into the details. Types of Modeling

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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

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Simplification of Prevention Investment Framework (private) IM See WIP integrating with economic view insight (private) and multiscale version IM private
HYPER Model Overview
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In this activity, the body reaction in the intake of food will be simulated: Food amount; type of food; when the intake of food took place; how fast the digestion occurs; reaction time of the pancreas; the connection between the blood glucose concentration and the insulin production.

The content will also cover the subject between the coordinated and harmonious functioning of the pancreas (which secretes insulin), the liver, and the body's cells (insulin receivers). The Homeostasis: Process that regulates the blood concentration. Together we’ll discover the cause-effects cycles that characterize the problem and how they become an important part of the solution.

This article will span the effect of pancreas’ insulin production in diabetes type I, as well as the cells’ glucose uptake and their rejection to insulin, all this with the intention of visualizing how it breaks into the cause-effect cycles that regulates the blood glucose concentration in the body, triggering the imbalance in health.  

Diabetes Learning Lab
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There are four relevant boundaries associated with the Network Magic situation.

Video

Network Magic/Boundaries
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Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

REM 221 - Causal Loop diagramming
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In the 1920s, mathematicians Vito Volterra and Alfred Lotka independently proposed
a model for populations of a predator species and its prey, such as hawk and
squirrel populations in a certain area. For simplicity, we assume that a hawk hunts
only squirrels and that no other animal eats squirrels. If the hawk’s only food source
is squirrel and the number of squirrels diminishes significantly, then scarcity of food
will result in starvation for some of the hawks. With reduced numbers of hawks, the
squirrel population should increase.
Predator-Prey
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Stock: A backlog of pending tasks of features and improvements to be implemented in the software

Input Flow: New feature and improvement requests (coming from users, development team, etc.)
Output Flow: Implementation of features and improvements (developed by the development team)

Delay: The time it takes for the development team to analyze, design, develop, test, and implement the features and improvements in the software.

In this example, it's necessary to maintain a backlog of tasks that can satisfy development demands during the time it takes to analyze, design, develop, test, and implement the features and improvements. This backlog acts as a buffer in case there are delays in the arrival of new feature and improvement requests or in the availability of the development team's resources.

The development team needs to maintain a healthy balance in the backlog to ensure that there's always work available and, at the same time, prevent the backlog from growing to a point where it becomes difficult to manage. To achieve this balance, the team may need to adjust the rate at which it accepts new requests or allocates resources to work on pending tasks.
Software Development Backlog Management