The main dependent variable measured in the model is the membrane potential (millivolts) of two different neurons in a series. You will be able to add excitatory and inhibitory neurotransmitters, and compare how these modulate electrical impulses of the two neurons. Additionally, you will be able to compare the effects of three neurotoxins: Tetrodotoxin, botulinum toxin, and sarin nerve gas. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
Each year, the cost of a college education continues to rise and more and more students must turn to student loans to complete their education. But as graduates leave college to embark on their careers, they face an almost Sisyphean struggle with student debt, forever facing an uphill battle while carrying a heavy burden, only to find they are getting nowhere! Whether you are graduating from college or just entering, we hope this model will enable you to better understand student loans and help plan for your future.
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes. The goal of this simulation is to determine the pattern of inheritance for the white-eyed phenotype. Is yellow body dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
Apterous is an allele that results in a fly without wings. Wild-type variants have normally functioning wings. The goal of this simulation is to determine the pattern of inheritance for the apterous phenotype. Is apterous dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
Simulation allows students to test the transformation principle. Two major goals of the experiment are: 1. Allow users to see that supernatant from heat-killed bacteria can transform the genes of another bacterium. 2. What transforms the inheritance of the bacteria is DNA, not RNA or proteins.
Nonlinear or capacity limited pharmacokinetics can occur whenever a process involved in the absorption, distribution or elimination of a drug becomes saturated. This model demonstrates nonlinear elimination (metabolism) using phenytoin as the model drug. Specifically, it demonstrates how increasing doses of the drug produce disproportionate increases in the plasma concentration. It also demonstrates how the model parameters, Km and Vmax influence of the plasma concentration -time profile.
This model shows the typical plasma concentration profile associated with the administration of several doses of a drug over time. It demonstrates the determinants of the fluctuation in the plasma concentrations, the accumulation of the drug over the course of therapy and the resting steady state plasma concentrations.
Most commonly people take oral doses of a drug over an extended period. This model demonstrates the unique plasma concentration profile associated with this type of drug administration. The model assumes first-order drug absorption with no lag time. Simulations can be carried out to observe how the rate and extent of absorption (bioavailability) affect the profile.
This is the model that is most commonly used to for the time course of drug effects in man. It assumes that the response is driven by the blood or plasma concentrations of the drug. When the model parameters are known, it can be used to predict response at anytime time after any dose.
A very simple, one stock, simulation of campus sexist attitudes toward rape and initimate partner violence. The model was originally developed in 1998 and later translated into Stella. The model has a number of modeling errors, but at the time, proved useful for gaining insight into the dynamics of the system and developing an innovative prevention program.
Explore a consulting firm’s headcount strategy. Understand the relationship between growth rates, promotion times, headcount pyramid ratios, and attrition rates. This model is based on actual work that was done with a very well-known consulting company (here, code-named TWBC, Inc.). The firm's strategic goals were well-articulated, and each made sense when written down in a list on a piece of paper. However, when subjected to the more rigorous, dynamic scrutiny that an iThink modeling effort provides, the goals (as is too often the case) turned out to be in conflict with one another--stimulating actions that worked at cross-purposes. Efforts to achieve one goal drove the firm farther away from achieving the others. The subsequent analysis conducted with the model also pointed the way toward resolving the internal strategic inconsistencies and putting the firm back onto a strategically sound growth path.
Este modelo es un primer intento de utilizar el "Business Canvas" desarrollado por Alexander Osterwalder e Yves Pigneur, para explicar su carácter sistémico mediante la simulación de un modelo de negocio genérico utilizando Stella Architect. El objetivo principal es mostrar el vínculo entre los conceptos del pensamiento sistémico y la práctica del "Systems Dynamics" con el ampliamente difundido "Business Canvas". En la narrativa utilizada para describir la construcción del diagrama "Stock & Flow", se denomina entre parentesis el tipo de componente (Stock, Flow, Converter, o Conector) correspondiente a los principales elementos del modelo de negocio. La simulación permite visualizar la naturaleza sistémica de un modelo de negocio representado mediante el "Business Canvas".
Congratulations! You've just been hired by the major grocery chain The Price Shopper as head of marketing. Your job is to turn around The Price Shopper's dismal sales of laundry detergent. The big-wigs have given you 12 months and a marketing budget of up to $10,000 per month to spend as you please. They'll decide to keep you, or send you to the cleaners based on how much profit you bring in over the year. Do you think you can make the big MONEY?
A country builds its empire by attacking its neighbours and taking over both their land and their people. The larger the empire becomes, the more resources they have available to take further territory by force. However the further they expand, the harder they find it to keep expanding due to the geographical and organisational logistics involved. Additionally the empire finds it harder to maintain social cooperation among its people, its asabiya.
This is our first model in the From Imagination to Simulation series. It is a nod to the Halloween season and investigates a zombie apocalypse! Our fascination with zombies continually grows with the help of movies, TV shows, and books that give a wide range of zombie possibilities. But what are the dynamics behind a zombie epidemic? This model will specifically look at the spread of a zombie outbreak and examine some of the variables that help and hinder the rate of infection. We hope you will continue to see the benefits and versatility of Systems Thinking and enjoy our new series, From Imagination to Simulation! Continue to ponder those out-of-the-ordinary problems. They may seem unrealistic, but perhaps some of their dynamics may resonate with reality. Check out our zombie apocalypse model to see if there is any chance for human survival!
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing factors to the reduction in the butterflies' population sizes. Climate change can alter the timing of lifecycles. When climate change disproportionally affects the timing of life cycles of species in an ecosystem asynchrony within a food web occurs.
Some drugs do not directly produce the measured drug response. Instead they act upstream, and either increase or decrease the amount of the entity that directly mediates the response (response variable). Indirect effect Model I can be used for drugs that inhibit the synthesis of the response variable. An example is warfarin which inhibits the synthesis of clotting factors.
This model is an extension of the Simple Agrarian Society model from Dynamic Systems. The extensions are to add a CO2 cost to the industrialization, an impact of CO2 on global temperature, an impact of global temperature on drought frequency, and impact of drought on food production and an impact of global temperature on polar sea ice.
Change image Submit your own comment on the simulation. Share Comment upgrade hosting plan delete simulation Transit Compartment Model of Drug Response By Sara Rosenbaum Sim URL: https://forio.com/simulate/sarar/transit-compartment-model Sim access:Other authors can download source model Sim plan: Simulate Free Sim stats:This sim has been run 326 times. This simulation was uploaded to Forio Simulate with the isee NetSim software. More information can be found at iseesystems.com. Your Rating: 1 star2 star3 star4 star5 star Average Rating: rating(1) Click here to edit the description A delay in response to a drug can occur when it takes a long time for the drug’s initial effect to be translated into the final response (a long transduction process). The delayed response profile can be captured using a series of transit compartments.
Do you ever feel like work is taking over your life? Burnout is generally characterized as a state of mental and physical exhaustion resulting in low productivity and de-personalization and is most likely caused by prolonged stress that does not dissipate. There are many different aspects that affect both the building and dissipation of burnout. This model focuses on workloads and vacations to see how they contribute to both your level of burnout and productivity. Use this model to ask questions about your workload and any benefits you would receive from taking a vacation. What happens when you suddenly have a bigger workload? What happens when work piles up? Does vacation increase or decrease your stress levels?
This simulation gives the user the ability to specify their own current condition (weight, age, height etc.), choose their exercise regime and eating plans. The simulator then gives a projection for the user's weight for the next year (at a weekly resolution). Please take note that most of the pictures are navigation buttons to different screens, so remember to click on the pictures. I have personally used this simulator to successfully lose more than 20 kg. Hope you find this as valuable as I did. Good luck with your weight journey!
This model shows the typical effect of several anticancer drugs on the number of circulating neutrophils. The drugs destroy neutrophils as they develop in the bone marrow, and its takes several days for their action to affect the circulating neutrophils. The model demonstrates how inter-individual variability in pharmacokinetics and pharmacodynamics can effect the magnitude and duration of this response.
The dynamic model shall explain the rapid diffusion of the lionfish - an invasive species - throughout the Caribbean Sea and the Atlantic Ocean. The interface contains two explanatory models - a simple diffusion model and more realistic convection model - as well as a policy game to manage the regional countermeasures of local decision makers.
This is the second version of the simulation that analyzes the interactions among the six Sustainable Development Goals (SDGs) that are the focus of the Second Annual Multi-stakeholder Forum on Science, Technology, and Innovation for the Sustainable Development Goals (STI Forum). The interface can be used to understand the trade-off due to the complex interplay among the set of six SDGs
This simulation shows the basic dynamics of a hospital emergency room. Patients arrive, are treated and leave. You are able to control the average arrivial rate and average treatment time. This simulation was made using the 3rd party developer API embedded within Stella Architect.
This model is a second extension of the Simple Agrarian model from Dynamic Systems that modifies the simple agrarian society model to include drought, industry produced CO2 and ice sheet dynamics. Primarily this is published as a test of porting form Stella 10.1 and learning how the new Stella Online operates. At some point a user interface and story will be added and the starting conditions calibrated to approximate treating Earth as an industrialized, agrarian society.
Some drugs do not directly produce the measured drug response. Instead they act upstream, and either increase or decrease the amount of the entity that directly mediates the response (response variable). Indirect effect Model IV can be used for drugs that stimulate the degradation of the response variable. As a result they decrease the amount of the response variable.
The Bass Model or Bass Diffusion Model was developed by Frank Bass and it consists of a simple differential equation that describes the process of how new products get adopted in a population. The model presents a rationale of how current adopters and potential adopters of a new product interact.
Some drugs act by binding covalently to their receptors. As a result, the target is destroyed and its function returns only when it has been replaced by newly synthesized product. The target may be a protein, DNA, an enzyme, or a cell at any stage of development. This model has been applied to the action of the proton pump inhibitors, which bind to and destroy the H+,K+-ATPase pumps in the parietal cells of the gastric mucosa. Normal proton secretion is restored only when the pumps are replaced by newly synthesized functioning pumps (i.e., the usual turnover time of the system).
Some drugs do not directly produce the measured drug response. Instead they act upstream, and either increase or decrease the amount of the entity that directly mediates the response (response variable). Indirect effect Model III can be used for drugs that stimulate the production of the response variable. As a result they increase the amount of the response variable.
The model shows the unique plasma concentration-time profile associated with the administration of a drug using multiple short infusions. It demonstrates the influence of the duration of the infusion and allows the user to practice the calculation of a suitable dose and dosing interval to achieve desired peak and trough plasma concentrations of a drug.
The model was developed in a company of the Agri-food sector and considers the distribution link in the collection center of the Tomato Roma product for export to Rio Rico AZ, in 2017 by students of the Technological Institute of Sonora of the Department of Industrial Engineering.
An agrarian population can exceed its normal carrying capacity by the formation of a state that helps improve land productivity. As the population and state grow, it becomes harder for state revenue to stay ahead of expenditure. Eventually the state runs out of money and collapses, with a large drop in population numbers.
Can Energy Prices Really Be Passed on to the Consumer? Energy literally fuels every aspect of today's economy. When energy costs increase, many businesses will increase prices thereby "passing on" the cost to consumers. This story helps to explain some of the broader reaching impacts of such a policy. This model was created by Steve Peterson.
ResiMod was developed by the Association for Water and Rural Development (AWARD), a South African non-profit organisation, with partners. The underlying work was funded by the United States Agency for International Development, under a USAID Southern Africa grant – RFA-674-12-000016 RESilience in the LIMpopo Basin Program (RESILIM). The RESILIM-O part of the programme is implemented by AWARD, in association with project partners.
Use this learning lab to investigate the housing crisis. Play with interest rates as if you are Chairman of the Federal Reserve and see the impact on housing supply and demand. What happens when banks relax mortgage requirements and more people qualify to buy homes?
This model replicates dynamics of crop selection in an agricultural system in which there are two groups of farmers: upstream and downstream. Upstream farmers have immediate access to surface water but downstream farmers can use surface water that is remaining after upstream use. Both groups of farmers grow two types of crops. Crop characteristics as well as other assumptions of the model could be changed by model users. Different scenarios for water availability are also available to the users.
Suppose we have a bucket sitting under a tap with water flowing into it at a constant rate. The bucket has a hole in the bottom, so water leaks out over time. The rate at which water flows out of the hole won't be constant because the water pressure at the bottom depends on the height of the water in the bucket. Therefore, if the bucket is nearly empty, only a trickle will escape, but if the bucket is full, the extra weight of the water will push the water out of the hole much faster. Also, if the hole is bigger, the water will flow out much faster. For this model, we're going to assume that the outflow rate is proportional to the volume of water in the bucket multiplied by the size of the whole: Out_flow = Volume_In_bucket * Size_of_hole
Yo listen up, here's the story About a little guy that lives in a blue world And all day and all night and everything he sees is just blue Like him, inside and outside Blue his house with a blue little window And a blue Corvette And everything is blue for him And himself and everybody around 'Cause he ain't got nobody to listen I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I have a blue house with a blue window Blue is the color of all that I wear Blue are the streets and all the trees are too I have a girlfriend and she is so blue Blue are the people here that walk around Blue like my Corvette, it's in and outside Blue are the words I say and what I think Blue are the feelings that live inside me I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I have a blue house with a blue window Blue is the color of all that I wear Blue are the streets and all the trees are too I have a girlfriend and she is so blue Blue are the people here that walk around Blue like my Corvette, it's in and outside Blue are the words I say and what I think Blue are the feelings that live inside me I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa
In this game you play the part of Dunkin Donuts in an established market of 1,000,000 coffee drinkers. This market is controlled only by Dunkin Donuts and Starbucks, there is no other competition. The market is segmented into 4 sub-groups: Heavy Regular, Heavy Espresso Base, Occasional Regular Occasional Espresso Base. The occasional coffee drinkers normally order a pastry (donut, cake, etc.) with their coffee more often than the the heavy coffee drinkers, but on an individual by individual basis the heavy coffee drinkers are buying more donuts each month than the occasional coffee drinkers. For this game you are concerned with selling 3 products: Regular Coffee, Espresso Base Coffee, Pastry (donuts, cakes, etc.) For each product you sell you have control over the following decisions: Process Improvement Spending, Taste Improvement Spending, Marketing, Price. Finally you can then also choose to open new stores or close existing stores.
This simple model explores the demand dynamics for a state's energy usage. For three sectors (residential, industrial, and agricultural) you can adjust the size of initial user base, the growth rate for the number of users, and the rate for the change in demand per user.
Suppose we have a bucket sitting under a tap, with water flowing into it at a constant rate. The bucket has a hole in the bottom, so water leaks out over time. The rate at which water flows out of the hole will not be constant because the water pressure at the bottom depends on the height of the water in the bucket. Therefore if the bucket is full, the extra weight of the water will push the water out of the hole faster. Also if the hole is bigger the water will flow faster. For this model, we're going to assume that the outflow rate is proportional to the volume of the water in the bucket multiplied by the size of the hole.
The purpose of this model is to (1) demonstrate a way to represent human development that includes individual resources, social networks, and spatial relationships within a single model of a formal feedback theory of development, (2) provide an approach to theory development that begins with a simple model and gradually includes more complex facets of social reality (e.g., social networks, location), and (3) illustrate its application to formally testing and comparing a theory over a wider range of assumptions that can inform the design of data collection and analysis to more accurately reflect the dynamics of human development and outcomes. The approach has a wide range of possible applications in theory development and community intervention design, research, and evaluation. Examples include school-based and community based positive youth development interventions, drug use/addiction and treatment in rural settings, community responses to domestic violence, neighborhood effects and interventions, homelessness, supports for ex-offenders released from prison or jail, and health inequities. Version 1.0 focuses on mainly working out a simple example of interactions between social networks and spatial relationships. The model (right) represents a formal theory of how people will move to be close to their nearest friend. Since friends are determined by a social network where people have different sets of friends, and people are in different locations, movement will depend on an interaction between each individual’s social network, the location of their friends, the distance to their friends, and identifying their nearest friend and comparing one’s present location to the location of one’s nearest friend. The model implements this with a random social network for 100 individuals randomly distributed in 100m by 100m coordinate space.
About 5 million tyres are disposed of every year in New Zealand and 70 per cent end up in a landfill. These tyres occupy a considerable amount of space. Often unaccounted for after disposal, tyre dumps eventually attract rats and other contaminants which may disrupt nearby environmental ecosystems in a way such as soil pollution. The standard is such that there is a difficulty with regards to recycling tyres due to the lack of an efficient system, tools, mechanics or even a commercial product that makes use of used tyres. As a result, tyres are quickly forgotten after disposed. This is an important problem in New Zealand with disastrous longer term environmental effects if not dealt with in the next few years.
With this model I model the physical locations of all individuals in real space. (X,Y location). Individuals move randomly each day so that they mix. Based on an individuals location relative to each other individuals there is a chance for a person to communicate the infection to another person. To determine if the infection is communicated we draw a random number. If the number is equal to or less then the chance of infection if the other person is the carrier then the person P contracts the infection and can then spread it through the population. What is superior about this model is that we can now EASILY model the attributes of any individuals as a stock arrayed by Individuals and the interaction of people with others as arrayed variables by Individual, Individual. For instance if we wanted to model the time that an individual has had a disease we can do that by creating a stock called time_infected and have an inflow of 1 for each day that an individual is in the infected state.
it is a model for the adoption of a new technology, Given P as the potential adopters of the new technology, and A as the actual adopters, the adoption of new technology takes place due to two process - 1) word of mouth and 2) advertising and any other external influence. the adoption rate AR from potential adopters is AR= WoM + AfA
Tolerance may be defined as a process that results in a reduction in the response to a specific drug concentration following repeated drug exposure. Tolerance could occur if an endogenous compound that plays an essential role in the response chain becomes depleted during response. This model assumes the drug stimulates the production of a response variable which becomes then becomes depleted.
Dairy farmers in Matiguás, Nicaragua face feed system constraints that reduce their competitiveness. Conventional value chain analysis methods are unsuited to prioritize upgrading options. System dynamics modeling of the Matiguás dairy value chain was therefore used to quantify and analyse policy impacts. The model was constructed and tested with stakeholders in the Matiguás dairy value chain through group model building.
In response to financial issues, the administration at an undergraduate tuition-dependent university pushed for growth in student enrollment. The faculty, who argued that the quality of education had been declining, resisted the expansion. More students also affected the use of the university’s infrastructure. By actively engaging key stakeholders, we developed a simple system dynamics model of university expansion.
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor neuron and the muscle fiber it innervates. You will be able to add excitatory and inhibitory neurotransmitters, and compare how neurotransmitters modulate the electrical impulses of the motor neuron and the muscle fiber. Additionally, you will be able to compare the effects of four neurotoxins: Tetrodotoxin, botulinum toxin, sarin nerve gas, and VX. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
Keystone species are defined as a plant or animal that plays a unique role in the way the ecosystem functions. But what would happen if that species were removed? What ripple effects would be caused by the absence of this species? We can examine these questions by looking at the wolf population in Yellowstone National Park. Wolves once flourished in Yellowstone and its surrounding areas. However, soon after the area was settled, misperceptions caused by fear and hatred fueled a large extermination effort of the wolves. For nearly 70 years, wolves were absent from Yellowstone. During this time, the ecosystem changed and diminished until scientists realized the value of the wolves and reintroduced them to Yellowstone. This model, built in iThink, uses storytelling to understand the dynamics of this keystone species. What animals were affected by their presence or absence. See how wolves play a part in not only population control of their prey but other animals and even plants far down the trophic levels.
Students use a simple simulation to explore "what if" questions relating to characters. They can change how characters behave to consider whether a story might have emerged differently. Note that students do not need to read the play, The Tragedy of Romeo and Juliet in order to explore the simulation.
Many drugs are removed from the body by metabolism in the liver. A drug's hepatic clearance is a measure of the liver's ability to metabolize a drug. This simulation demonstrates the characteristics of high extraction (nonrestrictive clearance, low extraction (restrictive clearance and intermediate clearance.
This simulation is based on the SCREI model, simulating early recruitment of the Barents Sea cod stock under ocean warming and acidification. The model is based on experimentally quantified data and calibrated to empirical cod egg production, 0-group abundance and ecological data. It allows the exploration of different climate change driver trajectories and adaptaion scenarios.
Experience the dynamics of making a business shift from traditional to e-commerce. Simulate different scenarios for how you’ll allocate spending on marketing versus infrastructure. You will see one of the more common dynamics in making a business shift, what Systems Thinkers refer to as the "worse before better" dynamic. If initial investments are made in the infrastructure quality rather than in marketing, total customers will actually fall for awhile. But if increasing amounts are spent on marketing (once the infrastructure is in place) then total customers will begin to explode. And the transition becomes successful!
Simulation of a territory over a 10-year time horizon (inhabitants, students, households, journeys,...) according to different housing policies, job scenarios, taking into account the territory attractiveness.
A look at disaster relief under uncertain local government scenarios. It looks at how long it might take to establish clean water thru flying in bottled water and constructing wells. There is also the impact on spread of disease and survival due to lack of water. Created by Mark Heffernan and George McDonnel
An equilibrium model of groundwater in the North Fork watershed of the Shenandoah Valley in western Virginia. The model captures annual rainfall and consumption of ground water by livestock and humans. This project was undertaken as part of ISAT 391 in the Spring of 2018 for Dr. Nash, Dr. Handly and Dr. MacDonald
Model Mysteries Chapter 1: Growing, Growing, Gone Model 2: Zombie Chickens
The flows of light energy toward and away from the Earth. Energy comes in from sunlight, but some of its reflected back away from Earth, depending on the planet's albedo. The rest is absorbed by the Earth's surface and stored there. The Earth's surface gives infrared blackbody radiation according to the Stefan-Boltzmann law. A balance is reached when the inflowing solar energy exactly equals the outflowing infrared energy.
Some drugs do not directly produce the measured drug response. Instead they act upstream, and either increase or decrease the amount of the entity that directly mediates the response (response variable). Indirect effect Model 2 can be used for drugs that inhibit the degradation of the response variable. As a result they increase the amount of the response variable.
This simulation shows the location and functioning of the major clinically important drug transporters in the : gastrointestinal membrane; renal tubular membrane; and the membranes of the hepatocyte. Simulations demonstrate their functioning after oral and intravenous doses of a drug substrate
The model is suppose to help, learn and investigate the flow of carbon between the atmosphere and land plants and soils through photosynthesis and respiration. The key questions we want to understand are: ● How does the plant fertilization feedback work? ● Are plants taking up a significant amount of the carbon humans are emitting? ● Can we solve the climate change problem by planting trees to take up our CO2?
Model Mysteries Chapter 2: Energy Drink Mania Model 1: Basic Model
Pinocho Cuando Pinocho miente su nariz se alarga 1 centímetro. Y cada vez que pinocho hace una obra buena se le disminuye 5 centímetros. Cada día pinocho miente unas 8 veces y hace una obra buena. Pregunta: Si el lunes en la mañana la nariz de pinocho mide 4cm. ¿Qué tan larga será el sábado en la noche?
The behavior over time of a population limited by density-dependent factors is called logistic growth. You will be simulating a model of logistic population growth. You'll be able to change factors that address how fast an animal population grows, how long individuals in the population live on average, and how much area the population has available. See if you can vary the shape of the logistic curve, or create something different.
Model Mysteries Chapter 1: Growing, Growing, Gone Model 3: Zombie Chickens Dare
Model Mysteries Chapter 4: Spreading Like Crazy Base model
Second iteration of price war multiplayer game for ISDC 2017. Two players are required a third is optional. Each player is competing to control the market. They sell perfect substitutes with equal production costs. Your only choice is what price you sell your product at
This model represents dynamics of crop selection decisions by two groups of farmers: upstream and downstream. These groups of farmers select crops based on several factors including market signals, crop characteristics, and quantity and quality of available irrigation water.