Jon Darkow's Profile
Number of items: 124
Date joined: Apr 05 2016
Website: www.jondarkow.com
Jon Darkow has taught a variety of science and science education courses at the high school and coll ...Read more Jon Darkow has taught a variety of science and science education courses at the high school and college level for the past 20 years. Currently, Jon teaches AP Physics, College Anatomy and Physiology I and II, and high school Biology at Marion L Steele High School in Amherst, Ohio. Jon is most interested in teaching scientific reasoning and systems thinking using system dynamics modeling.
Jon Darkow's Work
#1
Oxytocin and Child Birth
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⋮ 257008 runs
#2
Cellular Respiration Inquiry
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computa
... Read more
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computations.
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⋮ 123982 runs
metabolism
respriation
ATP
biology
#3
Position, Velocity, and Acceleration Simulation
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⋮ 4158 runs
Science
#4
Beta Cell Simulation - Split story
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⋮ 86572 runs
#5
Evolution of Antibiotic Resistance Simulation
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of
... Read more
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of bacteria. The main purpose of the model is to show that new adaptations are not caused by an environmental factor, like antibiotics. Rather, new adaptations are the selection of available variations. In this model you can increase variations by increasing the UV dose. The UV dose increases the mutation rate with a Monte Carlo function.
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⋮ 207408 runs
Biology
Science
Ecology
Education
#6
Phosphorus in Lake: Changes to Flows in a Dynamic System
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a
... Read more
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a lake), an inflow (added P/day), and an outflow (removed P/day).
The flows can either be constant throughout the simulation run, or dynamic (changing throughout the simulation run.)
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⋮ 3641 runs
flows
dynamic
phosphorus
#7
Diffusion of a Spherical Cell
Why are cells small? This model allows users to see how the size of a sphere affects the rate of dif
... Read more
Why are cells small? This model allows users to see how the size of a sphere affects the rate of diffusion.
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⋮ 155018 runs
diffusion
surface area
volume
radius
#8
Tesing Unknown Enzymes
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⋮ 296575 runs
enzymes
#9
Slider Bets and Metacognition
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⋮ 89 runs
Education
#10
Stock, Inflow, and Outflow with Atrazine
Simple stock and flow diagram. Flows linear.
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⋮ 98 runs
stock
flow
atrazine
#11
Neurophysiology and Information Processing 2022
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⋮ 21598 runs
Biology
information processing
neuron
neurotransmission
neurophysiology
#12
Extinction
sim
#13
Evolving Bits N=40
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⋮ 2842 runs
evolution
bits
receptor
substrate
#14
Genotyping with Electrophoresis
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⋮ 46026 runs
biology
inheritance
DNA
restriction enzyme
#15
Cellular Respiration Accounting Model
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in i
... Read more
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in its chemical bonds is transfered.
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⋮ 794848 runs
cellular respiration
aerobic respiration
ATP
biology
#16
Chaos Theory: Strange Attractor
Manipulate the main variables of the Lorenz equation.
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⋮ 2591 runs
chaos theory
Lorenz
attractor
manifold
#17
Photosynthesis Model
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⋮ 2878846 runs
#18
Water Potential and Osmosis
Factors that affect the flow across a semi-permeable membrane.
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⋮ 450252 runs
#19
Lactase Enzyme Simulation with Data Analysis
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⋮ 13676224 runs
#20
ATP Hydrolysis
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⋮ 8067 runs
Science
ATP
Free Energy
Entropy
#21
Photosynthesis Simulation with Variance
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⋮ 209089 runs
#22
Photosynthesis Simulation - Simplified
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⋮ 121 runs
Environment
Biology
Science
Ecology
Education
#23
Evolving Bits
Diversity and selection for the basis of evolution. This simple model tries to illustrate these conc
... Read more
Diversity and selection for the basis of evolution. This simple model tries to illustrate these concepts.
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⋮ 1689 runs
Diversity
Selection
Evolution
Receptor
Antigen
#24
Bathtub Dynamics
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model
... Read more
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model 2 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub.
Model 3 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub. However, Model 3 uses Torricelli's law to calculate the flow rate based on physical principles.
This law was formulated by Evangelista Torricelli, an Italian physicist, in the 17th century. It's an important principle in fluid dynamics and is closely related to Bernoulli's principle. Torricelli's law states that the speed (velocity) of efflux of a fluid through a hole under the force of gravity is proportional to the square root of the vertical distance (height) between the fluid surface and the center of the hole. The formula is given by efflux velocity = 2*g*ℎ, where:
g is the acceleration due to gravity (approximately 9.81 m/s² on Earth).
ℎ is the height of the fluid column above the hole.
The idea is that the fluid's potential energy due to its height is converted into kinetic energy as it falls. The higher the fluid, the greater its potential energy and thus the greater the speed at which it exits the hole. This principle is used in various applications, such as determining the flow rate of liquids from tanks, in hydrodynamics studies, and even in everyday situations like draining a bathtub. The law assumes an ideal fluid (incompressible and non-viscous) and neglects factors like air resistance and the viscosity of the fluid. It also assumes that the size of the hole is small compared to the depth of the fluid.
The flow rate (the volume of fluid flowing per unit time) can be calculated by multiplying the cross-sectional area of the hole (A) by the velocity of the fluid (v), leading to the formula
Q=A*v, where Q is the flow rate.
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⋮ 2393 runs
Environment
Science
Education
Bathtub
hydrodynamics
#25
Carbon in the Atmosphere - Graphic Input constant
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⋮ 28 runs
#26
Illusions and Assumptions
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⋮ 1056 runs
Biology
Science
#27
Thyroid Hormone - Negative Feedback
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⋮ 84011 runs
negative feedback
thyroid hormone
metabolism
biology
#28
Predator Prey Model - Mobile
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⋮ 176 runs
Biology
#29
Ball Bet Code Generators for Answer Keys
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⋮ 846 runs
Education
#30
Gravitational Attraction of Three Bodies
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⋮ 552 runs
Science
Education
Forces
Gravitation
Physics
#31
Mechanical Energy and Kinematics
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⋮ 502 runs
Science
Physics
Energy
Acceleration
Velocity
#32
Grant Finches Mobile
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⋮ 15 runs
#33
Student Model (X. Hicks and J. Margraf) - HIV
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⋮ 84 runs
#34
Oxytocin-P
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⋮ 38 runs
Biology
#35
Ball Bet 3.0.2
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⋮ 2 runs
#36
Exponential Growth
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⋮ 14832 runs
Biology
Ecology
#37
Circadian Clock in the Mouse
Transcriptional Translational Feedback Loop in the Mouse
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⋮ 31880 runs
Mouse
Circadian
Clock
#38
Beta Cell Membrane Transport - Insulin Regulation
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⋮ 275 runs
Insulin
Glucose
Beta Cell
#39
Population dynamics of white footed mouse
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⋮ 1681961 runs
#40
Understanding Linear Motion
Understand linear motion with automated feedback.
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⋮ 1418 runs
Science
Education
physics
motion
velocity
#41
Apterous Genetics
Apterous is an allele that results in a fly without wings. Wild-type variants have normally function
... Read more
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?
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⋮ 312984 runs
Genetics
#42
Growth Factors, Cyclins, and Cancer
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (gro
... Read more
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (growth factors), to stimulate the cell cycle feedback loops.
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⋮ 321237 runs
growth factors
cyclins
cell cycle
cancer
#43
Cardiovascular Model
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⋮ 31358 runs
#44
System Dynamics of Carbon Budget
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems d
... Read more
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems dynamics based on John Sternman (MIT) and Krytyna Stave (University of Nebraska)
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⋮ 17142 runs
system dynamics
carbon
climate
#45
Evolution of LAP Allele in Mussels
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⋮ 88376 runs
Evolution
Natural Selection
Cline
#46
Cell Cycle - Simpler 2020
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⋮ 63031 runs
Biology
Science
Education
#47
Cell Cycle Simulation
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⋮ 2559 runs
Biology
#48
Soybean and Aphid Dynamics
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⋮ 148 runs
Environment
Biology
Science
Economics
Ecology
#49
Fruit Fly with variable sample size
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⋮ 43 runs
#50
Tryptophan Operon: A repressible system
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⋮ 90109 runs
#51
Steady State in Freshwater Ecosystems
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⋮ 37901 runs
#52
HPV with Influenza A Humoral Immunity
Immune response of HPV
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⋮ 29065 runs
HPV
antibodies
biology
Immunity
#53
Body Temperature Regulation with Scatter Plot
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⋮ 226 runs
Biology
Science
Education
Health
#54
HPV and Adaptive Immune Response
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⋮ 12903 runs
HPV
Antibodies
feedback loops
vaccine
#55
Transformation Simulation
Simulation allows students to test the transformation principle. Two major goals of the experiment a
... Read more
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.
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⋮ 137289 runs
transformation
DNA
biology
#56
Uniform Circular Motion
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⋮ 940 runs
Science
Education
Circular
Motion
Physics
#57
Pattern with recessive single band
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⋮ 95944 runs
genetics
#58
Lactose Operon: An Inducible System
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteri
... Read more
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteria. Lactose induces the system by inhibiting and inhibitor.
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⋮ 147396 runs
Inhibition
negative feedback
biology
lactose
operon
#59
Ball Bet for Metacognition - Random
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⋮ 105 runs
Education
#60
GLUT and Insulin
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⋮ 20 runs
#61
Logistic Growth Model and the Butterfly Effect
Model allows users to test the starting population size (N), the carrying capacity of the populatio
... Read more
Model allows users to test the starting population size (N), the carrying capacity of the population (K), and the intrinsic rate of growth (r max).
Iterations are discrete, not continuous.
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⋮ 6494 runs
logistic growth
carrying capacity
#62
Evolution: Grants Finches
Models the effects on population sizes of ground finches with different beak sizes in response to di
... Read more
Models the effects on population sizes of ground finches with different beak sizes in response to different amounts of annual precipitation.
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⋮ 12747 runs
evolution
biology
natural selection
#63
Limiting Nutrients in Aquatic Ecosystems
Experiment with a variety of nutrients that are limited by different degrees in four different ecosy
... Read more
Experiment with a variety of nutrients that are limited by different degrees in four different ecosystems.
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⋮ 137879 runs
limiting nutrients
ecosystem
biology
logistic growth
#64
The dynamics of photosynthesis - variable sample size
The dynamics of photosynthesis - variable sample size
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⋮ 94849 runs
photosynthesis
sample size
biology
#65
Evolution and Natural Selection
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⋮ 378835 runs
#66
Transformation Experiment with Controls
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griff
... Read more
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griffith.
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⋮ 31090 runs
Biology
Science
Education
transformation
DNA
#67
Lotka-Volterra Predator-Prey Model
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by t
... Read more
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by the interconnections of a negative feedback loop governs much of life.
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⋮ 334059 runs
negative feedback loop
Lotka-Volterra
homeostasis
predator-prey
#68
SIR COVID-19 Coronavirus Simulation
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⋮ 19930 runs
Environment
Biology
Science
Education
SIR
#69
Catastrophic Regime Change in Aquatic Ecosystems
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⋮ 125047 runs
Ecology
#70
Photosynthesis with Variable Sample Sizes
Sample sizes of Photosynthesis stocks in an array
#71
Simple Genetics
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⋮ 136515 runs
#72
Tick Tock: The Biological Clock and Circadian Rhythm
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circa
... Read more
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circadian rhythm.
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⋮ 1128 runs
circadian
clock
feedback loop
#73
Fruit Fly Choice
Simulation to model random behavior in a fruit fly choice chamber
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⋮ 1027 runs
randomness
random
#74
Recombination and Gene Linkage
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⋮ 155407 runs
#75
Evolution with Heterozygous Advantage
Evolution of Populations: Genetic Drift, Natural Selection, and Mutations
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⋮ 7697 runs
evolution
natural selection
genetic drift
#76
White-Eyed Genetics
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes.
The
... Read more
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?
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⋮ 195659 runs
Genetics
#77
Lac Operon with Monod Bump
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⋮ 209163 runs
Lac Operon
Gene Regulation
mRNA
#78
Extinction Vortex
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⋮ 71775 runs
#79
Soybean and Aphid Population Dynamics
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⋮ 3256 runs
Biology
Science
#80
Guppy Evolution
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⋮ 191206 runs
evolution
biology
genes
#81
Phenology of the Karner Blue Butterfly
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing fac
... Read more
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.
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⋮ 13509 runs
asynchrony
timing
phenology
climate change
butterfly
#82
Neurophysiology and Neurotoxicity
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor
... Read more
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.
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⋮ 46458 runs
Neurophysiology
toxins
sarin
VX
TTX
#83
Enzyme Diversity
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⋮ 512684 runs
enzyme
biology
substrate
pepsin
indicators
#84
Lactase with Variable Sample Sizes
Arrayed Lactase Model
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⋮ 934164 runs
Lactase
array
sample size
biology
#85
Carbon Cycle Simulation
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can
... Read more
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can manipulate with graphical inputs the changes in fossil fuel emissions, land-use, and ocean sinks.
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⋮ 11951 runs
Environment
Biology
Science
Ecology
Education
#86
Enzyme Diversity: Enzymes, Products, and Substrates
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⋮ 1229328 runs
enzymes
substrates
products
DNA
trypsin
#87
Information Processing and Neurophysiology Model
The main dependent variable measured in the model is the membrane potential (millivolts) of two diff
... Read more
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.
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⋮ 375624 runs
infromation processing
neurophysiology
biology
#88
Pendulum Model
sim
⋮ 50 runs
Science
Education
Physics
Simple Harmonic Motion
Pendulum
#89
#90
Comparing COVID-19 with xxx
This model was copied from Jon Darkow:
#91
SIR Model for Coronavirus (COVID-19)
#92
#93
#94
#95
#96
#97
#98
#99
#100
#101
#102
#103
#104
Projectile Motion Physics
#105
#106
Modeling Constant Acceleration
#107
Endocrine System Dynamics
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge fr
... Read more
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge from underproduction and excess production of the hormone.
This model was developed for a high school Anatomy and Physiology class.
#108
Two Variations - Population Growth
#109
#110
SIR Model for Coronavirus (COVID-19) - with social distancing
This model was copied from Jon Darkow:
#111
#112
#113
Mechanical Energy Model
#114
Exponential Growth in Population - AF
Chapter 2: Modeling the Environment
#115
SIR Model for COVID-19
This model was copied from Jon Darkow:
This model was copied from Jon Darkow:
#116
#117
#118
#119
#120
#121
Differential Reproduction, Natural Selection Model
This is the fourth model in a sequence of models to show the logic of natural selection, formalized
... Read more
This is the fourth model in a sequence of models to show the logic of natural selection, formalized by Earnst Mayr.
Mayr E. The growth of biological thought. Cambridge: Harvard University Press; 1982.
#122
#123
Uploading a Bundle from Zip
Instead of creating bundles, categories, and assemblies one by one, you can upload a single zip file that contains all of your bundle's content. To create your zipped bundle, make a folder with your bundle's name and add subfolders with your categories' names. The folder tree should have the same structure that you want the categories to have in your bundle. Place your assembly .stmx files in the appropriate category folders, then zip your bundle folder and upload it using the Upload Bundle from Zip link above.
Assemblies, Bundles, and Categories
Assemblies are self contained models that demonstrate common ways to connect together building blocks and that can be used as parts of other models. This is analogous to using prefabricated wall and roof pieces to construct a house.
Bundles are groups of assemblies with a common use or theme. For example, a Health Care bundle might contain a variety of assemblies that aid in creating health care models. When you download assemblies from the isee Exchange™, you download an entire bundle, rather than individual assemblies.
Categories are subgroups of assemblies within a bundle. For example, a Health Care bundle might contain a Funding category for assemblies related to the management of hospital funds. All assemblies must be assigned to a category—they cannot be assigned to the root of a bundle.
Assemblies, bundles, and categories can be created and uploaded to the isee Exchange™ via the options on the Manage My Assemblies page. To learn more, visit our help pages, or take our assemblies tutorial.
Sim App (Sim)
An interface that allows users to interact with a model.
Sim apps allow users to interact with a model using buttons, sliders, knobs, tables, graphs, and storytelling. These interactions help users understand how parts of a system interact.
Interfaces are created by model authors in the Stella desktop software and can be uploaded to the isee Exchange™.
Model
A diagram that represents how elements in a system influence one another.
Models are mathematical representations of how elements in a system are connected and interact (e.g., ecosystems, organizations, supply chains). When running models on the isee Exchange™, results can be viewed in output devices like graphs and tables.
Models appear in the isee Exchange™ directory when authors upload them from the Stella® desktop software or create them with Stella Online™.
Causal Loop Diagram (CLD)
A map that represents the feedback structure of a system.
CLDs are high-level maps that represents the feedback structure of a system and easily communicate the essence of a model. They appear in the isee Exchange™ when authors upload them from the Stella desktop software or create them with Stella Online™.