Maple Can Mathematicians Predict the Outcome of a Paintball Battle?

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Mathematicians are modeling the outcome of a paintball battle between academics and technicians using differential equations to predict team performance over time. The model accounts for the teams' shooting rates and their respective probabilities of hitting targets, with technicians having a significantly higher hit probability. Initial conditions set the academics at 100 players and the technicians at 80. A numerical approximation and graph generated in Maple will illustrate the populations' dynamics over a 20-minute battle. The analysis will reveal the likely outcome based on these mathematical predictions.
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The academics and the technicians of a university faculty are planning a paintball battle and the mathematicians are trying to predict their chances of winning with a continuous model. They are representing the numbers in the two teams at any time t as and respectively and have decided that the system to model the encounter should be dA/dT= - k2T and dT/dt= - K1A, where k1 and k2 are positive constants.
The muscles and eyesight of the academics have of course suffered from too much ‘book learning’ over the years, but at least they are aware of their limitations as good soldiers. They estimate that although both sides can fire paintballs at the same rate as each other, denoted by shots per minute, the technicians have a probability of 0.035 of hitting their target with a single paintball shot whilst the academics have only a 0.01 probability of hitting theirs.
Based on the initial conditions A(0)=100 ,T(0)=80, use Maple to produce a numerical approximation andgraph of the populations over a 20 minutes battle then comment on the outcomeafter that time.
 
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