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Subsections
The purpose of this lab is to use Maple to study applications of
exponential and logarithmic functions. These are used to model many
types of growth and decay, for example bacterial growth and
radiaoctive decay. This lab also describes applications of exponential
and logarithmic functions for heating and cooling and to medicine dosage
The simple model for growth is
exponential growth, where
it is assumed that
is proportional to
. That is,
Separating the variables and integrating (see section 4.4 of the text),
we have
so that
In the case of exponential growth, we can drop the absolute value
signs around
, because
will always be a positive quantity.
Solving for
, we obtain
which we may write in the form
, where
is an
arbitrary positive constant.
In a sample of a radioactive material, the
rate at which atoms decay is proportional to the amount of material present.
That is,
where
is a constant. This is the same equation as in exponential growth,
except that
replaces
. The solution is
where
is a positive constant. Physically,
is the amount of
material present at
.
Radioactivity is often expressed in terms of an element's half-life.
For example, the half-life of carbon-14 is 5730 years. This statement means
that for any given sample of
, after 5730 years, half of it
will have undergone decay.
So, if the half-life is of an element Z is
years, it must be
that
, so that
and
.
What is usually called Newton's law of cooling is a simple model for
the change in temperature of an object that is in contact with an
environment at a different temperature. It says that the rate of
change of the temperature of an object is proportional to the
difference between the object's temperature and the temperature of the
environment. Mathematically, this can be expressed as the differential
equation
where
is the constant of proportionality and
is
the temperature of the environment. Using a technique called
separation of variables it isn't hard to derive the solution
where
is the temperature of the object at
.
If a drug is administered to a patient intravenously, the concentration
jumps to its highest level almost immediately. The concentration
subsequently decays exponentially. If we use
to represent the concentration at time t, and
to represent the
concentration just after the dose is administered then our exponential
decay model would be given by
A problem facing physicians is the fact that for most drugs, there is
a concentration,
, below which the drug is ineffective and a
concentration,
, above which the drug is dangerous. Thus the
physician would like the have the concentration
satisfy
This means that the initial dose must not produce a concentration
larger than
and that another dose will have to be administered
before the concentration reaches
.
The main functions you need are the natural exponential and
natural logarithm. The Maple commands for these functions are
exp and ln. Here are a few examples.
> f := x -> exp(-2*x);
> simplify(ln(3)+ln(9));
> ln(exp(x));
> simplify(ln(exp(x)),assume=real);
The assume=real
is needed in the command above, because Maple
usually works with complex variables.
Sometimes you need to use experimental data to determine the value of
constants in models. For example, suppose that for a particular drug,
the following data
were obtained. Just after the drug is injected, the concentration is
1.5 mg/ml (milligrams per milliliter). After four hours the
concentration has dropped to 0.25 mg/ml. From this data we can
determine values of
and
as follows. The value of
is the
initial concentration, so we have
To find the value of
we need to solve the equation
which we get by plugging in
and using the data
. Maple commands for solving for
and defining and
plotting the function
are shown below.
> k1 := solve(0.25=1.5*exp(-4*k),k);
> C1 := t -> 1.5*exp(-k1*t);
> plot(C1(t),t=0..6);
- A thermometer is taken from a room at
to the outdoors where the temperature is
. Using Newton's law of cooling, approximate the reading on
the thermometer after 3 minutes,
if the reading drops to
after 1
minute.
- Suppose that the population of a certain bacteria can be modeled
by an exponential function. In a particular experiment, the number of
bacteria was
at
. Four hours later, the number of
bacteria was
. Find the value of the growth constant
and
use it to predict the number of bacteria that would have been present
after
hours.
- Suppose that for a certain drug, the following results were
obtained. Immediately after the drug was administered, the
concentration was 5.3 mg/ml. Six hours later, the concentration had
dropped to 1.85 mg/ml. Determine the value of
for this drug.
- Suppose that for the drug in the previous exercise, the maximum
safe level is
and the minimum effective level is
. What is the maximum possible time between doses
for this drug?
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Up: lab_template
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William W. Farr
2002-02-08