/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 7 Trout, Moose, and Bear lakes are... [FREE SOLUTION] | 91Ó°ÊÓ

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Trout, Moose, and Bear lakes are connected into a chain by a stream that runs into Trout Lake, out of Trout Lake into Moose Lake, out of Moose Lake and into Bear Lake and out of Bear Lake. The volumes of all of the three lakes are the same, and stream flow is constant into and out of all lakes. A load of waste is dumped into Trout Lake. With \(t\) measured in days and concentration measured in \(\mathrm{mg} / \mathrm{l}\), the concentration of wastes in the three lakes is projected to be $$ \begin{array}{ll} \text { Trout Lake: } & C_{\mathrm{T}}(t)=0.01 e^{-0.05 t} \\ \text { Moose Lake: } & C_{\mathrm{M}}(t)=0.005 t e^{-0.05 t} \\ \text { Bear Lake: } & C_{\mathrm{B}}(t)=0.000025 \frac{t^{2}}{2} e^{-0.05 t} \end{array} $$ For each lake, find the time interval, it any, on which the concentration in the lake is increasing.

Short Answer

Expert verified
Moose Lake: increasing on \(0 < t < 20\); Bear Lake: increasing on \(0 < t < 40\); Trout Lake: always decreasing.

Step by step solution

01

Understand the Problem

We need to find the time intervals where the concentration of waste in each lake is increasing. This requires us to find the derivative of each concentration function and determine where these derivatives are positive.
02

Differentiation of Trout Lake Concentration

The function for Trout Lake is given as \( C_{\mathrm{T}}(t) = 0.01 e^{-0.05t} \). The derivative, \( C_{\mathrm{T}}'(t) \), is found using the chain rule: \( C_{\mathrm{T}}'(t) = 0.01 \times (-0.05) e^{-0.05t} = -0.0005 e^{-0.05t} \). This derivative is always negative, so the concentration in Trout Lake is always decreasing.
03

Differentiation of Moose Lake Concentration

For Moose Lake, the function is \( C_{\mathrm{M}}(t) = 0.005 t e^{-0.05t} \). Applying the product rule, we have: \[ C_{\mathrm{M}}'(t) = 0.005 e^{-0.05t} + 0.005 t (-0.05) e^{-0.05t} = 0.005 e^{-0.05t} (1 - 0.05t). \] The concentration increases when \( C_{\mathrm{M}}'(t) > 0 \), i.e., when \( 1 - 0.05t > 0 \). Solving for \( t \), we get \( t < 20 \). Hence, the concentration is increasing for \( 0 < t < 20 \).
04

Differentiation of Bear Lake Concentration

The function for Bear Lake is \( C_{\mathrm{B}}(t) = 0.000025 \frac{t^2}{2} e^{-0.05t} \). Applying the product rule: \[ C_{\mathrm{B}}'(t) = 0.000025 \frac{t^2}{2}(-0.05) e^{-0.05t} + 0.000025 t e^{-0.05t}. \] Simplifying gives \[ C_{\mathrm{B}}'(t) = 0.000025 e^{-0.05t} \left(t - 0.025t^2\right). \] Setting \( C_{\mathrm{B}}'(t) > 0 \) means \( t - 0.025t^2 > 0 \). Solving gives \( t (1 - 0.025t) > 0 \), leading to \( 0 < t < 40 \). Therefore, the concentration increases for \( 0 < t < 40 \).

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Derivatives
Derivatives are a fundamental concept in differential calculus. They represent the rate at which a function is changing at any given point. In the context of lake concentrations, the derivative tells us how the concentration of waste in each lake is changing with respect to time. For example, if the derivative is positive, the concentration is increasing, while a negative derivative indicates a decreasing concentration.
  • To find the derivative of a function, we need to understand different rules and techniques, such as the Chain Rule and Product Rule, which are essential for tackling complex functions.
  • In the given problem, we are interested in identifying when the lake's concentration increases, determined by finding where the derivative is positive.
Understanding derivatives allow us to predict changes and make informed decisions based on mathematical models like the waste concentration in lakes.
Chain Rule
The Chain Rule is a method in calculus used when differentiating composite functions, where one function is inside of another. It allows us to see how a change in one part of the function affects the entire function.
  • In the formula form, if we have a composite function like \( g(h(x)) \), the derivative is \( g'(h(x)) \cdot h'(x) \).
  • In our problem with Trout Lake, the concentration function is \( C_{\mathrm{T}}(t) = 0.01 e^{-0.05t} \), which is a simple exponential function with a constant.
  • Taking its derivative involves using the Chain Rule, where we first differentiate the outer function, the exponential, and then multiply it by the derivative of the inner function, which is \(-0.05t\).
This technique simplifies the process of differentiating more complex expressions by breaking them down into more manageable parts.
Product Rule
The Product Rule is essential when differentiating functions that are products of two or more functions. It states that if you have a function \( u(t) \cdot v(t) \), the derivative is \( u'(t) \cdot v(t) + u(t) \cdot v'(t) \).
  • For Moose Lake, the concentration function \( C_{\mathrm{M}}(t) = 0.005 t e^{-0.05t} \) is a product of \( 0.005t \) and \( e^{-0.05t} \).
  • Using the Product Rule helps us differentiate by taking the derivative of one function while keeping the other constant, then swapping, and adding the results.
  • This ensures that we properly account for all parts of the function, leading to accurate results and allowing us to determine when the concentration in the lake is increasing.
Utilizing the Product Rule simplifies working with complex multipliers, making differentiation quick and simple.
Exponential Functions
Exponential functions are mathematical functions of the form \( a \cdot e^{kt} \), where \( e \) is the base of natural logarithms, approximately equal to 2.718. They are crucial in modeling growth and decay processes.
  • In the context of lake concentrations, each one of our lake functions incorporated an exponential decay \( e^{-0.05t} \), showing how concentration decreases over time.
  • They are particularly important in this scenario as they help model how different factors like the initial waste dump and time affect pollution levels in the lakes.
  • The behavior of exponential functions, specifically their decay or growth rates, can be determined through the sign and value of the exponent, making it easier to predict long-term changes in the system.
Understanding exponential functions provides insights into how systems naturally evolve, exhibiting fast changes initially and stabilizing over time.

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Most popular questions from this chapter

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Exercise 8.3.5 Sickle cell anemia is an inherited blood disease in which the body makes sickle-shaped red blood cells. It is caused by a single mutation from glutamic acid to valine at position 6 in the protein Hemoglobin B. The gene for hemoglobin \(\mathrm{B}\) is on human chromosome \(11 ;\) a single nucleotide change in the codon for the glutamic acid, GAG, to GTG causes the change from glutamic acid to valine. The location of a genetic variation is called a locus and the different genetic values (GAG and GTG) at the location are called alleles. People who have GAG on one copy of chromosome 11 and GTG on the other copy are said to be heterozygous and do not have sickle cell anemia and have elevated resistance to malaria over those who have GAG on both copies of chromosome 11 . Those who have GTG on both copies of chromosome 11 are said to be homozygous and have sickle cell anemia \(-\) the hydrophobic valine allows aggregation of hemoglobin molecules within the blood cell causing a sickle- like deformation that does not move easily through blood vessels. Let \(A\) denote presence of \(\mathrm{GAG}\) and \(a\) denote presence of GTG on chromosome \(11,\) and let \(A A,\) \(A a\) and \(a a\) denote the various presences of those codons on the two chromosomes of a person (note: \(A a=a A) ; A A, A a\) and aa label are the genotypes of the person with respect to this locus. It is necessary to assume non-overlapping generations, meaning that all members of the population are simultaneously born, grow to sexual maturity, mate, leave offspring and die. Let \(P, Q\) and \(R\) denote the frequencies of \(A A, A a\) and aa genotypes in a breeding population and let \(p\) and \(q\) denote the frequencies of the alleles \(A\) and \(a\) among the chromosomes in the same population. The frequencies \(P, Q,\) and \(R\) are referred to as genotype frequencies and \(p\) and \(q\) are referred to as allele frequencies. In a population of size, \(N\), there will be \(2 N\) chromosomes and \(P \times 2 N+Q \times N\) of the chromosomes will be \(A\). In a mating of \(A A\) with \(A a\) adults, the chromosome in the fertilized egg (zygote) obtained from \(A A\) must be \(A\) and the chromosome obtained from \(A a\) will be \(A\) with probability \(1 / 2\) and will be \(a\) with probability \(1 / 2\). Therefore, the zygote will be \(A A\) with probability \(1 / 2\) and will be \(A a\) with probability \(1 / 2\) a. Show that the allele frequencies \(p\) and \(q\) in a breeding population with genotype frequencies \(P, Q\) and \(R\) are given by $$ p=P+\frac{1}{2} Q $$ and $$ q=\frac{1}{2} Q+R $$ b. Assume a closed population (no migration) with random mating and no selection. Complete the table showing probabilities of zygote type in the offspring for the various mating possibilities, the frequencies of the mating possibilities, and the zygote genotype frequencies. Include zeros with the zygote type probabilities but omit the zeros in the zygote genotype frequencies. Random mating assumes that the selection of mating partners is independent of the genotypes of the partners. c. When the table is complete, you should see that $$ \begin{aligned} \Sigma_{A a} &=\frac{1}{2} P Q+P R+\frac{1}{2} Q P+\frac{1}{2} Q^{2}+\frac{1}{2} Q R+R P+\frac{1}{2} Q R \\ &=P Q+2 P R+\frac{1}{2} Q^{2}+Q R=2 P\left(\frac{1}{2} Q+R\right)+Q\left(\frac{1}{2} Q+R\right) \\ &=(2 P+Q)\left(\frac{1}{2} Q+R\right) \quad=\quad 2\left(P+\frac{1}{2} Q\right)\left(\frac{1}{2} Q+R\right) \\ &=2 p q \end{aligned} $$ Show that $$ \Sigma_{A A}=p^{2} \quad \text { and } \quad \Sigma_{a a}=q^{2} $$ This means that under the random mating hypothesis, the zygote genotype frequencies of the offspring population are determined by the allele frequencies of the adults. This is referred to as the Hardy-Weinberg theorem. If the probability of an egg growing to adult and contributing to the next generation of eggs is the same for all eggs, independent of genotype, then the allele frequencies, \(p\) and \(q,\) are constant after the first generation. Random mating does not imply the promiscuity that might be imagined. It means that the selection of mating partner is independent of the genotype of the partner. In the United States, blood type would be a random mating locus; seldom does a United States young person inquire about the blood type of an attractive partner. In Japan, however, this seems to be a big deal, to the point that dating services arranging matches also match blood type. The major histocompatibility complex (MHC) of a young person would seem to be fairly neutral; few people even know their MHC type. It has been demonstrated, however, that young women are repulsed by the smell of men of the same MHC type as their own \(^{4}\). d. Show that in a closed random mating population with no selection, if the frequency of \(A\) in the adults in one generation is \(\hat{p},\) then the frequency of \(A\) in adults in the next generation will also be \(\hat{p}\). e. Suppose that because of malaria, an \(A A\) type egg, either male or female, has probability 0.8 of reaching maturity and mating and because of sickle cell anemia an aa type has only 0.2 probability of mating, but that an \(A a\) type has 1.0 probability of mating. This condition is called selection. Then the distribution of genotypes in the egg and the mating populations will be \(\begin{array}{lccc}\text { Genotype } & A A & A a & a a \\ \text { Egg } & p^{2} & 2 p q & q^{2} \\ \text { Adult } & 0.8 p^{2} / F & 2 p q / F & 0.2 q^{2} / F\end{array}\) $$ \text { where } \quad F=0.8 p^{2}+2 p q+0.2 q^{2} $$ Find the frequency of \(A\) in the adult population. Note: This will also be the frequency of \(A\) in the next egg population. f. We call \(F(p)\) the balance of the population, and because \(p+q=1\) $$ F=F(p)=0.8 p^{2}+2 p(1-p)+0.2(1-p)^{2} $$ You will be asked in Exercise 8.3 .8 to show that when the probability of reproduction depends on the genotype (selection is present), during succeeding generations, allele frequency, \(p,\) moves toward the value of local maximum of \(F\). 1\. Show that \(F(p)=1-0.2 p^{2}-0.8(1-p)^{2}\). 2\. Find the value \(\hat{p}\) of \(p\) that maximizes \(F(p)\).

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