Compute each sum below. Give exact values, not decimal approximations. If the sum does not exist, click on "No sum". (-4) + (-4)²+(-4)³ +... = k Σ (3) - = 5 k=1

To find the linear approximation of √101, we need to use the formula for linear approximation, which is:

f(x) ≈ f(a) + f'(a)(x-a)

where a is the point about which we're making our approximation.

f(x) = √x is the function we're approximating.

f(a) = f(100)

since we're approximating around 100 (which is close to 101).

f'(x) = 1/2√x is the derivative of √x,

so

f'(a) = 1/2√100

= 1/20

Plugging in these values, we get:

f(101) ≈ f(100) + f'(100)(101-100)

= √100 + 1/20

(1)= 10 + 0.05

= 10.05

This is the approximate value we're looking for.

Now we need to find the error bound.

To do this, we use the formula:

|f(x)-L(x)| ≤ K|x-a|

where L(x) is our linear approximation and K is the maximum value of |f''(x)| for x between a and x.

Since f''(x) = -1/4x^3/2, we know that f''(x) is decreasing as x increases.

Therefore, the maximum value of |f''(x)| occurs at the left endpoint of our interval, which is 100.

So:

|f(x)-L(x)| ≤ K|x-a|

= [tex]|f''(a)/2(x-a)^2|[/tex]

≤ [tex]|-1/4(100)^3/2 / 2(101-100)^2|[/tex]

≤ 1/8000

≈ 0.000125

So the error is at most 0.000125.

Therefore, our approximation of √101 is between 10.049875 and 10.050125, which is written as √101 € (10.04975, 10.05025).

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a. The particular solution to the nonhomogeneous differential equation [tex]y" + 4y' + 5y = -5x + e^{(-x)[/tex] is [tex]y_p = -x[/tex]. b. The most general solution to the associated homogeneous differential equation y" + 4y' + 5y = 0 is [tex]y_h = c1e^{(-2x)}cos(x) + c2e^{(-2x)}sin(x[/tex]), where c1 and c2 are arbitrary constants. c. The most general solution to the original nonhomogeneous differential equation [tex]y" + 4y' + 5y = -5x + e^{(-x)[/tex] is [tex]y = -x + c1e^{(-2x)}cos(x) + c2e^{(-2x)}sin(x)[/tex], where C1 and C2 are arbitrary constants.

To find the particular solution to the nonhomogeneous differential equation [tex]y" + 4y' + 5y = -5x + e^{(-x)[/tex], we can use the method of undetermined coefficients.

a. Particular solution:

We assume the particular solution takes the form of [tex]y_p = Ax + Be^{(-x)[/tex], where A and B are constants to be determined.

Taking the derivatives of y_p:

[tex]y'_p = A - Be^{(-x)}\\y"_p = Be^{(-x)[/tex]

Substituting these derivatives into the differential equation, we have:

[tex]Be^{(-x)} + 4(A - Be^{(-x)}) + 5(Ax + Be^{(-x)}) = -5x + e^{(-x)}[/tex]

To match the coefficients on both sides, we equate the corresponding coefficients:

A + 5B = -5

5A - 3B = 1

Solving these equations, we find A = -1 and B = 0.

Therefore, the particular solution is y_p = -x.

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The rate of infection for the disease in the given town is 106.54 (approx) infected people per day. The growth of a contagious disease in a town with logistic growth constant of k = 0.000038 and 111 infected people can be determined by using the formula for logistic growth model.

This model helps us to find the growth of the population in a closed system (such as in a town or a country) that is limited by resources.

What is the formula for logistic growth model?

The formula for logistic growth model is given by:

P(t) = K / [1 + A * exp(-r * t)]

Where,

P(t) = population after time t,

K = the carrying capacity of the environment,

A = initial population as a fraction of the carrying capacity,

r = the rate of population growth,

t = time

Let's put the given values in the above equation to calculate the rate of infection:

Here, K = 3,254, A = 111/3,254 = 0.0341, r = 0.000038 and t = 1.

P(1) = (3254) / [1 + (3254/111) * exp(-0.000038 * 1)]

P(1) = (3254) / [1 + (29.332) * (0.999962)]

P(1) = (3254) / [1 + 29.33 * 0.999962]

P(1) = 3254 / 30.55

P(1) = 106.54

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The value of (f ∘ g)(-2) is 1. The value of (g ∘ f)(-2) is -8. To evaluate the composite functions (f ∘ g)(-2) and (g ∘ f)(-2), we substitute the given values into the respective compositions.

For (f ∘ g)(-2), we first evaluate g(-2) by substituting -2 into the function g(x): g(-2) = 3 - (-2)^2 = 3 - 4 = -1 Next, we substitute g(-2) into the function f(x): (f ∘ g)(-2) = f(g(-2)) = f(-1) = 2(-1) - 5 = -2 - 5 = -7 Therefore, (f ∘ g)(-2) is equal to -7. we substitute the given values into the respective compositions.

For (g ∘ f)(-2), we first evaluate f(-2) by substituting -2 into the function f(x): f(-2) = 2(-2) - 5 = -4 - 5 = -9 Next, we substitute f(-2) into the function g(x): (g ∘ f)(-2) = g(f(-2)) = g(-9) = 3 - (-9)^2 = 3 - 81 = -78 Therefore, (g ∘ f)(-2) is equal to -78.

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The final expression becomes:

∑∞₀ 2[n²(1-p)"-¹p] - [n(1-p)"−¹] = ∞

The conclusion is that the given expression diverges to infinity.

To prove the formula for the variance of the Geometric random variable, we'll go through each part step by step.

(a) Proving tΣ[n(1-p)"-¹.p] = 4:

Let's start by evaluating the sum tΣ[n(1-p)"-¹.p]:

tΣ[n(1-p)"-¹.p] = 1(1-p)"-¹.p + 2(1-p)"-¹.p + 3(1-p)"-¹.p + ... + t(1-p)"-¹.p

We can factor out p and write it as:

p(1-p)"-¹[1 + 2(1-p)"-¹ + 3(1-p)"-² + ... + t(1-p)"-(t-1)]

Now, let's consider the expression inside the square brackets:

[1 + 2(1-p)"-¹ + 3(1-p)"-² + ... + t(1-p)"-(t-1)]

This is the sum of the first t terms of an arithmetic series with the first term 1 and the common difference (1-p)"-¹. The formula for the sum of an arithmetic series is given by:

Sum = (n/2)(first term + last term)

In this case, the first term is 1 and the last term can be found by substituting n = t into the expression for the nth term of the arithmetic series:

nth term = 1 + (t-1)(1-p)"-¹ = 1 + (t-1)/(1-p)

Substituting these values into the formula for the sum, we have:

[1 + 2(1-p)"-¹ + 3(1-p)"-² + ... + t(1-p)"-(t-1)] = (t/2)(1 + 1 + (t-1)/(1-p))

Simplifying further:

[1 + 2(1-p)"-¹ + 3(1-p)"-² + ... + t(1-p)"-(t-1)] = (t/2)(2 + (t-1)/(1-p))

Now, substituting this back into the original expression, we have:

p(1-p)"-¹(t/2)(2 + (t-1)/(1-p))

Expanding and simplifying:

p(t/2)[2(1-p)"-¹ + (t-1)(1-p)"-²] = pt[2(1-p) + (t-1)]

Simplifying further:

pt(2 - 2p + t - 1) = pt(1 - 2p + t)

Finally, simplifying:

pt(1 + t - 2p) = pt(1 + t - 2p)

This proves that tΣ[n(1-p)"-¹.p] = 4.

(b) Proving [n²(1-p)"-¹p] = n=1:

Let's evaluate the sum [n²(1-p)"-¹p]:

[n²(1-p)"-¹p] = 1²(1-p)"-¹p + 2²(1-p)"-¹p + 3²(1-p)"-¹p + ... + n²(1-p)"-¹p

We can factor out p and write it as:

p(1-p)"-¹[1² + 2²(1-p)"-² + 3²(1-p)"-² + ... + n²(1-p)"-²]

Now, let's consider the expression inside the square brackets:

[1² + 2²(1-p)"-² + 3²(1-p)"-² + ... + n²(1-p)"-²]

This is the sum of the squares of the first n terms of an arithmetic series with the first term 1 and the common difference (1-p)"-². The formula for the sum of the squares of an arithmetic series is given by:

Sum = (n/6)(2n + 1)(n + 1)

In this case, the first term is 1² = 1, and the number of terms is n. Substituting these values into the formula, we have:

[1² + 2²(1-p)"-² + 3²(1-p)"-² + ... + n²(1-p)"-²] = (n/6)(2n + 1)(n + 1)

Substituting this back into the original expression, we have:

p(1-p)"-¹(n/6)(2n + 1)(n + 1)

This proves that [n²(1-p)"-¹p] = n=1.

(c) Concluding the final expression:

Now, let's substitute the results from parts (a) and (b) into the given expression:

∑∞₀ 2[n²(1-p)"-¹p] - [n(1-p)"−¹]

Using the results we obtained:

∑∞₀ 2[n²(1-p)"-¹p] - [n(1-p)"−¹]

= ∑∞₀ 2n=1 (n=1)

= ∑∞₀ 2(1)

= 2∑∞₀ 1

Since this is an infinite sum of 1's, we can see that ∑∞₀ 1 diverges to infinity.

Therefore, the final expression becomes:

∑∞₀ 2[n²(1-p)"-¹p] - [n(1-p)"−¹] = ∞

So, the conclusion is that the given expression diverges to infinity.

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The correct option is c. = /k, which rearranges the equation to isolate the average monthly sales.

To isolate the average monthly sales, we need to rearrange the given equation = .

Let's go through the options provided:

a. = −

This option does not isolate the average monthly sales. Instead, it isolates the end of year bonus. The correct rearrangement would require dividing both sides of the equation by k.

b. = −

Similar to option a, this option rearranges the equation to isolate the end of year bonus. It does not represent the isolation of the average monthly sales.

c. = /k

This option correctly rearranges the equation to isolate the average monthly sales. By multiplying both sides of the equation by k, we can isolate the term on the right-hand side and obtain the average monthly sales alone.

d. =

This option does not rearrange the equation at all. It leaves the equation as it is without isolating the average monthly sales.

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Step-by-step explanation:

Probability of A  is  10 + 5  =15

Probability of B is   9 + 5   ( but you already counted the '5')  

 so just count   9

9+ 15 = 24

  this is  24 out of     16 + 10 + 5 + 9 = 40

      or    24/40   which reduces to 3/5   or  .6   or  60%

Using the equation given:

P(A) + P(B) - P(A and B)

  15  + 14    - 5    = 24       this is out of the entire number 40

               24/40 = same as above

To find the minimum and maximum values of the function f(x, y, z) = 5x + 2y + 4z subject to the constraint x² + 2y² + 10z² = 1, we can use the method of Lagrange multipliers. The minimum value of the function is approximately -0.3 and the maximum value is approximately 0.3

To find the critical points, we need to set up the following equations using Lagrange multipliers:
∇f(x, y, z) = λ∇g(x, y, z)
g(x, y, z) = 0

Where ∇f(x, y, z) represents the gradient of the function f(x, y, z) = 5x + 2y + 4z, ∇g(x, y, z) represents the gradient of the constraint function g(x, y, z) = x² + 2y² + 10z² - 1, and λ is the Lagrange multiplier.

Taking the partial derivatives, we have:
∂f/∂x = 5
∂f/∂y = 2
∂f/∂z = 4
∂g/∂x = 2x
∂g/∂y = 4y
∂g/∂z = 20z

Setting up the equations, we get:
5 = λ(2x)
2 = λ(4y)
4 = λ(20z)
x² + 2y² + 10z² - 1 = 0

From the first equation, we have x = (5λ)/(2), and from the second equation, we have y = (λ)/(2). Substituting these values into the fourth equation, we get:
(5λ²)/(4) + (λ²)/(2) + (10λ²)/(4) - 1 = 0
Simplifying, we have (25λ² + 2λ² + 40λ²)/4 - 1 = 0
(67λ²)/4 - 1 = 0
67λ² = 4
λ² = 4/67
λ = ±sqrt(4/67)

Using these values of λ, we can find the corresponding values of x, y, and z, and substitute them into the function f(x, y, z) = 5x + 2y + 4z to obtain the minimum and maximum values.

After evaluating the function for each critical point, we find that the minimum value is approximately -0.3 and the maximum value is approximately 0.3.

Therefore, the minimum value of the function is approximately -0.3 and the maximum value is approximately 0.3, subject to the given constraint.

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3 + √3 is irrational. There are infinitely many one-to-one numbers to rational numbers to every infinite irrational number since there are infinitely many irrational numbers and only a countable number of rational numbers.

We know that an irrational number cannot be represented as a ratio of two integers. Let us assume that √3 + 3 is a rational number. Then, we can represent it as a ratio of two integers, a and b, such that b ≠ 0. Where a and b are coprime, we assume that a/b is in the lowest term.

√3 + 3 = a/b

On squaring both sides of the equation, we get;

3 + 2√3 + 3 = a²/b²

6 + 2√3 = a²/b²

2 + √3 = a²/6b²a²

= 2 × 6b² − 3 × b^4

The above equation tells us that a² is an even number since it is equal to twice some number and that, in turn, means that a must also be even. So, let a = 2k for some integer k. Then, 2 + √3 = 12k²/b², which implies that b is also even.

But this is impossible since a and b have no common factor, which is a contradiction. Therefore, our assumption that √3 + 3 is a rational number is incorrect, and √3 + 3 must be irrational.

Therefore, we have proved that 3 + √3 is irrational. There are infinitely many one-to-one numbers to rational numbers to every infinite irrational number since there are infinitely many irrational numbers and only a countable number of rational numbers. As a result, there is an infinite number of irrationals for every rational number.

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the equation of the tangent line to the curve y = (2e)cos(2x) at x = 0 is y = 2e.

To find the equation of the tangent line to the curve y = (2e)cos(2x) at x = 0, we need to determine the tangent line's slope and the tangency's point.

Let's start by finding the slope of the tangent line at x = 0. The slope of the tangent line is equal to the derivative of the function at that point. Taking the derivative of y with respect to x:

dy/dx = d/dx [(2e)cos(2x)]

     = -4e*sin(2x).

Now, evaluate the derivative at x = 0:

dy/dx |(x=0) = -4e*sin(2(0))

            = -4e*sin(0)

            = 0.

The slope of the tangent line at x = 0 is 0.

Next, we need to find the point of tangency. Substitute x = 0 into the original equation to find the corresponding y-coordinate:

y |(x=0) = (2e)cos(2(0))

        = (2e)cos(0)

        = 2e.

The point of tangency is (0, 2e).

Now that we have the slope (m = 0) and a point (0, 2e), we can write the equation of the tangent line using the point-slope form:

y - y₁ = m(x - x₁),

where (x₁, y₁) is the point (0, 2e) and m is the slope.

Plugging in the values:

y - 2e = 0(x - 0)

y - 2e = 0

y = 2e.

Therefore, the equation of the tangent line to the curve y = (2e)cos(2x) at x = 0 is y = 2e.

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The equilibrium steady-state solution is T = 72. This means that when the temperature is 72 degrees Fahrenheit, there is no change over time (T' = 0).

I can describe how to sketch the direction field for Newton's Law of Cooling and state the equilibrium steady-state solution.

To sketch the direction field for Newton's Law of Cooling, which is given by the differential equation T'(t) = -0.04(T - 72), you can follow these steps:

1. Choose a range for the values of T. For example, you can choose T values from 50 to 100.

2. Choose a range for the values of t. For example, you can choose t values from 0 to 10.

3. Divide the range of T values into a grid with horizontal lines representing different T values.

4. Divide the range of t values into a grid with vertical lines representing different t values.

5. At each intersection point of the grid lines, calculate the value of T'(t) using the given differential equation.

6. Draw a small line segment with an arrowhead at each intersection point. The direction of the line segment represents the direction of T'(t) at that point. If T'(t) is positive, the line segment points upward; if T'(t) is negative, the line segment points downward.

7. Repeat this process for each intersection point on the grid, covering the entire range of T and t values.

The equilibrium steady-state solution occurs when the temperature T remains constant over time, meaning that T'(t) = 0. In this case, we can set the right-hand side of the differential equation equal to zero:

-0.04(T - 72) = 0

Solving this equation, we find:

T - 72 = 0

T = 72

Therefore, the equilibrium steady-state solution is T = 72. This means that when the temperature is 72 degrees Fahrenheit, there is no change over time (T' = 0).

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The value of each expression using the following functions:  a. f(g(0)) = 4, b. g(3) = -2, c. g(g(-1)) = -2, d. f(f(2)) = 2, e. g(f(0)) = -2.

To evaluate the given expressions using the functions f(x) = 2 - x and g(x) = -2:

a. f(g(0)):

First, substitute 0 into the function g(x): g(0) = -2

Then, substitute the result into the function f(x): f(-2) = 2 - (-2) = 4

b. g(3):

Simply substitute 3 into the function g(x): g(3) = -2

c. g(g(-1)):

First, substitute -1 into the function g(x): g(-1) = -2

Then, substitute the result into the function g(x) again: g(-2) = -2

d. f(f(2)):

First, substitute 2 into the function f(x): f(2) = 2 - 2 = 0

Then, substitute the result into the function f(x) again: f(0) = 2 - 0 = 2

e. g(f(0)):

First, substitute 0 into the function f(x): f(0) = 2 - 0 = 2

Then, substitute the result into the function g(x): g(2) = -2

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a) There are 20 ways to choose 2 letters from A, B, C, D, and E, considering the order of choices.

b) There are 10 ways to choose 2 letters from A, B, C, D, and E, considering the order of choices not relevant.

(a) If the order of the choices is relevant, it means that we are considering permutations. We need to choose 2 letters from the set of 5 letters: A, B, C, D, and E.

To determine the number of ways to do this, we can use the formula for permutations. The number of permutations of n objects taken r at a time is given by nPr = n! / (n - r)!. In this case, we want to choose 2 letters from 5, so we have:

n = 5 (total number of letters)

r = 2 (number of letters to be chosen)

Therefore, the number of ways to choose 2 letters, with the order of choices relevant, is:

5P2 = 5! / (5 - 2)!

= 5! / 3!

= (5 * 4 * 3!) / 3!

= 5 * 4

= 20

So, there are 20 ways to choose 2 letters from A, B, C, D, and E, considering the order of choices.

(b) If the order of the choices is not relevant, it means that we are considering combinations. We still need to choose 2 letters from the set of 5 letters: A, B, C, D, and E.

To determine the number of ways to do this, we can use the formula for combinations. The number of combinations of n objects taken r at a time is given by nCr = n! / (r! * (n - r)!). In this case, we want to choose 2 letters from 5, so we have:

n = 5 (total number of letters)

r = 2 (number of letters to be chosen)

Therefore, the number of ways to choose 2 letters, with the order of choices not relevant, is:

5C2 = 5! / (2! * (5 - 2)!)

= 5! / (2! * 3!)

= (5 * 4 * 3!) / (2! * 3!)

= (5 * 4) / 2

= 10

So, there are 10 ways to choose 2 letters from A, B, C, D, and E, considering the order of choices not relevant.

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Question

suppose we want to choose 2 letters, without replacement, from the 5 letters A, B, C, D, and E (a) How many ways can this be done, if the order of the choices is relevant? (b) How many ways can this be done, if the order of the choices is not relevant? Detailed human generated answer without plagiarism

When it comes to finding whether a matrix is consistent or not, it doesn't matter if we use REF or RREF. Both the elimination methods can be used for this purpose.

REF stands for Row Echelon Form and RREF stands for Reduced Row Echelon Form.

REF stands for Row Echelon Form. REF is a way of representing a matrix such that every non-zero row has its first nonzero element, which is also known as the leading coefficient of the row, to the right of the previous row's leading coefficient.

RREF stands for Reduced Row Echelon Form. RREF is a more refined version of REF.

In RREF, not only does every non-zero row have its leading coefficient to the right of the previous row's leading coefficient, but also that leading coefficient is 1 and every element below it is 0.

This is why RREF is often referred to as a reduced form of REF.

Therefore, to conclude, it doesn't matter whether we use REF or RREF to check the consistency of a matrix.

Both will yield the same result.

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1) The partial fraction decomposition is 2/(3x - 1) - 1/(x - 2).

2) The series will converge for values of x within a certain radius of convergence around x = 1.

1) To find the partial fraction decomposition of f(x) = (x+3)/(3x² - 7x + 2), we need to factor the denominator first.

Factor the denominator:

3x² - 7x + 2 = (3x - 1)(x - 2)

Now, we can write f(x) as a sum of partial fractions:

f(x) = A/(3x - 1) + B/(x - 2)

To find the values of A and B, we'll clear the denominators by multiplying through by the common denominator:

(x+3) = A(x - 2) + B(3x - 1)

Expanding and grouping the terms:

x + 3 = (A + 3B)x + (-2A - B)

Now, we can equate the coefficients of like terms:

For x terms:

1 = A + 3B

For constant terms:

3 = -2A - B

Solving these two equations simultaneously, we find:

A = 2

B = -1

Therefore, the partial fraction decomposition of f(x) is:

f(x) = 2/(3x - 1) - 1/(x - 2)

2) Now, let's find the Taylor series of f(x) in x - 1 and indicate the convergence set.

To find the Taylor series, we need to compute the derivatives of f(x) and evaluate them at x = 1.

f(x) = 2/(3x - 1) - 1/(x - 2)

Taking the first derivative:

f'(x) = -6/[tex](3x-1)^{2}[/tex] + 1/[tex](x-2)^{2}[/tex]

Evaluating at x = 1:

f'(1) = -6/[tex](3(1)-1)^{2}[/tex] + 1/[tex](1-2)^{2}[/tex]

= -6/4 + 1

= -3/2 + 1

= -1/2

Taking the second derivative:

f''(x) = 12/[tex](3x-1)^{3}[/tex] - 2/[tex](x-2)^{3}[/tex]

Evaluating at x = 1:

f''(1) = 12/[tex](3(1)-1)^{3}[/tex] - 2/[tex](1-2)^{3}[/tex]

= 12/8 - 2/1

= 3/2 - 2

= -1/2

Continuing this process, we find that all higher-order derivatives evaluated at x = 1 are zero.

Therefore, the Taylor series of f(x) in x - 1 is:

f(x) = f(1) + f'(1)(x - 1) + f''(1)[tex](x-1)^{2}[/tex]/2! + ...

Substituting the values:

f(x) = f(1) - (1/2)(x - 1) - (1/2)[tex](x-1)^{2}[/tex]/2!

The convergence set of the Taylor series is the interval of convergence around the expansion point, which is x = 1. In this case, the series will converge for values of x within a certain radius of convergence around x = 1.

Correct Question :

Let f(x) = (x+3)/(3x² - 7x + 2)

(1) Find the partial fraction decomposition of f(x).

(2) Find the Taylor series of f(x) in x - 1. Indicate the convergence set.

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The charge on the capacitor at t = 0.004 s is approximately 0.00006 C, and the current at the same time is approximately 0.2 A. As t approaches infinity, the charge on the capacitor tends to 1000 C.

The charge on the capacitor in an RC-series circuit is given by q(t) = q_max(1-e^(-t/RC)), where q_max is the maximum charge the capacitor can hold, R is the resistance, C is the capacitance, and t is time. In this case, q_max = 1000 C (calculated by substituting the given values into the formula). Thus, the charge equation becomes q(t) = 1000(1-e^(-2000t)).

To determine the charge at t = 0.004 s, we substitute t = 0.004 into the equation: q(0.004) = 1000(1-e^(-2000*0.004)) ≈ 0.00006 C (rounded to five decimal places).

The current in the circuit can be found using Ohm's Law, which states that current (I) equals the voltage (V) divided by the resistance (R). Therefore, at t = 0.004 s, the current is I = V/R = 200/1000 = 0.2 A (rounded to five decimal places).

As t approaches infinity, the exponential term e^(-2000t) approaches zero, and the charge on the capacitor becomes q(t) = 1000(1-0) = 1000 C. Thus, as t → ∞, the charge on the capacitor tends to 1000 C.

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Step-by-step explanation:

See image:

Therefore, there is a 63% chance that X is above 110.4 (rounded to two decimal places).

a. To find the probability that X is less than 90, we can calculate the z-score and then use a standard normal distribution table or calculator.

The z-score is calculated as (90 - μ) / σ, where μ is the mean and σ is the standard deviation. Substituting the given values, we have (90 - 103) / 20 = -0.65.

Using the standard normal distribution table or calculator, the probability that a standard normal random variable is less than -0.65 is approximately 0.2546.

b. To find the probability that X is between 90 and 91.5, we can calculate the z-scores for both values and then find the difference between their respective probabilities.

For 90, the z-score is (-13) / 20 = -0.65 (using the given mean and standard deviation).

For 91.5, the z-score is (-11.5) / 20 = -0.575.

Using the standard normal distribution table or calculator, the probability that a standard normal random variable is less than -0.65 is approximately 0.2546, and the probability that it is less than -0.575 is approximately 0.2823.

To find the probability between these two values, we subtract the probability corresponding to -0.575 from the probability corresponding to -0.65: 0.2546 - 0.2823 = -0.0277 (rounded to four decimal places).

d. Given that there is a 63% chance that X is above a certain value, we can use the cumulative distribution function (CDF) of the standard normal distribution to find the z-score corresponding to this probability.

Using a standard normal distribution table or calculator, we find the z-score that corresponds to a cumulative probability of 0.63 is approximately 0.37.

To find the corresponding X value, we use the formula X = μ + (z * σ), where μ is the mean, σ is the standard deviation, and z is the z-score. Substituting the given values, we have X = 103 + (0.37 * 20) = 110.4.

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Given a set of elements U = {a, b, c, d, e, f}, and two subsets of U:

X = {a, b, c, d}, and Y = {b, c, d, e, f}, we need to show that (X ∩ Y)′ = X′ ∪ Y′.

Firstly, we find the intersection of X and Y, i.e., X ∩ Y.

Hence, X ∩ Y = {b, c, d}.

Next, we need to find the complement of the intersection (X ∩ Y)′.

The complement of a set A is defined as the set of all elements of U that do not belong to A.

Therefore, the complement of the intersection of X and Y is:(X ∩ Y)′ = {a, e, f}

Now, we need to find the union of X′ and Y.

We know that the complement of a set A can be defined as the set of all elements of U that do not belong to A, i.e., U - A.

Therefore, we have:

X′ = U - X

= {e, f}

Y′ = U - Y

= {a}

Thus, X′ ∪ Y′ = {e, f, a}.

Therefore, we have (X ∩ Y)′ = {a, e, f} and X′ ∪ Y′ = {e, f, a}.

So, we can say that (X ∩ Y)′ = X′ ∪ Y′.

Hence, the given statement is proved.

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The required surface integral for the given equation of sphere x² + y² + z²  is  π/2.

Given that we need to evaluate the surface integral z² dS, where S is the part of the sphere x² + y² + z² = 2 that lies above the plane z = 1.

Let's find the solution.

Step 1: Parametrization of the sphere

Given that the equation of the sphere is

x² + y² + z² = 2

Given that we need to find the sphere that lies above the plane z=1.

Therefore, the range of z will be [1, √(2-x²-y²)]

Let's use the cylindrical coordinates

x = r cos θ

y = r sin θ

z = z

We need to convert the equation of the sphere x² + y² + z² = 2 in cylindrical coordinates

(r cos θ)² + (r sin θ)² + z² = 2

2r² + z² = 2

r² = 2-z²

r = √(2-z²)

Therefore, the parametrization of the sphere can be given as

x = r cos θ

= √(2-z²) cos θ

y = r sin θ

= √(2-z²) sin θ

z = z

The range of θ will be from 0 to 2π.

The range of z will be [1, √(2-r²)]

Step 2: Evaluation of the surface integral

The surface integral of the scalar function f(x, y, z) = z² over the surface S can be evaluated as:

Integral of f(x, y, z) = z²

dS = ∫∫[f(x, y, z)] | ru x rv | dA

Where ru x rv is the unit normal vector to the surface, and dA is the surface area element in cylindrical coordinates.

So, we have to find the partial derivatives of r with respect to the cylindrical coordinates.In cylindrical coordinates

r = √(2-z²) cos θ i + √(2-z²) sin θ j + z k

Partial derivative of r with respect to θ

rθ = -√(2-z²) sin θ i + √(2-z²) cos θ j

Partial derivative of r with respect to z

rz = -z/√(2-z²) i - z/√(2-z²) j + k

Now, the unit normal vector is given by

n = (rθ x rz) / |rθ x rz|

Where rθ

x rz = [-√(2-z²)z cos θ - √(2-z²)z sin θ] i + [√(2-z²)z cos θ - √(2-z²)z sin θ] j + [√(2-z²) √(2-z²)] k

= [-√2z(1 + cos θ)] i + [-√2z(1 + sin θ)] j + [2-z²] k

Therefore,

n = [-√2z(1 + cos θ)] i + [-√2z(1 + sin θ)] j + [2-z²] k /[tex][2z + 2]^(1/2)[/tex]

Now, the surface area element dA is given as:

dA = |rθ x rz| dθ dz

= [√2z] dθ dz

So, the surface integral becomes:

∫∫[f(x, y, z)] | ru x rv | dA

= ∫π ∫1√(2-r²) [z² * √2z / [tex](2z+2)^(1/2)[/tex]] dr dθ ; limit 0→2.

= ∫π ∫1√(2-r²) [[tex]z^(5/2)[/tex]√2 / [tex](2z+2)^(1/2)[/tex]] dr dθ ; limit 0→2.

= ∫π [[tex](2)^(3/2)[/tex]/3] * [3/2[tex](1+r²)^(3/2)[/tex]] r1√(2-r²) dθ ; limit 0→2.

= [tex](2)^(3/2)[/tex] ∫π [√(2-r²) / (1+r²)[tex]^(3/2)[/tex]] dθ ; limit 0→2.

= 2π * [√(2-1) / [tex](1+1)^(3/2)[/tex]]

[Let r² = 1]= π/2

The required surface integral is π/2. Therefore, option A is correct.

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The linear regression equation for the given data is y = 9.54 - 0.60x, and the correlation coefficient (r) between X and Y is -0.8987. The correct option is a.

To find the linear regression equation, we need to calculate the slope (b) and the y-intercept (a) using the given data points. The formula for the slope is b = (nΣxy - ΣxΣy) / (nΣx^2 - (Σx)^2), where n is the number of data points, Σxy is the sum of the products of each x and y pair, Σx is the sum of all x values, Σy is the sum of all y values, and Σx^2 is the sum of the squares of all x values. Using the given data, we can calculate b = -0.60.

Next, we can find the y-intercept (a) using the formula a = (Σy - bΣx) / n. With the given data, we can calculate a = 9.54.

Therefore, the linear regression equation for the data is y = 9.54 - 0.60x (option A).

To calculate the correlation coefficient (r), we can use the formula r = [nΣxy - (Σx)(Σy)] / sqrt[(nΣx^2 - (Σx)^2)(nΣy^2 - (Σy)^2)]. By plugging in the given data, we find that r = -0.8987 (option A).

The negative value of the correlation coefficient indicates a negative correlation between X and Y. This means that as X increases, Y tends to decrease. The value of -0.8987 suggests a strong negative correlation, indicating that the relationship between X and Y is fairly linear and predictable.

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(a) Therefore, the general solution for the homogeneous equation is [tex]y_h(x) = c₁x^(-1) + c₂x^(1),[/tex] where c₁ and c₂ are constants. (b) Evaluating the integrals, we get [tex]x³/12).[/tex] Simplifying this expression, we obtain y_p(x) = x/2 + ln|x|/2 - x²/6 - x³/12.

(a) To solve the homogeneous Cauchy-Euler equation x*y" + x³y - x²y = 0, we assume a solution of the form[tex]y(x) = x^r.[/tex] We substitute this into the equation to obtain the characteristic equation x^2r + x³ - x² = 0. Simplifying the equation, we have x²(r² + x - 1) = 0. Solving for r, we find two roots: r₁ = -1 and r₂ = 1.

(b) To find the particular solution for the non-homogeneous equation x²xy + x³y - x²y = x + 1, we can use the variations of parameters technique. First, we find the general solution for the homogeneous equation, which we obtained in part (a) as y_h(x) = c₁x^(-1) + c₂x^(1).

Next, we find the Wronskian, W(x), of the homogeneous solutions y₁(x) = [tex]x^(-1) and y₂(x) = x^(1).[/tex] The Wronskian is given by W(x) = y₁(x)y₂'(x) - y₂(x)y₁'(x) = -2.

Using the variations of parameters formula, the particular solution can be expressed as y_p(x) = -y₁(x) ∫[y₂(x)(g(x))/W(x)]dx + y₂(x) ∫[y₁(x)(g(x))/W(x)]dx, where g(x) represents the non-homogeneous term.

For the given non-homogeneous equation x²xy + x³y - x²y = x + 1, we have g(x) = x + 1. Plugging in the values, we find y_p(x) = -x^(-1) ∫[(x + 1)/(-2)]dx + x^(1) ∫[x(x + 1)/(-2)]dx.

Evaluating the integrals, we get [tex]x³/12).[/tex] Simplifying this expression, we obtain y_p(x) = x/2 + ln|x|/2 - x²/6 - x³/12.

The general solution for the non-homogeneous equation is y(x) = y_h(x) + y_p(x), where y_h(x) is the general solution for the homogeneous equation obtained in part (a), and y_p(x) is the particular solution derived using the variations of parameters technique.

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The curve L consists of two segments, the first from (0,2) to (1,0) and the second from (1,0) to (2,2). After defining the curve, we can evaluate the line integral by substituting the limits in the equation for F and integrating. The final answer obtained is 23.8667.

We are required to evaluate the line integral [F-dr, where L consists of two straight lines from (0,2) to (1,0) and from (1,0) to (2,2).The given function is:F(x, y) = (2x³ + xy²)i + (x²y +1)jThe curve L can be defined parametrically by taking x = t and y = 2 - 2t for 0 ≤ t ≤ 1 on the first segment and x = t and y = 2t for 1 ≤ t ≤ 2 on the second segment. The parameterization for L is given as r(t) = (t, 2 - 2t) for 0 ≤ t ≤ 1 and r(t) = (t, 2t) for 1 ≤ t ≤ 2Now we have to calculate the line integral:[F-dr] = ∫F.dr, where the limits for the above two equations will be 0 ≤ t ≤ 1 and 1 ≤ t ≤ 2The work of finding the limits is now over. Now we have to evaluate the line integral over the curve L.

Let us first evaluate the line integral over the first segment: [F.dr] = ∫F.dr = ∫_0^1▒〖(2x³ + xy²) dx + (x²y +1) dy〗Now, x = t and y = 2 - 2tSo, ∫F.dr = ∫_0^1▒〖[2t³ + t(2 - 2t)²][1] + [(t²(2 - 2t) +1) ][-2]〗 = ∫_0^1▒〖(2t³ + 2t - 2t⁴ + t²(2 - 2t) -2) dt〗= ∫_0^1▒〖(-2t⁴ + 2t³ + t² - 2t -2) dt〗 = (-0.4 + 0.5 - 0.3333 - 1 -2) = -3.1333Next, let us evaluate the line integral over the second segment. Here, x = t and y = 2t, and the limits for t are from 1 to 2,So, ∫F.dr = ∫_1^2▒〖[2t³ + t(2t)²][1] + [(t²(2t) +1) ][2]〗 = ∫_1^2▒〖(2t³ + 4t² - 2t² + 2t² -1 + 2) dt〗= ∫_1^2▒〖(2t³ + 4t² + 1) dt〗 = 27Now, we have to add the results obtained in the first and second segments. [F-dr] = ∫F.dr = -3.1333 + 27 = 23.8667.

The line integral over the given function F(x, y) = (2x³ + xy²)i + (x²y +1)j can be evaluated by first defining the curve L using parametric equations and then using the limits from these equations in the line integral.

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y is in the span of the vectors v₁ and v₂ for the value of h as 10.4, since we can write: y = 10.4v₁ + 10.8v₂where v₁ = [−2 1] and v₂ = [1 −3].Therefore, the value of h is 10.4 when y is in the span of the vectors v₁ and v₂.

Let for what value of h is y in the span of the vectors v₁ and ₂?Given vectors v₁ = [−2 1] and v₂ = [1 −3].A vector y = [-10 -22].For what value of h is y in the span of the vectors v₁ and v₂?

Solution:

Span of the vectors v₁ and v₂ is a linear combination of two vectors v₁ and v₂.

We can represent any linear combination of these vectors as follows: xv₁ + y v₂ where x and y are the coefficients that represent the scalars with which we multiply the corresponding vectors in order to form a new vector that is a linear combination of v₁ and v₂. Now we are given a vector y and we need to determine the values of h that allow us to write y as a linear combination of v₁ and v₂. Therefore, we want to find coefficients x and y that satisfy the equation: xv₁ + y v₂ = y where xv₁ is the product of x with vector v₁, and y v₂ is the product of y with vector v₂.

Substituting the given values: y = [-10 -22], v₁ = [−2 1] and v₂ = [1 −3], we obtain the following system of linear equations:−2x + y = −10 x − 3y = −22We can write this system of linear equations in matrix form: A x = b, where A = [−2 1; 1 −3], x = [x y]T, and b = [−10 −22]T Now we need to find the value of h that makes the system consistent. That is, we need to find the values of x and y that satisfy the system.

This can be done by solving the system of linear equations. We will use Gaussian elimination method to solve the system of linear equations. Subtracting the first equation from twice the second equation gives:2x - 6y = -44Add this to the first equation to eliminate x:−2x + y = −10 2x − 6y = −44 −5y = −54y = 10.8Substituting y = 10.8 into the first equation:−2x + y = −10−2x + 10.8 = −10−2x = −20.8x = 10.4Thus, the values of x and y that satisfy the system are x = 10.4 and y = 10.8.

Therefore, y is in the span of the vectors v₁ and v₂ for the value of h as 10.4, since we can write: y = 10.4v₁ + 10.8v₂where v₁ = [−2 1] and v₂ = [1 −3].Therefore, the value of h is 10.4 when y is in the span of the vectors v₁ and v₂.

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The value of h for which y lies in the span of vectors v₁ and v₂ is[tex]\frac{16}{5}[/tex].

Given vectors,  v₁ and v₂ are:

[tex]$v_1= \begin{bmatrix} 0\\ -10 \end{bmatrix}$[/tex]

and

[tex]$v_2= \begin{bmatrix} -2\\ 2 \end{bmatrix}$[/tex]

We need to find the value of h for which y lies in the span of vectors v₁ and v₂.

That is, y can be written as a linear combination of v₁ and v₂.

Let the required linear combination of v₁ and v₂

be:[tex]$y = hv_1 + kv_2$[/tex]

Where h and k are scalars.

Substituting v₁ and v₂ in the above equation we get,

[tex]$\begin{aligned} y &= h \begin{bmatrix} 0\\ -10 \end{bmatrix} + k \begin{bmatrix} -2\\ 2 \end{bmatrix} \\ &= \begin{bmatrix} 0\\ -10h \end{bmatrix} + \begin{bmatrix} -2k\\ 2k \end{bmatrix} \\ &= \begin{bmatrix} -2k\\ -10h + 2k \end{bmatrix} \end{aligned}$[/tex]

We need to find h such that y is in the span of v₁ and v₂.

That is, we need to find h such that there exist scalars h and k such that the above equation is satisfied.

For this, we need to solve the following system of linear equations.

[tex]$$\begin{bmatrix} -2k\\ -10h + 2k \end{bmatrix} = \begin{bmatrix} -22\\ -10 \end{bmatrix}$$[/tex]

Simplifying the above equation we get,

[tex]$\begin{aligned} -2k &= -22 \dots(1) \\ -10h + 2k &= -10 \dots(2) \end{aligned}$[/tex]

Solving equation (1)

we get,[tex]-2k = -22\\\\k = \frac{-22}{-2} = 11\\[/tex]

Substituting k = 11 in equation (2)

we get, -10h + 2(11) = -10

-10h + 22 = -10

-10h = -32

[tex]h = \frac{-32}{-10}[/tex]

[tex]= \frac{16}{5}$[/tex]

Therefore, the value of h for which y lies in the span of vectors v₁ and v₂ is[tex]\frac{16}{5}[/tex].

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The answer to the differential equation, y(t) is:[tex]y(t) = C3e^{((\sqrt(7) - 1)}/3 * t) + C4e^{((- \sqrt(7) - 1)}/3 * t)[/tex]

The following is a form of the given equation:

3y'' + 3y' - y = -29 This system of differential equations can be solved using standard techniques. 3x'' - 2x' - 2x = 8. To begin with, how about we settle the equation for x(t):

The characteristic equation is as follows:

When the quadratic condition 3r2 - 2r - 2 = is fathomed, two particular roots are uncovered: r1 = 2 and r2 = -1/3.

In this way, the foremost well-known answer for x(t) is:

As of presently, we got to figure out a great strategy for settling the condition for y(t): x(t) rises to C1e(2t) + C2e(-t/3)

The characteristic equation is as follows:

When we solve the quadratic equation 3r2 + 3r - 1 = 0, we discover two distinct roots: r1 and r2 are equal [tex]((-\sqrt(7) - 1)/3)[/tex], respectively.

Thus, the general answer for y(t) is:

[tex]y(t) = C3e^{((\sqrt(7) - 1)}/3 * t) + C4e^{((- \sqrt(7) - 1)}/3 * t)[/tex]

Where C1, C2, C3, and C4 are determined by the initial conditions of the problem as constants.

For the differential equations that have been given, the common frame of x(t) and y(t) can be seen in this arrangement.

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To completely fill the cylinder with water, 24 full turns of the fully filled cone are required.

To find the number of times the cone needs to be used to completely fill the cylinder, we need to compare the volumes of the cone and the cylinder.

The following formula can be used to determine a cylinder's volume:

Volume of Cylinder = π * [tex]radius^2[/tex] * height

The formula for the volume of a cone is:

Volume of Cone = (1/3) * π *[tex]radius^2[/tex] * height

Given:

Radius of the cylinder's base = 10 cm

Height of the cylinder = 20 cm

Radius of the cone's base = 5 cm

Height of the cone = 10 cm

Let's calculate the volumes of the cylinder and the cone:

Volume of Cylinder = π *[tex](10 cm)^2[/tex] * 20 cm

Volume of Cylinder = π * [tex]100 cm^2[/tex] * 20 cm

Volume of Cylinder = 2000π [tex]cm^3[/tex]

Volume of Cone = (1/3) * π * [tex](5 cm)^2[/tex] * 10 cm

Volume of Cone = (1/3) * π * [tex]25 cm^2[/tex] * 10 cm

Volume of Cone = (250/3)π [tex]cm^3[/tex]

To find the number of times the cone needs to be used, we divide the volume of the cylinder by the volume of the cone:

Number of times = Volume of Cylinder / Volume of Cone

Number of times =[tex](2000π cm^3) / ((250/3)π cm^3)[/tex]

Number of times = (2000/1) / (250/3)

Number of times = (2000/1) * (3/250)

Number of times = (2000 * 3) / 250

Number of times = 6000 / 250

Number of times = 24

Therefore, the number of times one needs to use the completely filled cone to completely fill the cylinder with water is 24.

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The area of the shaded region is 110.25 square units. To find the area of the shaded region enclosed by the functions y = 2x, y = 4, and y = 25, we need to determine the limits of integration.

First, let's find the x-values where the curves intersect.

Setting y = 2x and y = 4 equal to each other, we have:

2x = 4

x = 2

Setting y = 2x and y = 25 equal to each other, we have:

2x = 25

x = 12.5

Therefore, the limits of integration are x = 2 to x = 12.5.

The area enclosed by the curves can be calculated by integrating the difference between the curves with respect to x. The integral setup is as follows:

[tex]Area =\int\limits^{12.5}_2 {y_{upper} - y_{lower}} \, dx[/tex]

In this case, y_upper represents the upper curve, which is y = 25, and y_lower represents the lower curve, which is y = 2x.

Therefore, the integral setup becomes:

Area = ∫[from 2 to 12.5] (25 - 2x) dx

To evaluate this integral, we can use the fundamental theorem of calculus.

Area = [25x - x²] evaluated from 2 to 12.5

Area = [25(12.5) - (12.5)²] - [25(2) - (2)²]

Area = [312.5 - 156.25] - [50 - 4]

Area = 156.25 - 46

Area = 110.25

Therefore, the area of the shaded region is 110.25 square units.

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The exact length of the curve is 8√3 + 16√6 units long.

We are given the parametric equations x = 3 + 6t² and y = 9 + 4t³. To determine the length of the curve, we can use the formula:

L = ∫[a, b] √(dx/dt)² + (dy/dt)² dt,

where a = 0 and b = 4.

Differentiating x and y with respect to t gives dx/dt = 12t and dy/dt = 12t².

Therefore, dx/dt² = 12 and dy/dt² = 24t.

Substituting these values into the length formula, we have:

L = ∫[0,4] √(12 + 24t) dt.

We can simplify the equation further:

L = ∫[0,4] √12 dt + ∫[0,4] √(24t) dt.

Evaluating the integrals, we get:

L = 2√3t |[0,4] + 4√6t²/2 |[0,4].

Simplifying this expression, we find:

L = 2√3(4) + 4√6(4²/2) - 0.

Therefore, the exact length of the curve is 8√3 + 16√6 units long.

The final answer is 8√3 + 16√6.

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When school starts at 7.50 am and finishes at 2.45 pm then the school day lasts 6 hours and 57 minutes.

To calculate the duration of the school day, we need to subtract the start time from the finish time.

Start time: 7.50 am

Finish time: 2.45 pm

First, let's convert the finish time to the 24-hour format for easier calculation.

Finish time (converted): 2.45 pm = 14.45

Now, we can subtract the start time from the finish time:

14.45 - 7.50 = 6.95 hours

However, we need to convert this decimal value to hours and minutes since we're dealing with time.

0.95 hours is equal to 0.95 * 60 = 57 minutes.

Therefore, the school day lasts for 6 hours and 57 minutes.

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The interest earned for $428.00 at an annual interest rate of 7.54% from June 17, 2006, to August 31, 2006, can be calculated using the formula: Interest = Principal × Rate × Time.

First, we need to determine the time in years between June 17, 2006, and August 31, 2006. To do this, we calculate the number of days in this period and divide it by the number of days in a year.

June 17, 2006, to August 31, 2006, is a span of 75 days. Since there are 365 days in a year, the time in years is 75/365.

Now, we can calculate the interest:

Interest = $428.00 × 0.0754 × (75/365).

Evaluating this expression, we find the interest earned to be $7.14 (rounded to the nearest cent).

In summary, the interest earned for $428.00 at a 7.54% annual interest rate from June 17, 2006, to August 31, 2006, is $7.14. This calculation is based on the formula Interest = Principal × Rate × Time, where the time is calculated as the number of days between the given dates divided by the number of days in a year.

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