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Triangle JKL has vertices at J(−1, −5), K(−2, −2), and L(2, −4). Determine the translation direction and number of units of the image of triangle JKL if vertex J′ is at (2, −5).

1 unit down
1 unit up
3 units to the right
3 units to the left

The area covered in tiles is given as follows:

423.3 ft².

The dimensions of the rectangular region of the pool are given as follows:

20 ft and 30 ft.

Hence the entire area is given as follows:

20 x 30 = 600 ft².

The radius of the pool is given as follows:

r = 7.5 ft.

(as the radius is half the diameter).

Hence the area of the pool is given as follows:

A = π x 7.5²

A = 176.7 ft².

Hence the area that will be covered in tiles is given as follows:

600 - 176.7 = 423.3 ft².

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Answer:

In ascending order: 1/2, 3/5, 6/11, 8/9

We are asked to compute the matrix U, formed by concatenating u1 and u2 as columns, and to compute U'U and UUT. Additionally, we are asked to compute the projection of y onto the subspace spanned by u1 and u2, as well as (uuT)y and (UU)y.

We can compute the matrix U by concatenating u1 and u2 as columns. Thus, we have:

U = | 2/3 -2/3 |

| 2/3 1/3 |

| 1/3 2/3 |

Next, we can compute U'U and UUT as follows:

U'U = | 2 0 |

| 0 2 |

UUT = | 8/9 4/9 2/9 |

| 4/9 4/9 4/9 |

| 2/9 4/9 8/9 |

For the second part of the problem, we can compute the projection of y onto the subspace spanned by u1 and u2 using the formula,

[tex]projwy[/tex]= (y'u1/u1'u1)u1 + (y'u2/u2'u2)u2. Plugging in the given values, we get:

[tex]projwy[/tex]= | 22/9 |

| 20/9 |

| 4/9 |

We can also compute [tex](uuT)y[/tex]and (UU)y as follows:

[tex](uuT)y[/tex]= [tex]uuT y[/tex]= | 10 |

| 0 |

| 0 |

(UU)y = UU (4 5 1)' = | 14 |

| 14 |

| 7 |

We also computed the projection of y onto the subspace spanned by u1 and u2, as well as [tex](uuT)y[/tex] and (UU)y.

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If f is a function from the finite set x to the finite set y, then f is said to be one-to-one if every element in x maps to a unique element in y. In other words, no two elements in x can map to the same element in y.

Now, let's assume that |x|>|y|. This means that there are more elements in x than there are in y. Therefore, there must be at least one element in x that does not have a unique element in y to map to. If this element maps to the same element in y as another element in x, then f is not one-to-one. This is because two elements in x have mapped to the same element in y, violating the definition of a one-to-one function.

Hence, we can conclude that if |x|>|y|, then f cannot be one-to-one. This is a fundamental result in set theory and is important to understand in order to properly define functions and their properties.

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The like terms in the expression 8x² − 4x³ + 5x² × 2x² are 2x².

Like terms are terms with the same variables and the same power of the variables.
In the expression 8x² − 4x³ + 5x² × 2x², the variables are x and the coefficients are 8, −4, and 5 × 2 = 10.
The like terms are the terms that have the same variable raised to the same power.
We can combine these terms as we combine like terms, by adding their coefficients.
The like terms in this expression are:8x² and 5x² × 2x² = 10x² × 2x² = 20x⁴.

The summary is the given terms, 8, -4x³, and 5x² × 2x², are not like terms.

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The average value of the function f(x) = 6x over the interval [0, 9] is 27.

To find the average value of a function over a given interval, you need to take the definite integral of the function over that interval, and divide by the length of the interval. In this case, the function is f(x) = 6x, and the interval is [0, 9].

So first, we need to find the definite integral of 6x over [0, 9]:

∫[0,9] 6x dx = 3x^2 |[0,9] = 243

Next, we need to find the length of the interval, which is simply 9 - 0 = 9.

Finally, we divide the definite integral by the length of the interval:

Average value of f(x) = (1/9) * 243 = 27

So the average value of the function f(x) = 6x over the interval [0, 9] is 27.

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Answer:

13x

Step-by-step explanation:

+3y and -3y cancel out

Therefore, we have 4x+9x

13x

The experimenter is trying to measure the subject's just noticeable difference (JND).

Just noticeable difference (JND) is the smallest detectable difference between two stimuli that a person can detect. In this experiment, the experimenter is presenting the subject with a standard weight of 100 grams and then presenting comparison weights of increasing and decreasing amounts until the subject indicates that the weights are the same.

The just noticeable difference (JND) is an important concept in sensory psychology. It refers to the smallest detectable difference between two stimuli that a person can detect. In this experiment, the experimenter is trying to measure the subject's JND for weight. The experiment involves presenting the subject with a standard weight of 100 grams, followed by a comparison weight of increasing amounts until the subject says that the two weights are the same. The experimenter then repeats this process, but with a comparison weight of decreasing amounts until the subject again says that the two weights are the same.

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Answer: 2

Step-by-step explanation:2/3 x 6 x 1/2

any finite set is countable yes  (a) True

A finite set is countable because it has a specific number of elements that can be put into one-to-one correspondence with a subset of natural numbers. In other words, you can assign a unique natural number to each element in the finite set without running out of natural numbers to assign.


1. A finite set has a limited number of elements, meaning there is an exact count for the elements in the set.
2. A countable set is a set whose elements can be put into one-to-one correspondence with a subset of natural numbers (0, 1, 2, 3, ...).
3. Since a finite set has a specific number of elements, we can assign a unique natural number to each element without running out of numbers.
4. This one-to-one correspondence between the elements in the finite set and the natural numbers demonstrates that the set is countable.

Finite sets are countable because they contain a specific, limited number of elements that can be matched up with a subset of natural numbers. By establishing a one-to-one correspondence between the elements in the finite set and natural numbers, we can effectively count the elements in the set, making it countable.

Any finite set is countable because its elements can be placed in one-to-one correspondence with a subset of natural numbers, allowing for the set to be effectively counted.

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1. The height of the cone is equal to

2. You can solve for the slant height, s by applying Pythagorean's theorem.

3. To get from the base of the cone to the top of the hill, an ant has to crawl 29 mm.

In Mathematics and Geometry, the volume of a cone can be calculated by using this formula:

Volume of cone, V = 1/3 × πr²h

Where:

By substituting the given parameters into the formula for the volume of a cone, we have the following;

8792 =  1/3 × 3.14 × 20² × h

26,376 =  3.14 × 400 × h

Height, h = 26,376/1,256

Height, h = 21 mm.

Question 2.

In order to solve for the slant height, s, we would have to apply Pythagorean's theorem since the height of the cone has been calculated above.

Question 3.

By applying Pythagorean's theorem, we have the following:

r² + h² = s²

20² + 21² = s²

400 + 441 = s²

s² = 841

Slant height, s = √841

Slant height, s = 29 mm.

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The issue with the claim that a heat engine takes in 21 kJ of heat, discharges 16 kJ of heat to the environment, and performs 3 kJ of work is that the work performed does not equal the difference between the heat input and the heat output. Therefore, the correct option  is A.

1. According to the first law of thermodynamics, the work performed by a heat engine is equal to the difference between the heat input (Qin) and the heat output (Qout).
2. In this case, Qin is 21 kJ and Qout is 16 kJ.
3. The difference between the heat input and heat output is 21 kJ - 16 kJ = 5 kJ.
4. However, the claim states that the work performed is 3 kJ, which is not equal to the difference between the heat input and the heat output (5 kJ).

Hence, the claim is incorrect because the work performed does not equal the difference between the heat input and the heat output. The correct answer is option A.

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The expected value of X is 297/35 and the variance of X is 774/1225.

Let's define the indicator random variable Xi as follows:

Xi = 1, if the i-th roll results in a new number (that hasn't been rolled before).

Xi = 0, otherwise.

Then, X is the sum of these indicator variables, that is:

X = X1 + X2 + X3

We know that E[Xi] = 1/p, where p is the probability of rolling a new number on the i-th roll, given that i - 1 distinct numbers have already been rolled. Since there are i - 1 distinct numbers already rolled, the probability of rolling a new number on the i-th roll is (6 - i + 1)/6.

Thus, we have:

E[Xi] = 6/(6-i+1) = 6/(7-i)

Using the linearity of expectation, we can find the expected value of X:

E[X] = E[X1] + E[X2] + E[X3] = 6/7 + 6/6 + 6/5 = 297/35

To find the variance of X, we need to calculate the variance of each Xi:

Var(Xi) = E[Xi^2] - E[Xi]^2

We know that:

E[Xi^2] = 1(6-i+1)/6 + 0(i-1)/6 = (7-i)/6

So, we have:

Var(Xi) = (7-i)/6 - (6/(7-i))^2

Using the linearity of variance, we can find the variance of X:

Var(X) = Var(X1) + Var(X2) + Var(X3)

= (4/6) - (6/7)^2 + (3/6) - (6/6)^2 + (2/6) - (6/5)^2

= 774/1225

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The interval on which f(x) is increasing is (-3, 3).

To determine on what interval the function f(x) = x 0 (9 − t2) et2 dt is increasing, we need to find the derivative of f(x) and then examine its sign.

We can use the Leibniz rule to find the derivative of f(x):

f'(x) = (d/dx) x 0 (9 − t2) et2 dt = (9 − x2) ex2

Now we need to determine the sign of f'(x) on different intervals. Notice that the factor (9 - x^2) is always positive for x in the interval [-3, 3], and ex^2 is always positive for any x. Therefore, the sign of f'(x) is determined by the sign of (9 - x^2)ex^2.

If x < -3 or x > 3, then (9 - x^2) is negative, and so is f'(x). Therefore, f(x) is decreasing on (-∞, -3) and (3, ∞).

If -3 < x < 3, then (9 - x^2) is positive, and so is f'(x). Therefore, f(x) is increasing on (-3, 3).

Therefore, the interval on which f(x) is increasing is (-3, 3).

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The total surface area of the given pyramid is 336ft²

We have.

The surface area of a solid object is a measure of the total area that the surface of the object occupies.

The space occupied by a two-dimensional flat surface is called the area. It is measured in square units. The area occupied by a three-dimensional object by its outer surface is called the surface area.

A surface, as the term is most generally used, is the outermost or uppermost layer of a physical object or space. It is the portion or region of the object that can first be perceived by an observer using the senses of sight and touch, and is the portion with which other materials first interact.

Given is a net of a square pyramid and having dimensions,10 ft 8 ft 12 ft

The total surface area of the pyramid :-

= area of base square +(side)²

= 4 (1/2 x 12 x 8) + 144

= 144+192

= 336ft²

Hence, the total surface area of the given pyramid is 336ft²

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The complete question is :-

The net of a square pyramid and its dimensions are shown in the diagram. 10 ft 8 ft 12 ft What is the lateral surface area of the pyramid in square feet? A 384 ft? B 192 ft? C 160 ft? D 336 ft?​

The train is travelling at an initial velocity of 15 m/s. After 8 seconds, the train is travelling at a final velocity of 30 m/s. We need to calculate the acceleration of the train during this time period.

The formula for acceleration is given by the equation a = (v_f - v_i) / tWhere a is the acceleration, v_f is the final velocity, v_i is the initial velocity and t is the time taken .So, substituting the values we have: [tex]a = (30 - 15) / 8a = 1.875 m/s^2[/tex]Therefore, the acceleration of the train is [tex]1.875 m/s^2[/tex].The train is accelerating at a rate of 1.875 m/s^2. This means that every second, the train is increasing its velocity by 1.875 m/s. If the train continues to accelerate at this rate, it will reach a velocity of 60 m/s in 24 seconds.

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The percentage of data less than 61 on the box and whisker plot is given as follows:

100%.

A box and whisker plots shows these five metrics from a data-set, listed and explained as follows:

The metrics for this problem are given as follows:

The problem is given by the image presented at the end of the answer.

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The standard deviation of the number of aces is approximately 0.319.

To find the standard deviation of the number of aces, we first need to calculate the variance.

From Exercise 4.76, we know that the probability of drawing an ace from a standard deck of cards is 4/52, or 1/13. Let X be the number of aces drawn in a random sample of 5 cards.

The expected value of X, denoted E(X), is equal to the mean, which we found to be 0.769. The variance, denoted Var(X), is given by:

Var(X) = E(X^2) - [E(X)]^2

To find E(X^2), we can use the formula:

E(X^2) = Σ x^2 P(X = x)

where Σ is the sum over all possible values of X. Since X can only take on values 0, 1, 2, 3, 4, or 5, we have:

E(X^2) = (0^2)(0.551) + (1^2)(0.384) + (2^2)(0.057) + (3^2)(0.007) + (4^2)(0.000) + (5^2)(0.000) = 0.654

Plugging in the values, we get:

Var(X) = 0.654 - (0.769)^2 = 0.102

Finally, the standard deviation is the square root of the variance:

SD(X) = sqrt(Var(X)) = sqrt(0.102) = 0.319

Therefore, the standard deviation of the number of aces is approximately 0.319.

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The value of vector A is approximately 17.08.

To find the magnitude of a vector with components = 4.43 and = -16.5, you can use the Pythagorean theorem.

The formula for the magnitude of a vector (|A|) is:

|A| = √(x² + y²)

In this case, x = 4.43 and y = -16.5.

Plugging these values into the formula, you get:

|A| = √((4.43)² + (-16.5)²)

|A| = √(19.5849 + 272.25)

|A| = √(291.835)

Calculating the square root, you find that the magnitude of vector A is approximately 17.08.

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The Maclaurin series for f(x) as:

f(x) = ∑[n=0 to ∞] (a_n x^(2n+1) cos(1/7x^2) + b_n x^(2n) sin(1/7x^2))

To obtain the Maclaurin series for the function f(x) = 2x cos(1/7x^2), we first need to find the derivatives of the function at x = 0.

The Maclaurin series is then obtained by summing these derivatives multiplied by appropriate coefficients.

We start by taking the first few derivatives of the function:

f(x) = 2x cos(1/7x^2)

f'(x) = 2 cos(1/7x^2) - 4x^2 sin(1/7x^2)

f''(x) = 28x sin(1/7x^2) - 8 cos(1/7x^2) - 16x^4 cos(1/7x^2)

f'''(x) = -392x^3 cos(1/7x^2) + 56x^2 sin(1/7x^2) + 48x cos(1/7x^2) - 224x^6 sin(1/7x^2)

We can see a pattern emerging here: each derivative involves a combination of sine and cosine terms with increasing powers of x. To simplify the notation, we define:

a_n = (-1)^n (2/7)^(2n+1)

b_n = (-1)^n (2/7)^(2n)

Using these coefficients, we can write the Maclaurin series for f(x) as:

f(x) = ∑[n=0 to ∞] (a_n x^(2n+1) cos(1/7x^2) + b_n x^(2n) sin(1/7x^2))

This series involves both sine and cosine terms, with coefficients that depend on the power of x.

It is worth noting that the coefficients decrease in magnitude as n increases, which means that the series converges rapidly for small values of x.

However, as x becomes large, the terms in the series oscillate rapidly and the series may not converge.

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Answer:

x=42°

Step-by-step explanation:

angles around a point add to 360°

2x+3x+150=360°

take away 150°

2x+3x=210°

5x=210°

divide by 5

x=42°

Answer:

42

Step-by-step explanation:

2x+3x+150°=360°

collect like terms

2x+3x=360°-150°

5x=210°

divide both sides by 5x

therefore, x=42

The width of the path surrounding the garden is 1 meter.

To find the width of the path surrounding the garden, we need to factor the given area expression,[tex]4x^2 + 40x - 44,[/tex] and identify the value of x.
Factor out the greatest common divisor (GCD) of the terms in the expression:
GCD of[tex]4x^2,[/tex] 40x, and -44 is 4.

So, factor out 4:
[tex]4(x^2 + 10x - 11)[/tex]
Factor the quadratic expression inside the parenthesis:
We need to find two numbers that multiply to -11 and add up to 10.

These numbers are 11 and -1.
So, we can factor the expression as:
4(x + 11)(x - 1)
Since we are looking for the width of the path (x), and it's not possible to have a negative width, we can disregard the negative value and use the positive value:
x - 1 = 0
x = 1.

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The linear extension of l on s is {(1,3), (2,6), (5,), (1,5), (3,5)}.

The relation | on s = {1,2,3,5,6} means that two elements are related if they have the same parity (i.e., they are both even or both odd).
To find all linear extensions of | on s, we can first write down the pairs that are already related by |:
(1,3), (2,6), (5,)
We can then consider each remaining pair of elements and decide whether they should be related or not in a linear extension of |. For example, we could choose to relate 1 and 5, since they are both odd and do not currently have a relation.
One possible linear extension of | on s is:
{(1,3), (2,6), (5,), (1,5), (3,5)}

Note that there are several other possible linear extensions, depending on which pairs we choose to relate.

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Sonali purchased some pants and skirts the numbers of skirts is 7 less than eight times the number of pants purchase also number of skirt is four less than five times the number of pants purchased is 1 pant and 1 skirt.

Let's denote the number of pants Sonali purchased as P and the number of skirts as S. We're given two pieces of information:

1. The number of skirts (S) is 7 less than eight times the number of pants (8P). This can be represented as S = 8P - 7.

2. The number of skirts (S) is also 4 less than five times the number of pants (5P). This can be represented as S = 5P - 4.

Now we have a system of two linear equations with two variables, P and S:

S = 8P - 7
S = 5P - 4

To solve the system, we can set the two expressions for S equal to each other:

8P - 7 = 5P - 4

Solving for P, we get:

3P = 3
P = 1

Now that we know P = 1, we can substitute it back into either equation to find S. Let's use the first equation:

S = 8(1) - 7
S = 8 - 7
S = 1

So, Sonali purchased 1 pant and 1 skirt.

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Answer:

A'(-8,6)

B'(6,4)

C'(-8,0)

Step-by-step explanation:

 Since this transformation is a violation we can we can use the skill factor to multiply both the x-coordinate and the Y And the Y coordinate of the Of the point to make sure that everything is consistent and that the figures stay similar.

The maximum possible error is 2/3.

The Maclaurin series for cosine function is given by:

[tex]cos(x) = 1 - x^2/2! + x^4/4! - x^6/6! + ...[/tex]

Using the first three nonzero terms, we get:

[tex]cos(x) ≈ 1 - x^2/2! + x^4/4![/tex]

To estimate the error, we can use the Taylor remainder formula:

[tex]Rn(x) = f(n+1)(c) * (x-a)^(n+1) / (n+1)![/tex]

where f(n+1)(c) is the (n+1)th derivative of f evaluated at some value c between a and x.

In this case, we have:

f(x) = cos(x)

a = 0

n = 2

x = 2

To find an upper bound for the error, we need to find the maximum value of the absolute value of the third derivative of cosine function over the interval [0,2]. Since the third derivative of cosine is -cos(x), the maximum value of its absolute value is 1.

Therefore, we have:

[tex]|R2(2)| ≤ 1 * (2-0)^(2+1) / (2+1)![/tex]

≤ 4/3!

≤ 2/3

So the maximum possible error is 2/3.

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The period of the function in this problem is given as follows:

20 units.

A periodic function is a function that has the behavior repeating over intervals in the domain of the function.

Then the period of the function has the concept defined as the difference between two points in which the function has the same behavior.

Looking at the peaks of the function, they are given as follows:

Hence the period of the function is given as follows:

20 - 0 = 20 units.

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A good way to make sense of qualitative data is through quantitative analysis.

Qualitative data refers to non-numerical data that is descriptive, such as textual responses, interviews, observations, and open-ended survey questions. To make sense of qualitative data, quantitative analysis techniques are not applicable. Instead, qualitative data analysis methods are used.

Quantitative analysis is focused on numerical data and involves statistical techniques, such as linear regression, hypothesis testing, and data modeling. While these techniques are valuable for analyzing quantitative data, they are not suitable for analyzing qualitative data.

To make sense of qualitative data, researchers typically employ methods such as thematic analysis, content analysis, coding, categorization, and pattern recognition. These techniques involve organizing, coding, and interpreting the qualitative data to identify themes, patterns, and relationships.

Therefore, among the options provided, the most appropriate way to make sense of qualitative data is through qualitative analysis techniques rather than mental blocks, thinking units, or linear regression.

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The perimeter of the closet is 25.5 ft.

we have the scale

1 unit = 1.5 feet

Then the dimensions of closet are

3 unit = 3 x 1.5 feet = 4.5 ft

4 unit = 4 x 1.5 = 6 ft

4 unit =6  ft

6 unit = 6 x 1.5 = 9 ft

So, the perimeter of the closet

= 4.5 + 6 + 6 + 9

= 25.5 ft

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We have shown that [tex]cov(x_1, x_1) = v(x_1) = \sigma^2_1(x 1 ,x 1 ).[/tex]

To show that [tex]cov(x_1, x_1) = v(x_1) = \sigma^2_1(x 1 ,x 1 )[/tex], we need to first understand what each of these terms means:

[tex]cov(x_1, x_1)[/tex] represents the covariance between the random variable x_1 and itself. In other words, it is the measure of how two instances of x_1 vary together.

v(x_1) represents the variance of x_1. This is a measure of how much x_1 varies on its own, regardless of any other random variable.

[tex]\sigma^2_1(x 1 ,x 1 )[/tex]represents the second moment of x_1. This is the expected value of the squared deviation of x_1 from its mean.

Now, let's show that [tex]cov(x_1, x_1) = v(x_1) = \sigma^2_1(x 1 ,x 1 ):[/tex]

We know that the covariance between any random variable and itself is simply the variance of that random variable. Mathematically, we can write:

[tex]cov(x_1, x_1) = E[(x_1 - E[x_1])^2] - E[x_1 - E[x_1]]^2\\ = E[(x_1 - E[x_1])^2]\\ = v(x_1)[/tex]

Therefore, [tex]cov(x_1, x_1) = v(x_1).[/tex]

Similarly, we know that the variance of a random variable can be expressed as the second moment of that random variable minus the square of its mean. Mathematically, we can write:

[tex]v(x_1) = E[(x_1 - E[x_1])^2]\\ = E[x_1^2 - 2\times x_1\times E[x_1] + E[x_1]^2]\\ = E[x_1^2] - 2\times E[x_1]\times E[x_1] + E[x_1]^2\\ = E[x_1^2] - E[x_1]^2\\ = \sigma^2_1(x 1 ,x 1 )[/tex]

Therefore, [tex]v(x_1) = \sigma^2_1(x 1 ,x 1 ).[/tex]

Thus, we have shown that [tex]cov(x_1, x_1) = v(x_1) = \sigma^2_1(x 1 ,x 1 ).[/tex]

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