The researcher from Scenario I decides to compare a second dose-effect curve with carboxycotton to determine if the novel opioid has the capacity to induce tolerance (i.e., a rightward shift in the dose-effect function; a larger dose is required to produce the same effect). The researcher takes the carboxycotton-treated mice from the first experiment (subjects 6-10 from above) and administers cumulative doses of carboxycotton. He then measures tail withdrawal latency as before. On the following day, he administers cumulative doses of carboxycotton again to determine if tolerance development occurred. The results of this experiment are presented in the table below.

1. Write the name of the specific statistical test that is appropriate for these data: ______________________

2. Perform the test you identified inquestion 7 above using the statistical software (e.g., GraphPad Prism, Excel, R) of your choice. Be sure to perform a two-tailed test. Please round all answers to two decimal places, where appropriate.

1. Report the mean of differences between dose-effect curves: _______________
2. Report the standard deviation of differences between dose-effect curves: __________________
3. Report the standard error of the mean of differences between dose-effect curves: __________________
4. Report the results of the statistical test in the spaces below:

                        t( ____) = _____, p = _______

3. Report the 95% confidence interval (LL,UL) for the difference between dose-effect curves:

______________________

4. Compare the results from the 95% confidence interval in question 9 with the results from the statistical test in question 8. Is there sufficient evidence to reject the H₀ and claim that that there is a potency difference between the first dose-effect curve and the second dose-effect curve in carboxycotton-treated mice?

Yes or No (circle one)

In order to dispose of chemical waste, a waste ticket must be filled out listing all chemical components as a percentage.

This requires the use of conversion factors to convert the concentration of compounds into a percentage and list them on the waste ticket. When filling out waste tickets, each chemical is listed as less than or equal to ( ≦) its percentage. Water, or whatever solvent is used, is listed as ≧ the remaining percentage.

Us the information below, along with the information given in the prior questions for making Reagents A & B for nitrate assays to correctly fill out the waste ticket below.

Reagent A, the N-(1- Naphtyl) ethylenediamine solution (NNED Solution) contains 1 g L ^-1 NNED, as described in an earlier question.

Reagent B, the  S ulfanilamide  Solution, contains 10 g L  Sulfanilamide , and has an  HCl   concentration of 2.4 M as described in an earlier question. The formula weight of    HCl    is 36.46 g mole^-1.

Every sample is 8 mL, and shaken for 5 minutes with 0.1 g of cadmium powder prior to being mixed with 1 mL of Sulfanilamide solution and 1 mL NNED Reagent.

For this experiment, 60 samples and 5 standards were processed. The cadmium powder is insufficient to change the volume of the sample. Assume the samples have a total nitrate concentration ≦ 0.01%.

Given the above information, complete the waste ticket below for the chemical waste from performing Nitrate Assays in this experiment.  

Remember to consider the reagents were diluted when they were mixed with the sample.

Remember to calculate percentages as mass in grams over total volume (650 mL).

Round all answers to TWO decimal place.

Swift code

import Foundation

protocol TaksPerformer {

func doAThing()

}

class Employee: TaksPerformer {

let name: String

var boss: Boss?

init(name: String) {

self.name = name

}

func doAThing() {

print("\(name) is doing a thing")

}

}

class Boss {

var employee: Employee

let name: String

init(name: String, employee: Employee) {

self.name = name

self.employee = employee

employee.boss = self

}

func actLikeABoss() {

employee.doAThing()

}

}

// 1)

// A) What is wrong with the current implementation of Boss and Employee, why is it wrong, and how can we demonstrate that there is an issue?

//

// B) What pattern discussed in class does the Boss - Employee relationship remind you of? Give an example of the discussed pattern.

//

// C) Create a Person class that has the following property:

// let name: String

// Now have Employee and Boss inherit from Person

//

// D) You realize that there are speciffic tasks you would like an employee to perform. All tasks look like this:

// func makeCoffe(_ name: String) {

// print("\(name) made coffe")

// }

//

// func writeReport(_ name: String) {

// print("\(name) wrote a report")

// }

// Modify Boss, Employee and TaskPerformer in a way that a Boss can be instantiated with the following constructor:

// Boss(name: "Bossman", employee: anEmployee, tasks: [makeCoffe, writeReport])

// The employee instance should perform the tasks.

QUESTION 9

1. A 1,000-turn coil has a cross section of 7.0 cm ^ 2 and a length of 25 cm. Determine how much energy is stored in the coil's magnetic field when it has a current of 10.0 A.

a. 0.18 J

b. 0.36 J

c. 0.10 J

d. 28 J

e. 2.8 J

QUESTION 10

1. Determine which of the following types of waves is intrinsically different from the other four.

a. ultraviolet radiation

b. gamma rays

c. radio waves

d. visible light

e. sound waves

QUESTION 11

1. A circular copper cable is located perpendicular to a uniform magnetic field of 0.50 T. Due to external forces the cable area decreases at a ratio of 1.26 x 10 ^ -3 m ^ 2 / s. Determine the "emf" induced in the circular cable.

a. 7.9 x 10 ^ -3 V

b. 3.1 V

c. 1.2 x 10 ^ -3 V

d. 6.3 x 10 ^ -4 V

e. 3.1 x 10 ^ -4 V

QUESTION 12

1. A cable consists of 240 circular turns, each radius 0.044 m, and the current is 2.2 A. Determine the magnetic moment of the cable.

a. 23 Am ^ 2

b. 0.65 Am ^ 2

c. 15 am ^ 2

d. 0.21 Am ^ 2

e. 3.2 Am ^ 2

c. A protein called Merlin (Nf2) has been identified as a tumor suppressor. An explanation for its role as a tumor suppressor is likely found in Merlin’s influence on vesicular trafficking! Researchers labeled a v-SNARE with green florescent protein to monitor vesicular trafficking in cells lacking merlin protein. Why would monitoring a v-SNARE allow researchers to track vesicular trafficking? Rubric (2): explanation shows understanding of where vSNARES are present in the cell.

Answer: Once a vesicle is formed with its cargo inside, there is a v-snare protruding from the vesicle. By labeling the v-snare, the researchers could monitor the path of the vesicle from when the vesicle is released by coat assembly to when the v-snare and t-snare interact and fuse the vesicle and target membrane. This occurs during vesicular transport from the donor membrane to the target membrane.

e. The researchers found that anterograde vesicular transport was slower in cells with no Merlin protein present. This suggests that Merlin regulates motor protein function. Which type of motor protein might be affected by Merlin? Rubric (2): correct motor protein.

f.   Merlin slowed vesicular transport by influencing motor protein function. Hypothesize as to how Merlin might slow the walking of a motor protein. Rubric (2): all plausible answers get full points!

Let X1,X2,...,Xn be a random sample from a uniform distribution on the interval (0,a). Recall that the maximum likelihood estimator (MLE) of a is ˆ a = max(Xi).
a) Let Y = max(Xi). Use the fact that Y ≤ y if and only if each Xi ≤ y to derive the cumulative distribution function of Y.
b) Find the probability density function of Y from cdf.
c) Use the obtained pdf to show that MLE for a (ˆ a = max(Xi)) is biased.
d) Say I would like to consider another estimator for a, I will call it ˆ b = 2 ¯ X. Is it unbiased estimator of a (show)? How you can explain someone without calculations why ˆ b = 2 ¯ X is a reasonable estimator of a?
e) Based on the result in (c), I will propose to use unbiased estimator for a instead of ˆ a = max(Xi), say ˆ c = n+1 n max(Xi). Given that the relative efficiency of any two unbiased estimators ˆ b,ˆ c is the ratio of their variances
V ar(ˆ b) V ar(ˆ c)
,
explain which of these two unbiased estimators is more efficient. You can obtain the V ar(ˆ c) = V ar(n+1 n max(Xi)) from V ar(ˆ a) = Var(Y ). The variance of the Y = max(Xi) is
Var(Y ) =
n/( (n + 1)^2(n + 2))*a^2

Consider the utility functions of three individuals: u(x) = x^1/2, v(x) = ln x, and h(x) = x – 0.01 x², where x represents wealth.

Consider also the following lotteries: X = (w₀ + x₁, w₀ + x_2, w₀ + x_{3; ¼, ½, ¼ )} = (4, 16, 25; ¼, ½, ¼), where w₀ = $2, and lottery Y in which w₁ = $10, so that Y = (12, 24, 33; ¼, ½, ¼). Note that Y = X + (10; 1)

1. Tell whether u(x), v(x) and h(x) are risk averse, risk neutral or risk lovers individuals.

2. Compare individuals u(x) and v(x) with respect to their degree of risk aversion. Tell who is more risk averse.

3. Calculate the risk premium of individuals u(x) and v(x) with respect to lottery X. Did you obtain that the risk premium of v((x) is larger than that of u(x)? Is that result expected? Why?

4. Compare the risk premium of individual u(x) with respect to lotteries X and Y. Did you obtain that the risk premium with respect to lottery X is larger than that with respect to Y? Is that result expected? Why?

5. Compare the risk premium of individual h(x) with respect to lotteries X and Y. Did you obtain that the risk premium with respect to lottery X is larger than that with respect to Y? Is that result expected? Why?

1. Determine the current in the circuit by calculating the current in the resistor. Note: We will use I (and V_R since it has the same phase) for reference throughout our analysis (V_R/R = I).

2. Determine the capacitance of the circuit from its reactance, the current calculated above, and the frequency of the source (V_C/I = X_C).

3. Determine the inductance of the circuit from three different voltage measurements, the current calculated in step 1, and the frequency of the source, following the instructions below carefully (this can be complicated).

1. Determine the phase of V_LR with respect to V_R using the law of cosines (V_Lr²= V_LR² + V_R² – 2V_LRV_R cos(α)).

2. Determine the fraction of V_LR due to V_L alone (V_L = V_LRsin(α)).

3. Determine the inductance of the circuit from its reactance using the current determined in step 1 and the V_L determined above (V_L/I =X_L).

4. Determine the loss in the inductor and write it as a resistance using the current found in step 1

            (V_r = V_LRcos(α) – V_R and r = V_r/I).

4. Determine the phase between the source voltage and the current (φ = tan^-1 [(V_L – V_C)/(V_R+V_r)]).

5. Calculate the resonant frequency of the circuit from the values you determined for L and C

Assume you wish to evaluate the risk and return behaviors associated with various combinations of assets V and W under three assumed degrees of​ correlation: perfect​ positive, uncorrelated, and perfect negative. The following average return and risk values were calculated for these​ assets:
Asset   Average Return, {r}}   Risk (Standard Deviation), s
V   7.6%   4.7%
W   13.2%   9.4%


a. If the returns of assets V and W are perfectly positively correlated​ (correlation coefficient equals plus 1 ​), describe the range of​ (1) return and​ (2) risk associated with all possible portfolio combinations.
​(1) Range of expected​ return: between % and % ​(Round to one decimal​ place.)

​(2) Range of the​ risk: between % and % ​(Round to one decimal​ place.)

b. If the returns of assets V and W are uncorrelated​ (correlation coefficient equals 0 ​), describe the approximate range of ​(1​) return and​ (2) risk associated with all possible portfolio combinations.

​(1) Range of expected​ return: between % and % ​(Round to one decimal​ place.)

​(2) Range of the​ risk: between % and % ​(Round to one decimal​ place.)

c. If the returns of assets V and W are perfectly negatively correlated​ (correlation coefficient equals negative 1 ​), describe the range of​ (1) return and​ (2) risk associated with all possible portfolio combinations.

​(1) Range of expected​ return: between % and % ​(Round to one decimal​ place.)

​(2) Range of the​ risk: between % and % ​(Round to one decimal​ place.)

Can someone please tell me why I am getting errors. I declared the map and it's values like instructed but it's telling me I'm wrong.

#include <iostream>
#include <stdio.h>
#include <time.h>
#include <chrono>
#include <string>
#include <cctype>
#include <set>
#include <map>
#include "d_state.h"
using namespace std;
int main()
{

string name;
map<string,string> s;
map<string,string>::iterator it;

s[“Maryland”] = "Salisbury";
s[“Arizona”] = "Phoenix";
s[“Florida”] = "Orlando";
s[“Califonia”] = "Sacramento";
s[“Virginia”] = "Richmond";
cout << "Enter a state:" << endl;
cin >> name;
if( !name.empty() )
{
    name[0] = toupper( name[0] );

    for( int i = 1 ; i < name.length() ; i++ )
        name[i] = tolower( name[i] );
}
/*it = s.find(name);
if (it != s.end())
{
    cout << name << ", " << s[name] << endl;
}
else
{
   cout << name << " is not in the set" << endl;
}*/

    return 0;
}