Answer:
C++ code is given below
Explanation:
#include <iostream>
#include <cctype>
#include <string.h>
#include <cstring>
#include <sstream>
using namespace std;
struct Car {
public:
char reportingMark[5];
int carNumber;
string kind;
bool loaded;
string destination;
};
void input(Car *);
void output(Car *);
int main() {
Car *T = new Car;
input(T);
output(T);
delete T;
return 0;
}
void input(Car *T)
{
string str, s;
cout << " Enter the reporting mark as a 5 or less character uppercase string: ";
cin >> str;
for (int i = 0; i < str.length(); i++)
T->reportingMark[i] = toupper(str[i]);
cout << " Enter the car number: ";
cin >> T->carNumber;
cout << " Enter the kind: ";
cin >> T->kind;
cout << " Enter the loaded status as true or false: ";
cin >> s;
istringstream(s) >> boolalpha >> T->loaded;
if (T->loaded == true) {
cout << " Enter the destination: ";
cin.ignore();
getline(cin, T->destination);
}
else
T->destination = "NONE";
}
void output(Car *T)
{
cout << " Reporting Mark: " << T->reportingMark;
cout << " Car Number: " << T->carNumber;
cout << " Kind: " << T->kind;
cout << " Loaded Status: " << boolalpha << T->loaded;
cout << " Destination: " << T->destination << " ";
}
Answer:
accounting system
Explanation:
The most common response variable modeled for cropping systems is yield, whether of grain, tuber, or forage biomass yield. This yield is harvested at a single point in time for determinate annual crops, while indeterminate crops and grasslands may be harvested multiple times. Although statistical models may be useful for predicting these biological yields in response to some combination of weather conditions, nutrient levels, irrigation amounts, etc. (e.g., Schlenker and Lobell, 2010, Lobell et al., 2011), they do not predict responses to nonlinearities and threshold effects outside the range of conditions in data used to develop them.
In contrast, dynamic cropping and grassland system models may simulate these biological yields and other responses important to analysts, such as crop water use, nitrogen uptake, nitrate leaching, soil erosion, soil carbon, greenhouse gas emissions, and residual soil nutrients. Dynamic models can also be used to estimate responses in places and for time periods and conditions for which there are no prior experiments. They can be used to simulate experiments and estimate responses that allow users to evaluate economic and environmental tradeoffs among alternative systems. Simulation experiments can predict responses to various climate and soil conditions, genetics, and management factors that are represented in the model. “Hybrid” agricultural system models that combine dynamic crop simulations with appropriate economic models can simulate policy-relevant “treatment effects” in an experimental design of climate impact and adaptation (Antle and Stockle, 2015).
Answer: combine, control, and route audio signals from inputs to outputs
Explanation:
A audio mixer is refered to as the sound mixer or the mixing console and it's an electronic device that's used for mixing, and combining several audio signals and sounds.
The input to the console is the microphone. The audio mixer can also be used in controlling digital or analog signals. These are then summed up in producing output signals.
Therefore, the function of the audio mixer is to combine, control, and route audio signals from inputs to outputs.
