<span>All of the following are parts of the word processing window except for the button esc ____.</span>
Answer:
word = input('Enter a single word: ', 's');
n = length(word);
nodupWord = [];
for i = 1:n
dup = false;
c = word(i);
for j = 1:i-1
if word(j) == c
dup = true;
break;
end
end
if ~dup
nodupWord = [nodupWord, c]; %add the non-duplicate char to end
end
end
disp(['Adjusted word: ', nodupWord])
Explanation:
The code is in Python.
Answer:
Resource Polling is the correct answer to the given question .
Explanation:
The Resource pooling is used in cloud computing frameworks that describe a situation where companies offer temporary and flexible resources to different clients .In the resource polling the programs can be changed to fit the needs of each client without making any adjustments visible to the client.
The main function of resource pooling that it grants a service provider the opportunity to dynamically allocate common physical resources to different clients based on the utilization criteria of each client.
Answer:
it would be amhv i think i hope it answered u'er question
Explanation:
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).
