Explanation:
Most of the users uses Windows. It still holds the title as world's most used operating system.
Answer:
The answer to this question is given below in the explanation section.
Explanation:
The correct answer to this question is: Online community technologies.
So, we can fill this question with the correct option as below:
<u>Online community technologies</u> are technologies that support virtual communities and the sharing of content with friends and family.
As we know that online community technologies are those technologies where people of the same group or interest make community virtually online. Where they can share their contents such as pictures, videos, thaught, ideas, etc with the group or family members.
There are different technologies that support virtual communities to share content with friends and family.
Such as Zoom meetings, Sk ype, Face book, Insta gram etc.
Answer:
A computer does not have brain of its own
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).
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