Answer:
Option D is correct i.e., =DATEDIF(C2, $AE$2, "y").
Explanation:
The user's supervisor well into the following department tells him to compose the feature which measures the amount that times staff has served in their company utilizing the DATEDIF feature. Consider whether C2 includes the hiring dates for that staff and then that cell $AE$2 includes the cut-off point for whom to evaluate the hiring time with the duration of the service.
So, therefore the following option is correct according to the given scenario.
Answer:
SAML.
Explanation:
SAML seems to be an accessible standardized XML-based for some of the sharing of validation and verification details and has been generally implemented for the web apps and it seems to be a design that would be SSO. Verification data is shared via XML documentation which are securely signed. So, the following answer is correct according to the given scenario.
Answer
can we get a picture of the problem ?
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).
