Based on this data, can you please answer the following questions?

Multiple Choice #10: Has project #3 been approved (in our optimal solution)? A) Yes; this is one of the projects that has been approved. B) No; there is enough spare (aka slack aka extra) cash, but not enough spare personnel. C) No; there is enough spare personnel, but not enough spare cash to invest. D) No; there is neither enough spare cash nor spare personnel. Multiple Choice #11: Has project #8 been approved (in our optimal solution)? A) Yes; this is one of the projects that has been approved. B) No; there is enough spare (aka slack aka extra) cash, but not enough spare personnel. C) No; there is enough spare personnel, but not enough spare cash to invest. D) No; there is neither enough spare cash nor spare personnel. Multiple Choice #12: What is the total amount of cash used for all accepted projects? A) $ 480,000 B) S 250,000 C) $ 360,000 D) $ 225,000 Multiple Choice #13: What is the total amount of personnel used for all accepted projects? A) 36 B) 32 C) 40 D) 55 Multiple Choice #14: What is the total return obtained from all accepted projects? A) $ 495,000 B) S 330,000 C) $ 445,000 D) $ 570,000 Use the table below to answer the following question(s) by invoking the binary constraints on the variables using the standard Solver.l Below is the data for the spreadsheet for a project selection model: Project NPV (return) cash investment personnel requirements 1 75,000 30,000 10 2 50,000 45,000 5 3 25,000 75,000 10 4 85,000 30,000 4 5 50,000 45,000 8 6 25,000 75,000 7 7 95,000 45,000 6 8 25,000 60,000 1 9 75,000 30,000 2 10 65,000 45,000 2 You have $250,000 to invest and 36 people. Maximize NPV by approving/rejecting projects