Hi guys recently gave `observe.ai` `oa` for sde-2 position partially solved 3 problems in 75 minutes if you have optimized solution for each one of the below would love to know your approach 1. Given an array err of n integers. for a triplet of indices `i[1],i[2],i[3] (1<=i[1]<=i[2]<=i[3]<=n)`. GrossValue(`i[1],i[2],i[3])=sum[1,i[1])-sum[i[1],i[2])+sum[i[2],i[3])-sum[i[3],n+1)`. Here `sum[l, r)(1<=l<=r<=n+1)` is the sum of all the elements in the subarray arr[l,r) i.e `sum[l,r) =(arr[l]+arr[l+1]+---+arr[r-1]`. Note that sum[1,1) is 0 as arr[1,1) is an empty subarray. Find out the maximum gross value of any valid triplet. Example arr = [-5, 3, 9, 4] Some gross value calculations i[1] i[2] i[3] gross value 2 3 4 -> (-5)-(3)+9-4=-3 1 3 4 -> 0-(-2)+9-4 =7 1 2 5 -> 0-(-5)+16-0=21 row 1--> `arr[1,2) - arr[2,3) + arr[3,4) - arr[4,5)` is shown. maximum possible gross value is 21 for indices {1,2,5} constraints: 1<=n<=3000 -10^9<=arr[i]<=10^9 --- 2. A learner is given a sequential playlist of n videos to enhance their knowledge, implement a function to calculate the minimum time required to complete a total of m viewings while adhering to the platform's constraints. System Constraints • Sequential Viewing: • The learner must watch videos in the order they appear in the playlist. • To watch a video at index i, the learner must first watch all videos from index O to i-1 at least once. • Initial Full Viewing: • To view any video at index i for the first time, the learner must spend `firstWatch[i] + repeatWatch[i]` minutes. This ensures a complete understanding of the video. • Subsequent Viewings: • For subsequent viewings of a video at index i, the learner spends only repeatWatch[i] minutes. • At any time, they can rewatch any video they have already watched. • Minimum Total Watch Count: • The learner must achieve at least `m` total viewings across all videos. • Videos can be rewatched as desired, and not all videos need to be watched equally. Language Return the minimum time required to complete m viewings of videos while following these constraints. Example if n = 4, m = 4, firstWatch = [1, 5, 9. 11], and repeatWatch = [2, 7, 10, 11], the optimal strategy is as follows: • The learner watches the Oth video for the first time, spending firstWatch[O] + repeatWatch[0]= 1 + 2 = 3 minutes. • The learner then rewatches the Oth video 3 more times, spending repeatWatch[0]*3 = 2*3 = 6 minutes. • The learner has successfully completed 4 viewings. Thus, the total time required is 3 + 6 = 9 minutes, and 9 is returned. Constraints • 1<=n<=10^5 • 1<=m<=10^9 • 1<=firstWatch[i],repeatWatch[i]<=10^9 --- 3. Given n employees, the time when the `ith` employee starts working is represented by the array `startTime[i]` and the time when they finish the work is represented by the array `endTime[i]`. The `ith` employee can interact with the `jth` employee if their working hours overlap. A team can only be formed if at least one employee of the team can interact with all other team members. Determine the maximum size of such a team. Example n = 5 startTime = [1, 6, 4, 3,1] endTime = [2, 7, 5, 8, 2]. ![graph.png](https://assets.leetcode.com/users/images/0ded39f5-b2a4-46f2-bca9-80eefc47627b_1750831293.727425.png) Consider the group [1, 2, 3]. Employee 3 can interact with other employees in the group, so a team of size 3 is possible. A team with more than 3 employees is impossible. Therefore, the answer is 3. Constraints: 1<=n<=2*10^5