42 use the mo diagram given to find the bond order and predict whether h2- exists.

for example if x =4 , k=2 answer: yes number exists. and the number is 6 6= 2*3 (2 prime factors) 6 is divisible by 1,2,3,6 ( 4 factors) But the main problem is constraint. K can be 9 digits long. Any shortcut for that? Hello :) For my paper, I analyse how politicians use "happy" and "unhappy" words (regarding their connotation, so basically whether they have a positive and negative connotation). To do so, I have datasets with all the words two parties have used. This looks like that: https://preview.redd.it/hqwhrztvtf841.png?width=766&format=png&auto=webp&s=57260f44da2284aabaf3c132dabb0a375b124530 In coulmn B, one may find how often the word in C occurs. Column D shows the respective "happinn...

One text file has ~4800 and the other has ~2000 words. And each word is separated by a newline.

Use the mo diagram given to find the bond order and predict whether h2- exists.

I understand the concept. Basically make a more conical/bowl shaped "O'Neill Cylinder" on a moon/planet with lower gravity. The depth and shape of said habitat would depend on the local gravity, with it being more shallow the higher the local gravity (I think?). I just can't seem to find any good pictures, diagrams, or anything on this. Any help would be most welcome! Each test has can pass or fail, so a potential sequence can look like (test_id, p/f): (1, pass) ==> (4, fail) ==> (5, pass) ==> (6, pass) ==> (1, fail) ==> (4, pass). Which model should I use to predict the next one in the following: we executed the above ones and I want to know the prediction of each test failing after this one. I was thinking perceptron could be appropriate, but I'm not sure. k-means clustering I feel could work, especially if I want to add states other than...

Use the mo diagram given to find the bond order and predict whether h2- exists.. Each test has can pass or fail, so a potential sequence can look like (test_id, p/f): (1, pass) ==> (4, fail) ==> (5, pass) ==> (6, pass) ==> (1, fail) ==> (4, pass). Which model should I use to predict the next one in the following: we executed the above ones and I want to know the prediction of each test failing after this one. I was thinking perceptron could be appropriate, but I'm not sure. k-means clustering I feel could work, especially if I want to add states other than... I understand the concept. Basically make a more conical/bowl shaped "O'Neill Cylinder" on a moon/planet with lower gravity. The depth and shape of said habitat would depend on the local gravity, with it being more shallow the higher the local gravity (I think?). I just can't seem to find any good pictures, diagrams, or anything on this. Any help would be most welcome!

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