Solving Coupled pde in comsol [closed] - equation-solving

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Does anyone know which module in comsol should I use to solve below equations?
$partial_t u1 = -a1 \div ((cos(s), sin(s)) u1) + a2 \div (u1 \grad (u2) )+ a3 \partial_s ((-sin(s), cos(s)) \cdot \nabla c u1) + a4 \nabla^2 u1+a5 \nabla^2 u1+a6 \partial_s^2 u1$
$\partial_t u2= a5 \nabla^2 u2 - k u2 u1$

COMSOL Multiphysics base package can solve these kinds of problems. There are many examples and tutorials on equation based modeling in COMSOL.
Equation based modeling in COMSOL

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Google Spreadsheet - Is there a way to overflow over blank cells [closed]

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I wonder if someone could help me fixing this issue
Planning to have nearly 100 columns to be viewable without scrolling horizontally, so each column shoud have 21 pixels's width, so it's for this reason I can't nor enlarge the columns neither merge themm...
I need that text in A2 overflow/overwrite over E2, F3, G3, H3 cells which are blank since the validation data in E3 is not selected
I want that A2 reacts exactly as I2 is doing by overwrites blank cells in front of it (M2...)
Could you help me fix this out? Any advice would be appreciated.
I share with you an example of my work
https://docs.google.com/spreadsheets/d/12bmwYSi3exkblW0C2VXqDTq5UGEd5GH8D1PsSkjaFNI/edit?usp=sharing
solution here is to unmerge A2:
update:
={"";IFNA(VLOOKUP($E$5,Sheet2!$A$2:$E$5,5,FALSE))}

Prove that AD->B using armstrong's axioms [closed]

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R(A,B,C,D) F={A->C, D->B}
using Armstrong's axioms how do I prove that AD->B?
what I currently have is: using augmentation if D->B and A is any subset of U, then AD->AB
but I'm not confident on that answer
Here is a simple proof:
1. D -> B by hypothesis
2. AD -> AB by augmentation of 1
3. AB -> B by reflexivity
4. AD -> B by transitivity of 2 and 3

Open-source system/service/database alternative to a search algorithm [closed]

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I have a custom algorithm (written in java) to search in a list of strings (A) the string that is the longest substring of another string (B) (the longest common substring alg it's not suited in this case because the list of strings is big 100k+ ).
EX:
B -> "sadsaf dsfsc adsa 4 sad3 dfa fgs adsafd"
A -> ["fdsdf dsa", "adsa", "4 sad3", "cdsdfds dsa", "cx d45"]
And the result is "4 sad3" since its a subtring of B and also is
longer than "adsa" which is also a substring of B
I'm trying to find an alternative to a search algorithm using a system/service/database in order to externalize this algorithm .
What i've tried till now is:
mysql but it's pretty slow and it requires at least a ssd and a powerful cpu
elasticsearch using percolate query which i didn't benchmark yet but seems promising
redis but i didn't found a way to replicate the alg using their syntax
So any suggestion regarding a system/service/database that can do this relatively decent in terms of performance is appreciated, since the more options i'll have then the better (faster) the solution will be.

What does this tip mean? [closed]

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I need to write such a program:
Write a program that will fill an array with 30 elements of type int randomly selected from range 0 to 10. Print the array content on the screen. Then count and print out how many times each value appears in the array (tip: histogram).
Can somebody explain what this tip means?
Histogram is a representation, you can look it up online. Simply put in your, showing an item and its frequency(no:of occurrences) in a pictorial form. Check this image
Number column has the items that are present in your array, and count column has number of times each of them occur in your array(frequency). Frequency adds up to your array size - 30. Representing an item with its frequency is a histogram. And the graph is a pictorial representation.
The tip tells you what printing representation(number and its count) is.

Database which has categorized the english words into matching emotion [closed]

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is there a database or api which has the categorized version of English words into the matching emotion?
e.g: - http://www.psychpage.com/learning/library/assess/feelings.html
One useful resource is the NRC Word-Emotion Association Lexicon compiled by Saif Mohammad. It lists the sentiments (positive, negative) and emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust) for around 14,000 English words.
I would take a look into the topic of http://en.wikipedia.org/wiki/Sentiment_analysis If you are good with doing it in Python take a look at this demo: http://text-processing.com/demo/sentiment/ Which is able to get if a sentence is positive or negative using NLTK.

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