sojournTime @sojournTime@social.cleverlibre.org

@firewally would have loved to see anti-gerrymandering laws or ranked choice voting listed too...

@jalefkowit I feel called out...

@cweickhmann ironic given SAP is a German company...

@teledyn this where I first learned about dark patterns:

https://youtu.be/kxkrdLI6e6M

@cweickhmann first off, please don't misquote me. I did not say "one acre is the area of one acre". Second, I think you took my comment out of context. I was just answering @trinsec's question on what an acre-foot is. I made no judgement on whether an acre-foot was a good unit of measurement.

I know dunking on Americans' use of the imperial system is an international pastime, but please don't insult Rhode Island. If you're gonna make fun of a state, do it properly: make fun of New Jersey 😉.

PS - Fun fact: Rhode Island had the longest official state name: "State of Rhode Island and Providence Plantations". Then in November 2020, the people voted to drop the "and Providence Plantations" from the name. So, for a long time, Rhode Island was the smallest state with the longest official name!

@trinsec @cweickhmann yes, an acre-foot is the area of one acre times a depth of one foot:

https://en.m.wikipedia.org/wiki/Acre-foot

@rastinza This looks like what you're looking for:

https://discourse.julialang.org/t/python-to-julia-transpiler/21473

@rastinza I'm not too well versed in the chemistry/bioinformatics side, but briefly looking into RDKit for Julia looks like that they simply added a C API for any programming language, so any limitations with RDKit in Julia would be with the API:

https://chembl.blogspot.com/2021/05/julia-meets-rdkit.html?m=1

@rastinza In general, Julia has a lot of libraries similar to Python and is definitely catching up in the realm of data science. I will say though that Julia is far ahead in differential equations solvers:

https://www.stochasticlifestyle.com/comparison-differential-equation-solver-suites-matlab-r-julia-python-c-fortran/

@peterdrake so I can't say I prefer R, but I do like some aspects of it. So, a little bit of background: I did most of my undergraduate and masters research using R, particularly data mining biometric data for UX/UI experiments. I wasn't introduced to Python and Jupyter notebook until my last semester of my masters degree, and I've been using them ever since for my work and research.

R has what I call the anti-Pythonic philosophy: there are many packages/libraries that do the same thing. It was design for statistics first and foremost, hence the index starting at 1 and the multitude of statistical packages. This is particularly acute with statistical tests. One anecdote that I have was I found the same statistical test (believe it was Tukey's range test) in both Baylor's psychology statistical package and another stats package. Also, academia tends to make and publish their own statistical packages in R based on their research, though this has changed a lot, especially now that Python and Julia are more popular. However, despite R's anti-Pythonic philosophy, there is a more Pythonic push with Tidyverse ( https://en.m.wikipedia.org/wiki/Tidyverse).

One of the positives that I like about R is that it (probably) has every type of statistical model you could want. For my regression class, I created an ordinal logistic regression model for my final project, which was only possible to do in R at the time (I believe I used polr). Python now has ordinal regression in statsmodels, but this was very recent and may not be as expansive as polr. I will say though that rpy2 has made package deficiency in Python less of an issue, but it still takes downloading and understanding R packages.

tldr; R's one shining positive is that it (probably) has every statistical model and test you can name, no matter how obscure it is.

@peterdrake @Placholdr

Alright, I figured it out based on @peterdrake 's hint. You'll find that any integer ending either in 1 or 9 squared has to be a number divisible by 20 plus 1 (20a+1 where a is a natural number). This can be done by multiplying out \((10n+1)^2\) and \((10n+9)^2\) where \(n\) is a natural number. It should be pretty straight forward from there.

Since no number from the sequence \(\{a_k\}\) follows this, then by contradiction, \(\{a_k\}\) cannot be a perfect square.

@peterdrake @Placholdr

I agree, this is probably the best method.

Another observation I made was that perfect squares can be expressed as the sum of odd numbers, so maybe that can help since the sequence /({a_k}/) can be described as /(\sum\limits_{i=0}^{2k-1}10^{i}/).

@rastinza

So I think context matters in this case. In my opinion, the fact that she was getting messages once the pandemic hit probably indicates she did not willingly share her Instagram with these people. Thus, it seems like a bit of an invasion of privacy to simply just message her out of the blue on a platform she did not share with you. Think of it as having your phone number publicized without your consent.

Again, context is key. If she verbally shared her Instagram with them, then maybe I wouldn't classify this as harassment. But based on the context, it seems like she didn't.

@rastinza

The fact that people were messaging her over Instagram to ask her out is kind of excessive. Also, the fact that when she met with HR, they hadn't heard of any of her incidents despite reporting them almost immediately after they occurred. That's a big red flag for HR, especially for a large company like SpaceX.

I know flirting is a delicate line to toe, but it seems like all of these incidents crossed a line. These incidents definitely fall under harassment, at least in my opinion.

@ColinTheMathmo

This is cursed...

@christianp @narain

Alright, so I went over my code with a colleague, and he found an error in my code (forgot to round my floating number before converting to integer). My original number of solutions (41,846) still holds, but my probability and combination calculations were off. My current probability now matches the simulation number of approximately 14.2%. I have uploaded my code and solution on GitHub here:

https://github.com/dataNerd23/52_card_sum_problem

The following is an updated screenshot of my solution: