"You can suddenly have a neighbor or a apartment in the same building become a revolving door for strangers who don't care about the community, who are giving money to landlords who simply aren't present."
i currently live in an apartment with two full time airbnb units (out of 6); the two units are over-occupied (each advertising 16 guests in what should be a 2 or 3 person apartment). the airbnb host has an agreement with the landlord, where they pay the landlord an extra 30%/40% a month per unit and get to run their airbnb. none of the neighbors particularly like the airbnb units or the guests and our building is now known as the "airbnb building" on our block.
i've talked to the landlord (who is mostly absentee), the host (who runs 5 airbnbs) and to airbnb (through their official channels) and no one will budge (on lowering the number of guests) or concede that living next to a full time airbnb with 16 guests is terrible.
in the future, i will not live / rent a property that is being managed solely as an investment / way to earn money for the landlord and will pay special attention to any airbnbs nearby before moving in. aside from the noise and usual complaints you'd expect from having an airbnb as a neighbor, one particular side effect is that it reduces the neighborhood social-ness (compared to the previous places i've lived). our living space is actually more closed off because there is a steady stream of large groups of strangers in our building.
i had a similar issue with mongo and time series data. for special purpose event data like that gist, i think you should consider using a column store.
this study is a cross sectional study of 15k people, but they only actually used something like 1.3k of those individuals in order to match up to the ~330 vegetarians to a person from a different group. (that is 13k discarded survey results...)
this type of cross sample matching (where the majority of the individuals polled are tossed away) is suspect, as is the time it took to conduct the survey and release the results (2007 is when the survey concluded, the study wasn't released until 2014).
imo, the writer of the blog post should extend a critical eye to academic studies (and see where they could be improved), instead of re-posting them as troll bait (and leaving out important scientific notions, like: we can't extrapolate from this study)
can install with 'pip install autolux'. uses imagemagick, xdotool and xbacklight. please make it better