stdbrouw

It doesn't really need any config on most distros, no.

That said, if you want it to behave at its best when OOM, it does help to tweak vm.swappiness, vm.watermark_scale_factor, vm.min_free_kbytes, vm.page-cluster and a couple of other parameters.

See e.g.

https://makedebianfunagainandlearnhowtodoothercoolstufftoo.c...

https://documentation.suse.com/sles/15-SP7/html/SLES-all/cha...

I don't know of any good statistics script for zswap, I use the script below as a custom waybar module:

  #!/bin/bash
  stored_pages="$(cat /sys/kernel/debug/zswap/stored_pages)"
  pool_total_size="$(cat /sys/kernel/debug/zswap/pool_total_size)"
  compressed_size_mib="$((pool_total_size / 1024 / 1024))"
  compressed_size_gib="$((pool_total_size / 1024 / 1024 / 1024))"
  compressed_size_mib_remainder="$((compressed_size_mib * 10 / 1024 - compressed_size_gib * 10))"
  uncompressed_size="$((stored_pages * 4096))"
  uncompressed_size_mib="$((uncompressed_size / 1024 / 1024))"
  uncompressed_size_gib="$((uncompressed_size / 1024 / 1024 / 1024))"
  uncompressed_size_mib_remainder="$((uncompressed_size_mib * 10 / 1024 - uncompressed_size_gib * 10))"
  ratio="$((100 * uncompressed_size / (pool_total_size + 1)))"
  echo "$compressed_size_gib.$compressed_size_mib_remainder"

You don’t get more income, but you do get more disposable income.

You don't have to pay VAT on things you fix for yourself, because you don't pay yourself at all. This is in fact a kind of (legal) tax avoidance, but not (illegal) tax evasion. Given the cost of housing, being able to build your own house or even just doing small fixes here and there, leads to a big increase in perceived income. The tradies I know can afford whatever kind of car they want, whatever kind of holiday experience, and they live in a nice home. Mind you, they typically work 50h+ a week so there's that.

Of course, the parent may also have been referring to getting clients to pay in cash and not putting anything on the books, at the expense of getting barely any pension in the end, but that's not how I read it. This is getting somewhat less common because people are more likely than 20 years ago to get a loan from a bank to pay for renovation work, and the bank will want to see invoices.

Well, it implies that the "grassroots" element of it is fake, the message itself being false is optional.

Doesn't this argument hinge on equivocating between two different definitions of aversion, though? I'm averse to bananas, but that doesn't mean I think it's immoral to eat them. The moral dimension kicks in if somebody else had to ride that stationary bike for you, because then you'd be wasting their time on frivolities.

So if I send an email that lacks a feature that MUST be there, will the email police come get me? At a certain point, looking for an analogy stops making sense I think.

One of the things I like most about CachyOS is that the configuration is all just in text files, one of the things I like least is that I am never quite sure whether to modify the systemd unit settings that are usually in /usr/lib somewhere, the app settings in /etc or the personal configs in ~/.config. For packages that I am unfamiliar with, I usually end up trying all three locations until I notice that my changes seem to stick.

The installer also completely broke the Windows partition that came with the workstation even though I was planning on dual booting, but oh well, no great loss there.

Other than that, there are some small conveniences and apps that I miss from MacOS (the mac calendar and mail apps are just so nice!) but the Niri window manager is just so amazing that at this point I don't think there's anything that could make me switch back.

Hah! Thanks for the correction.

Cute and thus worthy of an upvote, but whenever I see scientists or economists refer to first or second order effects it pertains to things that are subsequent to each other in time, or at least intended vs. ancillary. I don't think anyone except for a Stafford "the purpose of a system is what it does" Beer acolyte would designate new demand of pill bottles as the first order effect of a new medication.

It's just something that statisticians have observed across many fields: you theorize about how potentially huge a particular interaction effect or knock-on effect could be relative to the main effect, you read about the Jevons Paradox and intuitively feel that it can explain so much of the world today... and then you get the data and it just almost never does. No reason why it couldn't, just empirically it rarely happens.

The thing about second order effects is that they are almost never larger than the first order effect.

Furthermore, GLP-1 users report having fewer cravings or just reduced appetite in general, whereas what you describe would require some sort of "calorie reduction pill" which would allow people to lose weight without altering their relationship to food. But that pill does not exist.

(Generalized) linear models have a straightforward probabilistic interpretation -- E(Y|X) -- which I don't think is true of total least squares. So it's more of an engineering solution to the problem, and in statistics you'd be more likely to go for other methods such as regression calibration to deal with measurement error in the independent variables.

I feel like all of the elements are there: zram, zswap, various packages that improve on default oom handling... maybe it's more about creating sane defaults that "just work" at this point?

Yeah, I didn't want to be contrary just for the sake of it, the heuristics you mention seem like good ones, and if followed would probably already cut down on quite a few superfluous references in most papers.

Do you still feel the same way if the froiznok method is an ANOVA table of a linear regression, with a log-transformed outcome? Should I reference Fisher, Galton, Newton, the first person to log transform an outcome in a regression analysis, the first person to log transform the particular outcome used in your paper, the R developers, and Gauss and Markov for showing that under certain conditions OLS is the best linear unbiased estimator? And then a couple of references about the importance of quantitative analysis in general? Because that is the level of detail I’m seeing :-)

The idea that references in a scientific paper should be plentiful but aren't really that important, is a consequence of a previous technological revolution: the internet.

You'll find a lot of papers from, say, the '70s, with a grand total of maybe 10 references, all of them to crucial prior work, and if those references don't say what the author claims they should say (e.g. that the particular method that is employed is valid), then chances are that the current paper is weaker than it seems, or even invalid, and so it is extremely important to check those references.

Then the internet came along, scientists started padding their work with easily found but barely relevant references and journal editors started requiring that even "the earth is round" should be well-referenced. The result is that peer reviewers feel that asking them to check the references is akin to asking them to do a spell check. Fair enough, I agree, I usually can't be bothered to do many or any citation checks when I am asked to do peer review, but it's good to remember that this in itself is an indication of a perverted system, which we just all ignored -- at our peril -- until LLM hallucinations upset the status quo.

Arguably Spark solves a problem that does not exist anymore: single node performance with tools like DuckDB and Polars is so good that there’s no need for more complex orchestration anymore, and these tools are sufficiently user-friendly that there is little point to switching to Pandas for smaller datasets.

In the US income from a hobby can just be added to your personal filing [1] and in Belgium, where I live, there is a similar arrangement for "diverse sources of income" [2]. If you do start a business, in the European Union you're exempt from filing VAT if your yearly revenue is below a certain amount [3]. Europe has also been pretty aggressive in getting rid of licensing requirements for various occupations and trades, certainly a photographer wouldn't need a license here.

I think the trouble you faced, resulted from being at the edge of these kinds of simple systems that do exist -- big enough to need to set up a business, but small enough that hiring an accountant or spending time to familiarize yourself with the legal requirements was out of proportion to the expected revenue. That's unfortunate, of course, but doesn't necessarily reflect on the amount of red tape that exists in general in a country.

[1] https://www.irs.gov/newsroom/heres-how-to-tell-the-differenc...

[2] https://www.vlaanderen.be/economie-en-ondernemen/een-eigen-z...

[3] https://europa.eu/youreurope/business/taxation/vat/vat-exemp...

Yeah, the intention to treat design is a particularly nice touch, not so common outside of biostatistics. They also compare the full cost of Montessori vs. plain ol', not the cost to the state, which could otherwise have given the Montessori schools (which are in wealthier neighborhoods on average) an unfair advantage if they have a lot of parents chipping in with donations and help. I've skimmed through the methods section and it does seem like they've gone to great lengths to allow for a fair comparison.

That doesn't necessarily mean the result will extrapolate, though. It seems plausible that teachers in Montessori schools are more motivated and knowledgeable than the average teacher and have made a conscious decision to teach in such a school. If every public school were to become a Montessori school, you would still get the cost savings (student-to-teacher ratios are higher in Montessori!) but you might lose that above-average enthusiasm and expertise and so the learning gains might not carry over. It's just really hard to know whether something might generalize in the educational sciences.

... but the key thing is that I am not saying that you are an old man who yells at the clouds, rather that a lot of people worry about themselves that they might be getting unduly close-minded and that this is what the blog post is trying to address.

Your mileage seems to vary, but I find that for food and drinks in particular it's the acquired tastes you get the most enjoyment from in the end -- I haven't met many people who enjoyed their first glass of peated whisky, for example. Heck, even my best friends are definitely an "acquired taste", as is obvious to me when I introduce them to other people I know.

If there is an ideal amount of some personality trait then for most people the advice would be "do more of this" even though for some others it'll have to be "do less of this" depending on where you're coming from. When I was young I definitely did a bit of over-socialization (everybody seems to like music festivals so I guess I must like them too if I don't want to be a weirdo?) but as you can see in the comments to this post, as we get older it's easy to get into a pattern where anything you're not familiar with is instantly met with suspicion or derision, and a lot of people don't like this about themselves, which is why this blogpost resonates with them.

Also, "liking something intrinsically", what does that even mean?

Even so. I read a lot of reports about educational policy (and occasionally produce them) and even if there are only 2-3 major decision makers you'd expect the report to be read by various cabinet members of those decision makers, by committee members in parliament, by academics, by other teams or colleagues or institutions that would have liked to write the report in your stead or that produce "competing" reports, by folks at think tanks, and by journalists and politicians in general. Because the executive summary is almost always inlined in these kinds of reports, the intended audience is generally quite broad. I'm not saying that attaining only a couple hundred downloads of a report necessarily show that money was wasted on superfluous research, but it definitely can be an indicator of waste.

I think this is one of those things where you can really overthink it and convince yourself that "the report was read only once, by the one person who had to read it" is an ideal outcome, but really it isn't.

> Then again, this is nothing like the type of problems I work on a daily basis.

I thought it'd be fun to take a stab at it in Python, which I haven't used in a while, but only barely still remembered that I could accept command-line input with the built in `input` function, something I don't think I ever used after writing my first lines of code 15 years ago. Then I figured I'd use just lists instead of a numpy array but had forgotten that [[0] * 4] * 4 would just create 4 references to the same list. And that pretty much derailed the whole thing for me, even though I was sure I'd get it done in 25 minutes or under :-)

I did a plastering course last winter and spring, and it reminded me about how, when you're young and in high school or college, you are continually confronted with not knowing things and not being able to do things that you would very much love to be able to do, and sometimes having to spend weeks or months without feeling much advancement before you suddenly "get it"... which is a kind of patience and stubbornness you rarely need once gainfully employed. It took months before I finished a wall that looked half decent, but then another month went by and suddenly everything had a mirror smooth finish. Your hands and arms and eyes notice things they didn't notice before. It reminded me that if you are willing to put in the hours, humans can do pretty amazing shit, and that you should never stop learning.

See https://www.amnesty.org/en/latest/news/2022/09/myanmar-faceb...

Sure, but I think the bigger point is that, if you've got a really great and really useful product, why would you need to convince people to use it by highlighting barely realistic use cases and exploiting their fears and anxieties?

This advice is insane. Except in specific settings (where a sensor may be misbehaving, where a survey respondent clearly just picked random choices) outliers are really just outlying values and should be kept in the analysis, or at most clipped / winsorized. When submitting to a scientific journal, admitting that outliers were removed without first inspecting why they are there can be enough for an instant rejection, and rightly so.

I wonder if it's really that rare for lawyers to look at a case from a strategic / economic point of view? When at some point in the past I was considering suing a company for breach of contract, that was pretty much what the entire initial conversation with our lawyers was about: they considered the timeline, probability of winning, costs for the lawyer'ing, costs for external experts, ability to recoup legal costs if successful or to incur those of the counterparty if not, ability of the counterparty to pay, alternatives to litigation and so on.

After about a day of prep work on my part, having them read through that prep work for about an hour and then discussing it with me for another hour, we concluded that the expected outcome was break even, with a time investment that was decidedly not break even, and did not proceed to litigation. They really helped our company to look at the problem objectively and without emotion, and I really hope that's not a rare experience!

(That said, I do understand that strategies for successfully dealing with being sued might need to get a bit more creative than those for deciding whether to sue.)

One way to illustrate some of the weirdness of dB is to look at the documentation of unit libraries, e.g.:

https://pint.readthedocs.io/en/stable/user/log_units.html

https://painterqubits.github.io/Unitful.jl/v0.7/logarithm/

Ah yes, I read "STM" and immediately figured it was one of those old school very low MHz microcontrollers but apparently those are available with ARM cores too... possibly had 'em confused with AVR/ATmega.

I'm a bit confused about the Pyboard. Do people buy Pyboards instead of ESP32 in order to support the project, or because they are more featureful, or both? Why does the Pyboard have a CPU in addition to the microcontroller, does the microcontroller only deal with IO?