[1]: https://github.com/ente-io/ente/discussions/625

1. The Autogenous vaccine, where a veterinarian submits swabs of offending organisms to a lab that cultures and produces a vaccine specific to that strain to sell back to the clinic. Genomics play a role in determining if the currently circulating strains match the culture that the vaccine is based on.

2. The prescription platform vaccine, where genomic sequences are used to create a custom antigen that is produced in a microbial factory.

The efficacy of these types of vaccines is hotly debated because they do not have to go through clinical trial before distribution. The development of "commercial" (i.e. clinical trial-burdened) vaccines appears to have slowed based on my observations. While I think some of these new vaccines show promise, many autogenous and prescription platform vaccines are just more expensive versions of vaccines already available, or they package organisms that are suspected commensals and market it as something that no one else has done.

It's hard for me to call today a "golden age of vaccine development" in that light. I hope that the article is only taking human vaccines into account and that there is appropriate efficacy data for every vaccine shown in the last chart.

That is a very bold assumption, and I doubt the data supports it.

I couldn't find much published research on the correlation, just this one paper: https://journals.sagepub.com/doi/pdf/10.2304/plat.2009.8.2.5.... It shows no correlation between time on exams and final score, but its methodology is questionable.

A LaTeX or Typst document can contain both the content and formatting together within the same file. This isn't idiomatic for either language, and my experience is that this is more common for Typst than LaTeX, but both can do so. All of those formatting rules like small caps, table widths, margins, page numbering, etc.? Those can be rigidly defined in either LaTeX or Typst and are better guarded aginst accidental formatting rules breaches from double click, copy/paste, or table cell insertion than in Word.

I'm more sympathetic to the network effect argument. It's hard to envision a reasonable redline system compatible with both Docx and LaTeX/Typst.

But isn't the whole point of this article that Matlab is more readable than Python (i.e. solves the readability problem)? The Matlab and Julia code for the provided example are equivalent[1]: which means Julia has more readable math than Python.

[1]: Technically, the article's code will not work in Julia because Julia gives semantic meaning to commas in brackets, while Matlab does not. It is perfectly valid to use spaces as separators in Matlab, meaning that the following Julia code is also valid Matlab which is equivalent to the Matlab code block provided in the article.

    X = [ 1 2 3 ];
    Y = [ 1 2 3;
          4 5 6;
          7 8 9 ];
    Z = Y * X';
    W = [ Z Z ];

One thing that probably didn't help my understanding of channels was that I run Nix on non-NixOS systems (primarily MacOS and Fedora). If I'd stuck to NixOS, then thinking of a channel in the same terms as apt/sources.list or yum.repos.d would have been an easier mental model.

Agreed. I think flakes are far more intuitive than channels. In a flake everything is declared in the repo it's used in. I still don't understand channels.

For someone who's used to thinking in channels, I suppose flakes would be jarring. For someone (like me) who came from the world of Project.toml and package.json, flakes make a lot of sense.

- Zed editor with Typst plugin

- Tinymist LSP settings turned on to render on save in Zed, see https://code.millironx.com/millironx/nix-dotfiles/src/commit...

- Okular open to the output document. Okular refreshes the document when changed on disk.

It's not as polished as say, LaTeX Workshop in VSCode, but it gets the job done.

The docs recommend setting up KaTeX CSS (which requires either a CDN link or Node), but by changing output to 'mathml,' you can have the browser render equations with zero dependencies.

No, it's not "normal," but it is fairly common. When I worked in NGS, nearly 1/4 of flow cells were duds. ONT used to have a policy where you could return the cell and get a new one if it failed its self-test.

I know the governors of Wyoming gave land away to NCAR and Microsoft talking about how they were going to "diversify Wyoming's economy," and then every employee of those data centers was a contractor out of Colorado. The current governor has kept up the hype, now claiming that AI will be good for the local energy companies despite the fact that the proposed centers are going to be connected to out-of-state energy pipelines.

When you look at top campaign contributions and see Google and Microsoft at the top, you understand why the gubernatorial class keeps their ears plugged.

Except, this study didn't do that. It did shotgun sequencing and found a correlation between certain microbial species (some were fungal, not bacterial) and cancer risk. It *did not* demonstrate anything about mechanism.

Based on the way it's phrased, maybe this article is saying that previous studies have found a mechanism, and this study found the microbial culprits. Unfortunately, I don't have access to the full study to see if that's the case in its introduction or discussion. Even so, that's an incredibly misleading opening to the article.

This has been a handicap in my career where I would by default reach for a Raspberry Pi or a National Instruments RIO in places where an IC or a Arduino would suffice. Stuff like data acquisition units (DAQ) and control systems are prime examples. Maybe by giving those applications first? I can think of several projects my 12-year-old self would have found a use for a DAQ or control system.

I think I was about 12 when I got these, and I remember that the learning curve between them was pretty steep - I was building all sorts of custom circuits with Snap, but had maxed out the capabilities of such basic parts pretty quickly. I never did figure out how to make anything other than the step-by-step projects with the breadboard kit. Although the ICs on Snap are kind of laughable, I could at least figure out what they did (also I seem to remember every one of them just played a sound), but the Radio shack kit never really explained why anything worked the way it did or what the applications were outside of its recipes, so eventually it just went on the shelf and was forgotten. That would be one trap to avoid from my experience.

[1]: https://shop.elenco.com/consumers/snap-circuits-jr-100-exper...

[2]: https://www.amazon.com/RadioShack-28-280-Electronics-Learnin...