Orange juice isn't actually all that healthy. Many "natural" sugars are bound up with fiber, diluting them lowering their glycemic index. Also IIRC there was some research a few years back that asserted the ratio of different sugar types actually had a significant impact on the metabolism.
I used ML techniques to help smooth over some of the difficult parts (there are many difficult parts). The hardest cases are ambiguous names, for instance delineating Hispanic vs. Puerto Rican naming conventions (they're different). The fundamental approach involved pushing all ambiguity up to the end user, so they always have the option to correct the system.
I actually wrote an API for handling personal names, because software mangling people's names irked my pedanticism. The fundamental takeaway is that names are ridiculously complex, equivalent to any other part of natural language. For every rule you could contrive there are exceptions, and many more legitimately ambiguous cases.
You shouldn't ever use first/last name fields, because they force users to adapt around your system (many names don't follow this structure). A long unstructured text fields is best, because it can accommodate nearly anyone who's name can be spelled with unicode. Finally always check your interpretation of a name with the person in question, seeing as they're the end authority.
These exist in the US, but they're called black and white cookies. According to Wikipedia they may have been created in New York by Bavarian immigrants. But it's unclear if the confection's origin is German or American.
Not quite, I'm referring to american fritessaus, which is more like mayonaise, and distinct from thousand island dressing (which is popular in the US, In-N-Out calls it "spread").
Digging a little deeper it appears like McDonalds may have actually invented the sauce to appeal to the Dutch market, where fritessaus is popular (instead of tomato ketchup). Because McDonalds is American, their take on fritessaus grew into it's own thing called "American Fritessaus," or simply "American Saus."
Digging a little deeper it appears like McDonalds may have actually invented the sauce to appeal to the Dutch market, where fritessaus is popular (instead of tomato ketchup). Because McDonalds is American, their take on fritessaus grew into it's own thing called "American Fritessaus," or simply "American Saus."
Lol reminds me of Hawaiian pizza (pizza topped with pineapples and thinly sliced ham). Hawaiian pizza is actually a Canadian dish, though it's now popular in most of the US, including Hawaii.
You're certainly correct. But in this case it might bolster human specific pathogens. I know there is some overlap between human an animal pathogens, but unfettered access to antibiotics might accelerate the problem for humans specifically (which is probably worse than the current prescription only policy in the US).
What's your stance on antibiotics? Or did you only mean "recreational" drugs?
The reason why I bring this up is that antimicrobial resistance is an externality of widespread antibiotic usage. Unfettered access to all drugs would probably accelerate antimicrobial resistance, because people tend to overuse/abuse antibiotics when they have the freedom to.
(Not trying to be mean/inflammatory/pedantic, I'm genuinely curious how HN would reconcile these stances.)
I would honestly be surprised if this kind of link didn't have at least some measurable impact, physiology is hardly decoupled (in the coding sense). It's been well established that poor mental health (loss of will to live) correlates strongly with early mortality, even when controlling for obvious variables. Though establishing the causality on that is challenging.
There are lots of strange physiological links that aren't necessarily logical, due to the imperfect nature of natural selection (it strives for the local optima and "good enough," over the global optima). For instance it's well documented that consciously smiling improves mood, even though the causality is "backwards."
I did some interesting work in this space. With several thousand seasons of data I used an MLP network to visualize phenotypic plasticity (how plants react to a range of environmental conditions).
Accurately cleaning the input data proved to be extremely important, because there's a tremendous amount of "noise" at the individual level when dealing with living organisms, so lots of high-quality data is necessary to tease out relationships. Establishing causality was also important, considering the potential for confounding variables.
It also gave me a chance to brush up on my React/front end skills, but that was more ancillary.
I'm a huge fan of Django, but I always felt that this was true. I wish there was more of a push to decouple parts of the framework. Keep the magic, but allow usage without it.