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pidge

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Our core innovation is a radiative cooling material that we’ve combined with a panel system to improve the efficiency of any vapor-compression based cooling system

A heat pump is a “ vapor-compression based cooling system” so that tech is an addition-to not an instead-of.

Whether it’s better probably depends on how expensive the additional efficiency is in practice.

SkyCool’s Panels save 2x – 3x as much energy as a solar panel generates given the same area.

So if you’re area constrained maybe.

Yeah, given that everything is now multi-core, it makes sense to use a natively parallel tool for anything compute-bound. And Spark will happily run locally and (unlike previous big data paradigms) doesn’t require excessive mental contortions.

Of course while you’re at it, you should probably just convert all your JSON into Parquet to speed up successive queries…

Following the numbered citation, I think this is the table of contents from a different book, originally published in Finnish by Jaak Henno, which would have an English title something like “It is simple with Prolog!”. He also seems to have published some of the content separately under the title “Prolog and Olympic Gods”.

http://staff.ttu.ee/~jaak.henno/publicat.htm

Yes, you should be able to tell your direct manager basically what you told us. Copy and paste into an email if that’s easier. (Your tone here is fine.)

It does sound like your manager’s manager has poor people skills / favors a more confrontational management style. If you have a good direct manager that can be tolerable, up to you to decide how much it bothers you.

Unfortunately there’s not a control arm here. Looks like maybe original design was to determine effect of the additive as treatment, with sodium bicarbonate as the control. But both arms were significantly different than the population average, leading to this publication.

Given that it’s hard to know if selection bias slipped in anywhere, for example during recruiting:

During the study period, 826 unique patients aged 55 and older were eligible to be contacted within 24 hours of a positive PCR; 79 were able to be enrolled and receive irrigation materials on the day of contact.

To clarify, they implemented the algorithm in Dafny, and then proved that version correct. They did not verify code that will actually run in production.

From the paper:

Dafny is a practical option for the verification of mission-critical smart contracts, and a possible avenue for adoption could be to extend the Dafny code generator engine to support Solidity … or to automatically translate Solidity into Dafny. We are currently evaluating these options

A literal one that I probably picked up from another comment section here:

Treat your closet as an LRU cache—always put clothes away on one side, and start looking for items from the same side. As an added benefit when you run out of capacity, anything that has ended up on the far side is a likely candidate to be evicted to a higher latency storage layer (bins in the attic), or simply deleted and recomputed if ever needed again (just drop it off at Goodwill, you can always buy another).

Incidentally, there’s actually a map projection where all “great circle” routes (shortest paths on a sphere, ie missile paths) are straight lines. It’s called the gnomonic projection, and it could have been used to illustrate the Russian-overflight issue more clearly.

Although it’s limited to only showing half of a sphere at a time, so it doesn’t solve the problem of illustrating a southern around-the-world route. An azimuthal equidistant projection centered at the launch site or target would work for that.

What did they mess up? I have one and all I noticed is that the iPhone app got an update that imparts a cleaner UI design, reminiscent of Nokia's golden age (i.e. Marko-Ahtisaari-esque).

Can you help me understand the graph that article references to claim that more storms are happening?[1] It looks like some classes of disaster have tripled since the '80s, and in general that disasters have basically doubled. Those both seem way beyond what I would imagine being caused by the the global temperature rise of about 1 degree Fahrenheit during the same period. (If temperate increases continue at the same rate, would we see another doubling of all weather-related disasters in ~30 years?).

Anyways, that makes me wonder whether the graph captures something like reported disasters or if disaster trends happen on multi-decade scales and that 35-year span is dominated by "short-term" variation. I can't find the original context, but there looks to be an updated version of the graph in this report from the same source [2] and the commentary is "In terms of the number of events, the trend towards greater and more detailed reporting continued, with the total number further increasing to 1,060 events."

1. https://i.guim.co.uk/img/static/sys-images/Guardian/Pix/pict... 2. Comment page 54, graph page 56 https://www.munichre.com/site/mram-mobile/get/documents_E-11...

If membership in a discrimination-protected category is not completely binary, equal-opportunity policies incentivize people who could identify with multiple categories to choose the one with the lowest discrimination -adjusted threshold.

Think about it as getting a time series of previous measurements to aid in the detection of anomilies. If you just give me the metrics of a production system at an instant in time, it's hard to say whether anything's wrong. But when I know the response time has been in the same range for the past year, and then increases to 2x and stays that way for a week, I can be pretty confident that something broke.

Whether we're anywhere near feasibly getting that resolution of data is a different question.