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Supercomputer analysis of Covid-19 leads to new theory

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Re: Supercomputer analysis of Covid-19 leads to new theory

#121

Post by throwaway_pdp09 »

pmiller2 wrote: post #85
kovek wrote: post #37

Earlier quoted context omitted.

That air is a natural disinfectant is super interesting. I read that vitamin D and observed benefits for those who have vitamin D is a correlation. Meaning that taking vitamin D supplements might not be as helpful as getting sunlight (a natural way to get vitamin D)

I would guess "air as disinfectant" is primarily because of its oxygen content. O_2 is actually a pretty nasty molecule like that. Oxidation is typically a fairly tough reaction to reverse or prevent.

Ozone is 03 (https://en.wikipedia.org/wiki/Ozone). 02 is the normal oxygen as we think of it.

Re: Supercomputer analysis of Covid-19 leads to new theory

#122

Post by augusto-moura »

navd wrote: post #93

Does this support nicotine as a therapeutic for covid? It supposedly acts on the RAS and down regulates ace2

Maybe, I found out a study[1] that suggest that nicotine helps in the vascular metabolism of bradykinin. I'm no researcher neither understand a lot o biology, but it could be a hint

[1]: https://journals.physiology.org/doi/full/10.1152/ajpregu.000...

Re: Supercomputer analysis of Covid-19 leads to new theory

#123

Post by s1artibartfast »

SideburnsOfDoom wrote: post #118
s1artibartfast wrote: post #73

Earlier quoted context omitted.

I think it is a question of semantics regarding the words generate and theory. Computers cant produce theories because they generate and analyze data, but cant process ideas. Unless the computer is conscious, it can not generate the theory.

> they generate and analyze data, but cant process ideas But what if the data represents ideas? https://en.wikipedia.org/wiki/Automated_theorem_proving > Unless the computer is conscious, it can not generate the theory. Why would you say that consciousness is necessary for theory generation? It isn't for arithmetic, equation solving, natural language processing or image identification, etc.

>> they generate and analyze data, but cant process ideas

>But what if the data represents ideas?

Then the computer would still be generating and analyzing data, not processing ideas.

>> Unless the computer is conscious, it can not generate the theory. >Why would you say that consciousness is necessary for theory generation? It isn't for arithmetic, equation solving, natural language processing or image identification, etc.

I think that the conscious analyst/observer is an intrinsic part of theory discovery, in the same way that a computer can not understand Chinese[1].

If the conscious observer is not necessary for a theory to exist, why is the computer necessary either? Certainly the phenomenon and data exist without it?

[1] https://en.wikipedia.org/wiki/Chinese_room

Re: Supercomputer analysis of Covid-19 leads to new theory

#125

Post by r00fus »

woeirua wrote: post #62
Enginerrrd wrote: post #44

Earlier quoted context omitted.

I had this same question early on and I recall reading somewhere that treated hypertension reduced risk. Ostensibly, even if that was from a credible source, it may not mean much though.

The problem is that the relationship between hypertension, antihypertensives, and Covid is going to be very nuanced and difficult to ascertain without large patient populations to study. One of the very unique aspects of the Covid pandemic is that the NPIs seem to be very effective at damping the spread, so much so that the pool of patients to study keeps moving from region to region every 60 days or so.

> so much so that the pool of patients to study keeps moving from region to region every 60 days or so.

How does NPI/mask effectiveness impact the study moving regions?

Re: Supercomputer analysis of Covid-19 leads to new theory

#126

Post by zuminator »

andrewflnr wrote: post #109
TheSpiceIsLife wrote: post #19

Earlier quoted context omitted.

Probably just you ;) Lay people use the two interchangeably. In at least two of the thesaurus I have at hand hypothesis is synonymous is theory .

It seems to me like even scientists use the terms not quite interchangeably, but on a spectrum. String theory is still "theoretical physics", not "hypothetical physics", even though it will likely never be tested in our lifetime.

That's because the whole internet idea of "a theory is a well-tested hypothesis" is silly and wrong. A hypothesis is a specific supposition or question about the way things work which if true has some level of explanatory power in a field of study. It can be confirmed or unconfirmed. It's still a hypothesis. An answered question is still a question.

A theory is a explanatory framework for a body of knowledge. Unlike a hypothesis, it's not inherently a question or a guess. That doesn't mean it's "true." It also can be unconfirmed (as you say, string theory) or even demonstrably false (phlogiston theory, Ptolemaic theory) and still be a theory.

Obviously there's considerable overlap between the two concepts and as you say they are sometimes used almost interchangeably. Colloquially, "I'm testing my hypothesis that orally ingesting booze provides protection against infection, which if confirmed will be a key part of a theory of booze immunology" gets collapsed into "I'm testing my theory of booze immunology." Big deal. It really only matters because people let themselves get bent out of shape about the whole "evolution is just a theory" thing.

And since I'm ranting already, evolution isn't "just a theory" because evolution itself isn't a "theory," evolution is the natural phenomenon that is being theorized about.

Re: Supercomputer analysis of Covid-19 leads to new theory

#127

Post by secabeen »

dekhn wrote: post #114
secabeen wrote: post #112

Earlier quoted context omitted.

In my experience with research computing, if you are able to keep a computer doing active work more than 60% of the time, it will be cheaper to purchase and run that computer yourself than renting it from AWS. That's the case even with commodity machines with only 10G Ethernet interconnect. $15k for a machine is only $0.34/hour over 5 years. That doesn't buy much of an AWS machine. (Yes, cooling, real estate and powe…

You're completely ignoring the other valuable aspects of being in a cloud: you're close to huge amounts of high throughput storage (blob and DB), and can increase/decrease the size of your fleet trivially. These are critical to nearly all modern scientific workflows (moreso than the raw compute, IMHO). As for the cost structure for research computing, the argument that the costs are externalized isn't a good one- tha…

> You're completely ignoring the other valuable aspects of being in a cloud: you're close to huge amounts of high throughput storage (blob and DB), and can increase/decrease the size of your fleet trivially. These are critical to nearly all modern scientific workflows (moreso than the raw compute, IMHO).

That has not been my experience. There are lots of scientific workflows that only need 10s of TB at most, yet can still consume lots of cycles.

> As for the cost structure for research computing, the argument that the costs are externalized isn't a good one- that overhead that pays for the facility, and the networking, comes out of your grant money, and using grad student time to admin your cluster often just causes your grad students to leave for FAAMG.

At the universities I've worked at, equipment (large purchases) is except from overhead, or results in a lower overhead charge. (Researchers balk at paying a ~50% overhead rate on a $1million instrument). Using grad student time to admin your cluster is dumb, but I'm more talking about users who need single-digit numbers of computers. If you need real HPC, you're in the world of queues, national and regional supercomputers, etc. etc.

Re: Supercomputer analysis of Covid-19 leads to new theory

#130

Post by pas »

r00fus wrote: post #125
woeirua wrote: post #62

Earlier quoted context omitted.

The problem is that the relationship between hypertension, antihypertensives, and Covid is going to be very nuanced and difficult to ascertain without large patient populations to study. One of the very unique aspects of the Covid pandemic is that the NPIs seem to be very effective at damping the spread, so much so that the pool of patients to study keeps moving from region to region every 60 days or so.

> so much so that the pool of patients to study keeps moving from region to region every 60 days or so. How does NPI/mask effectiveness impact the study moving regions?

(Not OP, not an expert either.)

By the time you design a study, recruit a pool and wait for some of them to get covid, not enough get it for the study to have enough statistical power.

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