Might be a problem of the number of pass repetitions, where O2 does not rerun the vectorisation after whatever manages to unroll everything but O3 does.
This is interesting, what tools are available to measure one's blood sugar and chart it throughout the day? I find it's pretty inconvenient to measure and report it accurately enough to get these trend lines with my regular meter.
The Freestyle Libre is good for 14 days at a time, and as far as I know costs $110-120 for a 2-pack. No it's not cheap, but it's not as expensive as the Dexcom. My son wears a Dexcom (type 1 diabetic) and my dad wears a Libre (type 2 diabetic.) The Dexcom is far more expensive, but it's the only one that will integrate with my son's insulin pump.
And about 450€ per transmitter that lasts for three months. Using open source tools you can extend the sensor lifetime to 2-3 weeks and transmitter to 6-9 months and I advice to read on that and try tools like xDrip.
Of course, but you can't just mix and match these medications. Some have serious side effects and can't be used repeatedly, and some have interactions with other meds.
You should just ask your vet. Vets will take into account the insects in your area, as well as your dog's coat and lifestyle.
It'd be a really bad idea to just load your dogs up on meds. The risk of these parasites varies greatly by geographical region. For example, in the pacific northwest, there's no need to protect against heartworms.
I Agree. All this things are changing. New vectors and new emergent diseases are not uncommon. An example is the new feline morbilivirus, very dangerous for cats and discovered in 2012. A local and experienced vet is in the best position to have trusty local info about diseases and parasites. Webs like this can not have this info, at least in its current state. Not a bad start, but can be improved a lot.
Is the med X legal in your country?, dunno, but you can order here your dog drugs. Can I mix X and Y?, dunno, order both and read the contraindications later. Are this meds dangerous for my other pets like my "always-chewing-dog-ears" cat, or my ferret? this web don't give you any clue. I know cases of kitten killed by the wrong treatment; Can you calculate the right doses for your big but starved and weak new rescued pet?... etc, etc...
Of course the owner can and should take some time to educate itself about recognising diseases (and much specially poisonings) of his pet, but good and comprehensive manuals are available in your book store, and of course to identify what kind of roundworm could or not have your dog is not trivial at all for a normal owner.
The guy that that puts all in his tank to cure "don't know what's this thing growing in my fishes" is sadly very common in aquariums. He/she kills currently much more aquarium fishes than the real diseases do.
Are you sure about this? My wife and I fostered a dog last year (here in Southern Oregon) that had heartworms. The treatment was nasty and dangerous to the dog, but the dog did recover.
Dogs won't contract heartworms naturally here but dogs brought in from other areas are definitely at risk of already having heartworms and possibly sharing those via feces. Basically an invasive species.
>>Is there an algorithm that would find the minimum subset of these to cover every parasite/bug?
This is the same problem we have in embedded systems diagnostics. We used to make a list of failure modes, and then a list of diagnostic tests. A given test may detect multiple different failures and I've made grids exactly like this. I always advocate for finding the minimum set of tests to detect all failures (to minimize false positives and simplify software). I was going to make the same point in this case, but parent already did.
To be clear, sometimes it's sufficient to detect failure without knowing exactly what the problem was. For specific diagnostics you may want POST to handle that, but at runtime you may only need to detect that something has failed.
One of the things I noticed from the Eye Tracking was that this is very similar to how we were trained to work through programming problems in high school level computer science competitions. Some competition problems involve tracing through code and determining output (of usually recursive functions) but the 'proper' method we were taught is almost exactly how he describes his thought process.
If you're just getting started, I highly recommend Andrew Ng's online ML class. I had started reading up before this was available, but it really tied a lot of basics together that I was confused about.
From there, read papers. For me, my primary interest is in neural networks. Geoffrey Hinton and Yoshua Bengio have two very good groups that both have contributed a great deal to research in this area, and their websites provide lots of good stuff.
After spending a bit of time on a survey of the field, try to come up with a practical goal as quickly as you can: I want to use ML to do X. Then, try to do that. When you get stuck, get back to reading until you find the answer. Rinse and repeat. The math naturally falls into this--you'll get stuck on things that you can't fix without a decent understanding of the math. So figure out how to formulate the question you're really asking, hit google, and read. Then try again. Rinse and repeat.
If you're interested in neural networks, I can also recommend the deep learning tutorials associated with Theano, a library for compiling python code down to CUDA code to get speed increases on certain operations that will let you train your models about 10-40x faster on GPU than if you tried it on CPU.
For me, putting things into practice has helped me make the biggest leaps in understanding, but of course I wouldn't have been able to do that at all without getting a basic grasp of the mechanisms involved. So it's a bit of push and pull between practice and learning, like anything worth doing.
Im not sure if you can find many places where they have both in great detal as most machine learning material assume some knowledge in the specific math but you could always write down the terms that you dont understand from any ML material and look it up on khan academy. For all the material you need for Andrew Ng's classes (on coursera) for example you can pretty much find all the required terms (matricies, probability etc) on khan academy
