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>Sometimes our bodies evolve weird quirks, and there's no actual benefit, but also no cost to our actual fitness. E.g hair graying in our elder years.)

This cannot be restated frequently enough here.

As long as a trait doesn't negatively impact an organism's reproductive fitness, it might just be carried around for no good reason whatsoever. That's how evolution works - some changes are good, some are bad, and (probably) the vast majority are neither, requiring no further explanation other than mutations cause fun things to happen.

Proteins are the functional molecules of the body, but I would not conflate the term amino acid with the generic idea of an acid. An amino acid has three groups: a basic amine group, an acidic carboxylic acid group, and then a functional ‘R’ group that has variable acidity. The concept of pKa is important here; the ionizable (or ability to lose/gain a proton) groups of proteins are based on pH, and this in turn confers a proteins function and interaction with other molecules.

We run slightly alkaline because gas exchange (O2 to CO2) is a tightly regulated process to ensure proper cellular function. Dissolved CO2 is acidic, and our blood (and the organs bathed in blood) needs to stay slightly basic to avoid CO2 build up.

It’s also important to note there are proton gradients in our cells, and these proton gradients drive functions like chemiosmosis (a crucial step in cellular respiration). Organelles like lysosomes are also highly acidic to facilitate breakdown of molecules.

Tldr: amino acids are not acidic just because they have acid in the name, slightly basic blood helps with gas exchange, and you can find membrane-bound structures that are highly acidic within cells.

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One possibility is that bipedalism evolved because it allowed us to free up our hands, allowing us to carry resources. Another is the endurance running hypothesis: that we evolved to become good long distance runners, and this shaped our legs.

I wouldn't assume that just because a trait evolved, like our hands wrinkling in the water, that it must have been evolutionarily adaptive. Sometimes our bodies evolve weird quirks, and there's no actual benefit, but also no cost to our actual fitness. E.g hair graying in our elder years.

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Yes. Cells may become multinucleated cells if something goes wrong during the cell division/fusion which is possible when cancerous cells divide way too often unregulatedly.

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No superglue?

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Bluring is not a bijective function. Meaning two different images could give the same blurred one. Some information is lost.

This said, some IA models are specifically trained to unblur images : they don't get back the lost information but only make up a possible sharp images that could have resulted to the blurred one, based on what it saw before.

The results are quite impressive.

https://ai.smartmine.net/service/computer-vision/image-deblurring

What the others have said is the correct answer to your question in the text.

However I'd just like to add that in the case of an allogeneic hematopoietic stem cell transplant (with a donor) you actually do "inherit the immune system of the donor" - sorta...

When you receive stem cells, those stem cells originate from another body, which the cells are completely compatible with. Should you later down the road need a new kidney for example, the original donor can donate their kidney without the need of immunosuppresants. Normally you'd need immunosuppresants for as long as the kidney was in your body in order to avoid rejection. However since the immune systems cells and the kidney are compatible - you don't.

I suppose it's exceedingly rare though. Just something I remember from immunology classes that I found extremely interesting.

Well what you described isn't really a blur function (it'd be a brightness shift). But if we want to call it that then yes it is reversible there.

There are several other mathematical operations you can do that are just reversible like that. However none of them are anywhere close to actual blur functions.

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There’s a whole bunch of special cases but I tried to target the case where you know exactly how it is blurred but the blurred version you have has additional noise. It is this additional noise that does you in. My example also could if explicitly brought in the blurring into the equation example and brought in the convolution nature:

Let’s think about a one dimensional deblurring problem where we measure just two blurred pixels. The left one is 34 and the right one is 27. Suppose we exactly know the blur (in kernel form) is three pixels wide and the blur has values A, B, C. If w,x,y,z is the unblurred image then

Aw + Bx + C*y + N= 34 and

Ax + By + C*z + M = 27

where N and M are small random numbers (noise in the pixel measurement).

To estimate the middle two pixels of the unblurred image, you have to solve the above equations for x and y. You only know A B and C but you (often) can assume that w, x,y,z are zero or positive and that N and M are fairly small. Even if you are really good at linear algebra, solving the above two equations for the two to six unknowns is il-posed.

If you get enough pixels (say more than the width of the blur), you can get away from having to solve for edge pixels like w and z and you can get approximate solutions like using the Wiener filter.

I have been assuming you know the blur and that the blur is the same everywhere in the image. If the blur is not the same over the image, the linear algebra tricks that make the Wiener filter don’t work and you have to selectively apply them over small enough patches that they still sort of work.

If you do not know the blur, it’s strong assumption time (also called “blind deconvolution”) and you need to consult a professional with details about your inverse problem to see how well it can be solved.