I get this comment a lot:

Hello Web Admin, I noticed that your On-Page SEO is is missing a few factors, for one you do not use all three H tags in your post, also I notice that you are not using bold or italics properly in your SEO optimization. . . .

I probably also don’t sprinkle enough chicken’s blood.

On a private mailing list, a novelist asks for suggestions: what technological hobbies might a bright teenager have, in Oakland circa 1975? Chemistry sets were mentioned, among other things.

I may have had a chemistry set at age 8 or so; memory is spotty. A few years later we got an electronics kit, consisting of a collection of elements in Lego-like blocks. There was a booklet, starting with easy things like a light switch and an electromagnetic telegraph relay. (Maybe I thought the latter was easy because Dad and I had made one, about the same time as the possible chem kit).

Then on the next page was an oscillator or something. No explanation of why it was an oscillator. I thought, well, if I can’t see for myself why it’s an oscillator, evidently I’m not cut out for this stuff; so I quietly abandoned it.

My adolescence in a nutshell.

Of course it never occurred to me that perhaps there was no explanation because I was not expected to understand an explanation; I was expected to treat the oscillator as a black box. (Not that I had the concept of “black box”, either!)

Oh well.

I got an interesting idea today.

As you may already know, I’ve been making models of Klein bottles an’ stuff; heretofore they’ve all been in the form of bent rods, but where possible I’d prefer a continuous surface. (A hollow body must have holes so that unused powder can be shaken out; but not all of my designs have enclosed spaces.) How to place a minimum number of vertices so that deviations from the abstract shape are within the resolution of the process? That’s less obvious with more degrees of freedom.

So, today’s idea. Start with an arbitrary set of sample nodes (in the abstract space of the parametric variables, rather than on the target surface itself), and their Delaunay triangulation. Along each edge of the triangulation, measure the deviation of the surface from a straight line; this gives the edge a weight. Move each node to the weighted average of its neighbors (with a bit of noise); thus, an edge whose image is strongly curved gets shorter.

After the movement phase, each edge ought to be checked, whether it’s still a Delaunay edge or needs to be replaced by the other diagonal of the quadrilateral formed by its two triangles. I don’t yet have criteria for adding nodes where existing nodes are too far apart, or merging them if they become redundant.