sixfold

joined 1 year ago
 

cross-posted from: https://lemmy.sdf.org/post/3795687

"Many of these terms were in common use into the 20th century."

I hear many of these terms in common usage today, like potash, tartar, spirits, soda/soda ash, lime, soda lime, slacked lime, quicklime, lye, alkali, caustic soda, caustic potash, caustic alkali, quicksilver, chalk, cinnabar, fools gold, fulminating silver, fulminating gold, gypsum, vitriol has taken on a less specific meaning, aqua regia, turpentines, lead sugar, sulfur.

I think the reason that so many of these terms are retained is that the substances they refer to have been known for thousands of years in some cases.

brimstone is a much cooler name for sulfur that should be brought back. aqua vitae is a nice name for ethanol. the names of metals haven't changed.

 

cross-posted from: https://lemmy.sdf.org/post/3732588

A nice trip up and down the scale of things. I especially like the ones from 10^1 to 10^14, inhumane numbers attempting to be brought to a human scale.

Source: CRC Standard Mathematical Tables and Formulas (Zwillinger, Daniel) (Z-Library)

 

cross-posted from: https://lemmy.sdf.org/post/3732588

A nice trip up and down the scale of things. I especially like the ones from 10^1 to 10^14, inhumane numbers attempting to be brought to a human scale.

Source: CRC Standard Mathematical Tables and Formulas (Zwillinger, Daniel) (Z-Library)

[–] [email protected] 0 points 10 months ago (1 children)

That's a super interesting project. For anyone else, the project overview has some great system level diagrams:

https://github.com/opentraffic/otv2-platform

[–] [email protected] 0 points 10 months ago (3 children)

time for some kind of anonymizing location data sharing service, peer to peer or federated protocol? that might be interesting, or sketchy, not sure which.

[–] [email protected] 1 points 10 months ago

Pretty sure you can download the maps ahead of time, GPS doesn't require data, then upload the fixes when you get home.

 

I put water in a jar and sealed it while it was boiling, and now it boils at any temperature. Super fun demo to try.

 

Now a set of useful mutations are implemented, and balanced so that the number of nodes or edges doesn't explode.

The mutations I've implemented (node are genes are nodes):

add random gene
delete node
delete group of nodes (range of indexes)
split edge    create new node in place of an edge (insertNode)
flip edge
duplicate node
duplicated group of nodes (range of indexes)
change node index (regrouping/separating functional groups)
change group of nodes index (transposable elements)
create random edge
delete random existing edge
scale existing edge weight
negate weight
redirect existing edge to random node
scale parameter (k1, b, k2)
negate bias

This is the next installment from the Gene Regulatory Network saga.

previously: https://lemmy.sdf.org/post/1967056######

[–] [email protected] 1 points 11 months ago* (last edited 11 months ago)

Well, it is technically differential equations, but with weighted inputs like a NN. Here's the equations

for each node (gene/morphogen) i. zi is the concentration of morphogen i, zj is that of j. f(x) is the sigmoid function, k1 is the maximum rate of expression, k2 is the degradation rate, b is the bias. wij is the weight for an edge from j to i.

This is just written in python, so the network is defined by a matrix with each number representing the weight between two of the edges. I ignore the edge if it's weight is zero.

What are the standard symbols for genetic circuits?

edit: sorry it's impossible to see the equations if you have a black background.

[–] [email protected] 2 points 11 months ago

Damn, that's cool.

 

I'm working on a program to edit and simulate gene regulatory networks using recurrent neural networks as a model. Here's a demo.

 

cross-posted from: https://lemmy.sdf.org/post/1775532

A model of gene regulatory networks using the mathematical model for recurrent neural nets from computer science. It's such a great way to describe how a cell 'knows' things. every single celled organism or cell in a body contains within a complex information processing chemical network of gene-regulating proteins. One way to think of it is that every individual cell integrates information like a neural network. Good read, there are newer papers on this subject, but I'm not sure if there are better ones.

[–] [email protected] 1 points 11 months ago

Here's the same 3 morphogen periodic clock network implemented in python https://diode.zone/w/9ApBpVcU5CnCbbTu3Lcegw

 

Based on Neural Model of the Genetic Network Vohradsky 2001 I'm working on a project to make reaction diffusion and evolutionary algorithms more interesting. I want to simulate development of artificial multicellular organisms.

 

Just comedy.