High-altitude natives are an exceptional model for understanding the genetic and physiological bases of evolutionary adaptation. Species that are broadly distributed across altitudes can provide powerful insight into the genetic basis of high-altitude adaptation, because it is possible to examine segregating variation for phenotypes that may contribute to hypoxia tolerance. Recent research has identified many genes that appear to have experienced selection in high-altitude taxa, including genes thought to be involved in O2 transport, energy metabolism and hypoxia signalling (Simonson, 2015; Simonson et al., 2012; Storz and Cheviron, 2021). However, in most cases, the specific effects of these genetic variants on physiological function are poorly understood. … Identifying these functional effects has the potential to uncover novel and adaptive physiological mechanisms, given the growing appreciation that protein variants can have auxiliary effects that are unrelated to the ‘canonical’ function of the protein in question (Marden, 2013a).
A derivative is linearisation, and differential calculus is essentially linear algebra, ... See Freya Holmér - Why Can't You Multiply Vectors? and Freya Holmér on Continuity of Splines . See also the MIT OCW page: Matrix Calculus For Machine Learning And Beyond (Alan Edelman, Steven G. Johnson) Subscribe to The Julia Programming Language . Alan Edelman talking about expressing mathematics as computer code. The idea is that you can use computer languages to communicate mathematical ideas precisely to other people. See my comments about functional programming languages here: https://prooftoys.org/ian-grant/hm/ Subscribe to TEDx Talks .
Listening to Freya Holmér last night I started to get glimmers of an idea I had long ago about how to represent vector spaces in computational processes using this recursive abstract type : abstype 'a point = POINT of {getx : 'a vector, diff : 'a point -> 'a point, move : 'a point -> 'a point, scale : 'a -> 'a point, proj : 'a point -> 'a} with fun new i (op +) (op -) (op * ) dot = let fun self x = POINT {getx = x, move = fn (POINT pr) => (self (x + (#getx pr))), diff = fn (POINT pr) => self (x - (#getx pr)), scale = fn i => (self (x * i)), proj = fn (POINT pr) => ...
I think this is the first time they've actually publicly announced anything about this project. See these posts: Eron Woolf on Why Open Source is Failing Matt Mikhailov and Vincent McKibbon on The Problem with Open Hardware Jason Kridner talking About BeagleBoard.org and Software Development . See these places: https://danielc.dev/rk/ https://github.com/petabyt/rk https://github.com/futo-org/ret See also https://pine64.org/devices/pinebook_pro/ . Subscribe to FUTO . See https://github.com/nir9/low-level-learning-resources/tree/master/setups/debian . Subscribe to Nir Lichtman . If you're looking for a cool init process, try https://ctx.graphics/terminal/ . See Artful Bytes - When to Use a RTOS and How to Create a Successful Open Source Project .
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