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lunedì 19 agosto 2024
# gst: apropos of 'normal' (jazzy?) codes, bacteria encode hidden, free-floating genes outside their genome.
venerdì 11 ottobre 2024
# evol: flip of the script when an entity invert code sequences
lunedì 18 settembre 2017
# soc: pulsatile self-destructive choices, by Oliver and Julia
<< Let’s all be thankful that FiveThirtyEight readers don’t control America’s nuclear arsenal >>
Last week AA << published an article on the game theory of nuclear standoffs. That article included an interactive game ... >>
Oliver Roeder, Julia Wolfe. Thank God You People Don’t Have The Nuclear Codes. Sep. 14, 2017.
https://fivethirtyeight.com/features/thank-god-you-people-dont-have-the-nuclear-codes/
<< Shall we play a game? >>
Oliver Roeder. How To Win A Nuclear Standoff. President Trump and Kim Jong Un’s saber-rattling is dangerous, but not irrational. Sep. 6, 2017
https://fivethirtyeight.com/features/how-to-win-a-nuclear-standoff/
lunedì 25 gennaio 2021
# gst: apropos of the structure of natural codes, a RNA folding knot (origami-style) dance
domenica 6 dicembre 2015
# s-phys-tech-bot: crackin' as a snap
<< If quantum computers existed, they would revolutionize computing as we know it. Based on fundamental properties of matter, the potential power of these theoretical workhorses would solve problems in a new way, cracking extremely complex spy codes and precisely modeling chemical systems in a snap. >>
http://www.eurekalert.org/pub_releases/2015-12/acs-aqs112415.php
Joseph M. Zadrozny, Jens Niklas, et al Millisecond Coherence Time in a Tunable Molecular Electronic Spin Qubit. ACS Central Science, 2015; DOI: 10.1021/acscentsci.5b00338
giovedì 6 luglio 2017
# s-brain: to distinguish between reality and imagination
<< neurons in the part of the brain found to be abnormal in psychosis are also important in helping people distinguish between reality and imagination >>
AA << investigated how the brain codes visual information in reality versus abstract information in our working memory and how those differences are distributed across neurons in the lateral prefrontal cortex region of the brain >>
Crystal Mackay. Researchers identify specific neurons that distinguish between reality and imagination. June 1, 2017
AA << results indicate that a functionally diverse population of LPFC (lateral prefrontal cortex) neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features >>
Diego Mendoza-Halliday & Julio C. Martinez-Trujillo. Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex. Nature Comm. 8, Article no: 15471 (2017) doi: 10.1038/ncomms15471 Publ. Jun 01, 2017
mercoledì 15 luglio 2020
# evol: iterative hacking mechanics; a large group of viruses can assemble human-virus codes to produce novel chimeric (UFO) proteins
martedì 14 aprile 2020
# gene: stuttering, syncopated (but not junk) codes
venerdì 24 febbraio 2023
# gst: apropos of transitions, erratic, bursty growth processes in cellular sprawl
lunedì 18 gennaio 2016
# s-gst: Shakespeare and Wordsworth' sound patterns of texts
<< Alexander Clark and Thao Tran evaluated sound patterns of texts, with the goal of comparing the sonnets of Shakespeare and Wordsworth. Clark and Tran used the soundex algorithm, a method of converting words into 5 digit "codes." >>
http://www.math.union.edu/~framem/AprilWorkshop/DataIFS/Texts/Clark/Clark.html
<< however close you look, the complexity stays >>
Dilip D'Souza. Fri, Jan 15 2016. 12 40 AM IST
http://www.livemint.com/Opinion/78slqi9jU44QuvhxPAsJNL/All-your-lifes-a-fractal.html
giovedì 14 aprile 2016
# s-ai: MICrONS is working in reverse
<< MICrONS (Machine Intelligence from Cortical Networks) project seeks to revolutionize machine learning by reverse engineering algorithms of the mammalian cortex. >>
<< MICrONS is fundamentally different, both technically and logistically. Rather than building a simulation of the human brain, which the HBP [Human Brain Project] set out to do, MICrONS is working in reverse. By mapping out the intricate connections that neurons form during visual learning and observing how they change with time, the project hopes to distill sensory computation into mathematical “neural codes” that can be fed into machines, giving them the power to identify, discriminate, and generalize visual stimulation. The end goal: smarter machines that can process images and video at human-level proficiency. >>
Shelly Fan. US Bets $100 Million on Machines That Think More Like Humans. Mar 13, 2016.
http://singularityhub.com/2016/03/13/us-bets-100-million-on-machines-that-think-more-like-humans/