Tootfinder

🇺🇦 #NowPlaying on KEXP's #Early
tUnE-yArDs:
🎵 Perpetual Motion
#tUnEyArDs
https://tune-yards.bandcamp.com/track/perpetual-motion
https://open.spotify.com/track/4nMeckVg01xa41I4I2OI8j

#Ambisonics algorithm: Can it beat human hearing? https://www.theneurotimes.com/ambisonics-algorithm-human-hearing/ "Can the ambisonics algorithm in AudioDome re…

Ambisonics Algorithm: Can It Beat Human Hearing? - The Neuro Times
Can the ambisonics algorithm in AudioDome recreate 3D sound more precisely than human perception? Explore the science behind this immersive tech.

3 #PositiveDinge gestern
- abends konzentriert die Chorstücke für Sonntag geübt und 2 Stunden Ruhe in meinem Musikkämmerlein gehabt
- Mitte der Woche schon erreicht
- Come Again, Sweet Love Doth Now Invite von John Dowland weiter geübt, jetzt mit Kapodaster im dritten Bund, dann sollte es in der richtigen Tonart erklingen. In der Ausgabe wurde das Stück eine Terz tiefer notier…

Hoarding syndrome is considered a psychiatric condition, not a crisis for democracy itself
-- with one giant exception:
When people with hoarding syndrome are born with or come into massive wealth
-- suddenly what was once a personal, psychiatric issue can become a crisis for all of society.
It happens every few generations.
It’s what drove the fascist oligarchs of the Confederacy to reach out and try to conquer the entire United States in the 1860s.
It …

The Billionaire Hoarders: How the Wealthy Became Our Biggest Threat
How a sick obsession is killing workers, democracy, and our planet.

Machine Learning-Guided Discovery of Temperature-Induced Solid-Solid Phase Transitions in Inorganic Materials
Cibr\'an L\'opez, Joshua Ojih, Ming Hu, Josep Lluis Tamarit, Edgardo Saucedo, Claudio Cazorla
https://arxiv.org/abs/2506.01449

Machine Learning-Guided Discovery of Temperature-Induced Solid-Solid Phase Transitions in Inorganic Materials
Predicting solid-solid phase transitions remains a long-standing challenge in materials science. Solid-solid transformations underpin a wide range of functional properties critical to energy conversion, information storage, and thermal management technologies. However, their prediction is computationally intensive due to the need to account for finite-temperature effects. Here, we present an uncertainty-aware machine-learning-guided framework for high-throughput prediction of temperature-induce…