Tootfinder

Les recomiendo la lectura de esta nota en la RollingStone en español sobre el clima de violencia actual. Se refiere particularmente a Argentina, pero es extrapolable a lo que ocurre en Chile y en muchas otras partes del mundo.
#Argentina #Violencia

🇺🇦 #NowPlaying on KEXP's #StreetSounds
JURIN ASAYA:
🎵 PS 118
#JURINASAYA
https://jayfromjerz.bandcamp.com/track/a15-ps118-jurin-asaya-feat-rapsody
https://open.spotify.com/track/1X5BMHJoKkVlf9Vo2YYsJz

"The student’s education then becomes not a victory for their own self-improvement or -enrichment, but rather that the teacher conquered the student’s presumed inherent laziness, shiftiness, etc. to instill some kernel of a lesson."
#FediLZ
@…

Liegt der Höhepunkt der sozialen Medien hinter uns? Das fragt @jburnmurdoch in der Financial Times. AI-generierte Videos fluten die Plattformen, viele sind nicht mehr selbst aktiv und vernetzen sich dort nicht mehr mit Freunden. Laut Umfrage verbringen gerade junge Leute unterdessen weniger Zeit auf #SocialMedia.
Have we passed peak social media?

🇺🇦 #NowPlaying on BBCRadio3's #RoundMidnight
Poppy Daniels:
🎵 Boundaries
#PoppyDaniels
https://open.spotify.com/track/4iDRc7gJ4Uvhrn5r0sMHKy

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Khruangbin:
🎵 Two Fish and an Elephant ii
#Khruangbin
https://open.spotify.com/track/48JBR081mjo6dD66VNjYzh

Digital Innovation in Microenterprises: Current Trends and New Research Avenues
Juan E. G\'omez-Morantes (Pontificia Universidad Javeriana), Andrea Herrera (Universidad de los Andes), Sonia Camacho (Universidad de los Andes)
https://arxiv.org/abs/2510.07519

Digital Innovation in Microenterprises: Current Trends and New Research Avenues
The relationship between microenterprises and information and communication technologies (ICTs) has always been troublesome. Because of the rapid pace of modern digital technologies, digital innovation processes are permeating the industries, markets, and social contexts in which microenterprises exist today. However, microenterprises have severe difficulties engaging or performing in these digital contexts and are at risk of being left behind. This paper reviews the literature on ICTs and micr…

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Litu Rout, Andreas Lugmayr, Yasamin Jafarian, Srivatsan Varadharajan, Constantine Caramanis, Sanjay Shakkottai, Ira Kemelmacher-Shlizerman
https://arxiv.org/abs/2510.02291

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
We study the problem of posterior sampling using pretrained discrete diffusion foundation models, aiming to recover images from noisy measurements without retraining task-specific models. While diffusion models have achieved remarkable success in generative modeling, most advances rely on continuous Gaussian diffusion. In contrast, discrete diffusion offers a unified framework for jointly modeling categorical data such as text and images. Beyond unification, discrete diffusion provides faster i…

YawSitter: Modeling and Controlling a Tail-Sitter UAV with Enhanced Yaw Control
Amir Habel, Fawad Mehboob, Jeffrin Sam, Clement Fortin, Dzmitry Tsetserukou
https://arxiv.org/abs/2510.02968

YawSitter: Modeling and Controlling a Tail-Sitter UAV with Enhanced Yaw Control
Achieving precise lateral motion modeling and decoupled control in hover remains a significant challenge for tail-sitter Unmanned Aerial Vehicles (UAVs), primarily due to complex aerodynamic couplings and the absence of welldefined lateral dynamics. This paper presents a novel modeling and control strategy that enhances yaw authority and lateral motion by introducing a sideslip force model derived from differential propeller slipstream effects acting on the fuselage under differential thrust. T…

Accurate linear modeling of EEG-based cortical activity during a passive motor task with input: a sub-space identification approach
Sanna Bakels, Mark van de Ruit, Matin Jafarian
https://arxiv.org/abs/2510.02596

Accurate linear modeling of EEG-based cortical activity during a passive motor task with input: a sub-space identification approach
This paper studies linear mathematical modeling of brain's cortical dynamics using electroencephalography (EEG) data in an experiment with continuous exogenous input. The EEG data were recorded while participants were seated with their wrist strapped to a haptic manipulator. The manipulator imposed a continuous multisine angular perturbation to the wrist as the exogenous input to the brain. We show that subspace identification, in particular the PO-MOESP algorithm, leads to a linear time-invari…