Tootfinder

Rural Fishermen Entrusted to Manage Pristine Caribbean Shoreline to Safeguard Their Fish and Future https://www.goodnewsnetwork.org/rural-fishermen-entrusted-to-manage-pristine-caribbean-shoreline-to-sa…

Rural Fishermen Entrusted to Manage Pristine Caribbean Shoreline to Safeguard Their Fish and Future
Artisanal fishing communities are celebrating the creation of a marine protected area to be co-managed with those communities.

#Steady-CommunityContent
Mit einem einfachen #Python-Skript auf dem #RaspberryPi sollten die Leistungsdaten des EZ1-SPE

EZ1-SPE Daten lokal speichern: Python-Skript auf Raspberry Pi (7/10)
Du willst Deine Wechselrichter-Daten lokal speichern und auswerten? So geht’s mit Raspberry Pi, Python und der EZ1-API!

🇺🇦 Auf radioeins läuft...
Sofia Kourtesis:
🎵 Corazón
#NowPlaying #SofiaKourtesis
https://sofiakourtesis.bandcamp.com/track/coraz-n
https://open.spotify.com/track/5A6SU4vLMAJZbkTy7C7xXJ

Sufficient minimum degree conditions for the existence of highly connected or edge-connected subgraphs
Maximilian Krone
https://arxiv.org/abs/2508.07997 https://

Sufficient minimum degree conditions for the existence of highly connected or edge-connected subgraphs
Mader conjectured that an average degree of at least $3k-1$ is sufficient for the existence of a $(k+1)$-connected subgraph. The following minimum degree version holds: Every graph with minimum degree at least $3k-1$ has a $(k+1)$-connected subgraph on more than $2k$ vertices. Moreover, for triangle-free graphs, already an average degree of at least $2k$ is sufficient for a $(k+1)$-connected subgraph (which has at least $2(k+1)$ vertices). For edge-connectedness (in simple graphs), we prove t…

Why might a digital piano sound good on (professional) headphones but bad with its own speakers? The reason is probably "because they speakers are bad", right?
The piano I'm talking about is a Donner DDP-80, in case you're curious.

SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization
Beilong Tang, Xiaoxiao Miao, Xin Wang, Ming Li
https://arxiv.org/abs/2508.07086 https://

SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization
Voice anonymization protects speaker privacy by concealing identity while preserving linguistic and paralinguistic content. Self-supervised learning (SSL) representations encode linguistic features but preserve speaker traits. We propose a novel speaker-embedding-free framework called SEF-MK. Instead of using a single k-means model trained on the entire dataset, SEF-MK anonymizes SSL representations for each utterance by randomly selecting one of multiple k-means models, each trained on a diffe…

the sidewalk is not "your driveway," SF motorists. enough with the entitled grabbing of public space
https://www.sfchronicle.com/sf/article/car-driveway-san-francisco-20763724.php

MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts
Junda Ye, Zhongbao Zhang, Li Sun, Siqiang Luo
https://arxiv.org/abs/2509.09337 https://

MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts
While graph neural networks (GNNs) have achieved great success in learning from graph-structured data, their reliance on local, pairwise message passing restricts their ability to capture complex, high-order subgraph patterns. leading to insufficient structural expressiveness. Recent efforts have attempted to enhance structural expressiveness by integrating random walk kernels into GNNs. However, these methods are inherently designed for graph-level tasks, which limits their applicability to ot…

Hub survey: 42% of Americans say they were more likely to keep subscribing to a streaming bundle over an individual app; only 14% say they were less likely (Matthew Keys/TheDesk.net)
https://thedesk.net/2025/08/hub-streaming-bundles-june-2025-survey/

Hub: Streaming bundles make consumers stick around
Consumers are more likely to keep a streaming subscription when they are able to pair it with other services through a bundle.

Multi-Target Backdoor Attacks Against Speaker Recognition
Alexandrine Fortier, Sonal Joshi, Thomas Thebaud, Jesus Villalba Lopez, Najim Dehak, Patrick Cardinal
https://arxiv.org/abs/2508.08559

Multi-Target Backdoor Attacks Against Speaker Recognition
In this work, we propose a multi-target backdoor attack against speaker identification using position-independent clicking sounds as triggers. Unlike previous single-target approaches, our method targets up to 50 speakers simultaneously, achieving success rates of up to 95.04%. To simulate more realistic attack conditions, we vary the signal-to-noise ratio between speech and trigger, demonstrating a trade-off between stealth and effectiveness. We further extend the attack to the speaker verific…