Tootfinder

E-21 Level Instability Frequency Dissemination over 2067 km noisy Telecommunication Infrastructure
Fa-Xi Chen, Li-Bo Li, Jiu-Peng Chen, Kan Zhao, Jian-Yu Guan, Yang Xu, Lei Hou, Fei Zhou, Cheng-Zhi Peng, Qiang Zhang, Hai-Feng Jiang, Jian-Wei Pan
https://arxiv.org/abs/2507.14192

E-21 Level Instability Frequency Dissemination over 2067 km noisy Telecommunication Infrastructure
The realization of ultra stable optical frequency transmission through fiber networks is critical for advancing global optical frequency standards and enabling applications such as redefining the second in the International System of Units, geophysical sensing, quantum network construction, and fundamental physics experiments. However, achieving high reliability and low instability optical frequency carrier transmission links over distances exceeding thousands of kilometers remains technically …

Determination of Fragmentation Functions from Charge Asymmetries in Hadron Production
Jun Gao, ChongYang Liu, Bin Zhou
https://arxiv.org/abs/2507.14637 htt…

Determination of Fragmentation Functions from Charge Asymmetries in Hadron Production
We propose a novel method for extracting non-singlet (NS) fragmentation functions (FFs) of light charged hadrons from charge asymmetries measured in hadron fragmentation, using data from both single-inclusive electron-positron annihilation and semi-inclusive deep-inelastic scattering processes. We determine the NS FFs for pions and kaons at next-to-next-to-leading order in Quantum Chromodynamics, including a comprehensive uncertainty analysis. The extracted FFs reveal a scaling index of about 0…

Paris confirms strong interest in Ukraine arms co-production: https://benborges.xyz/2025/07/22/paris-confirms-strong-interest-in.html

ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signal
Yucong Zhang, Juan Liu, Ming Li
https://arxiv.org/abs/2508.14689 https://arxiv.org/p…

ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signal
Pre-trained foundation models have demonstrated remarkable success in vision and language, yet their potential for general machine signal modeling-covering acoustic, vibration, and other industrial sensor data-remains under-explored. Existing approach using sub-band-based encoders has achieved competitive results but are limited by fixed input lengths, and the absence of explicit frequency positional encoding. In this work, we propose a novel foundation model that integrates an advanced band-sp…

"UK ministers reopen door to drilling at two North Sea oilfields as new guidance released"
#UK #UnitedKingdom #NorthSea

Top House Democrats are calling on Brendan Carr,
chair of the Federal Communications Commission (FCC),
to resign over the indefinite suspension of Jimmy Kimmel’s late night show.
The congressional leaders accuse Carr – who runs the US’ media watchdog
– of engaging in a “corrupt abuse of power”
by “bullying ABC” and forcing the media company to “bend the knee to the Trump administration”.
Democratic leader Hakeem Jeffries, Minority whip Katherine Clark, Demo…

No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targets
Pranay Dugar, Mohitvishnu S. Gadde, Jonah Siekmann, Yesh Godse, Aayam Shrestha, Alan Fern
https://arxiv.org/abs/2508.14098

No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targets
Humanoids operating in real-world workspaces must frequently execute task-driven, short-range movements to SE(2) target poses. To be practical, these transitions must be fast, robust, and energy efficient. While learning-based locomotion has made significant progress, most existing methods optimize for velocity-tracking rather than direct pose reaching, resulting in inefficient, marching-style behavior when applied to short-range tasks. In this work, we develop a reinforcement learning approach…

Testing Autonomous Driving Systems -- What Really Matters and What Doesn't
Changwen Li, Joseph Sifakis, Rongjie Yan, Jian Zhang
https://arxiv.org/abs/2507.13661

Testing Autonomous Driving Systems -- What Really Matters and What Doesn't
Despite extensive research, the testing of autonomous driving systems (ADS) landscape remains fragmented, and there is currently no basis for an informed technical assessment of the importance and contribution of the current state of the art. This paper attempts to address this problem by exploring two complementary aspects. First, it proposes a framework for comparing existing test methods in terms of their intrinsic effectiveness and validity. It shows that many methods do not meet both of …

"Von der Einstellung" von Johann-Mattis List: https://wub.hypotheses.org/2895 "Ich habe […] mit mir persönlich vereinbart, dass ich mir fortan meine Forschung von niemandem mehr kaputtmachen lasse, ganz besonders nicht von mir selbst."

Label Uncertainty for Ultrasound Segmentation
Malini Shivaram, Gautam Rajendrakumar Gare, Laura Hutchins, Jacob Duplantis, Thomas Deiss, Thales Nogueira Gomes, Thong Tran, Keyur H. Patel, Thomas H Fox, Amita Krishnan, Deva Ramanan, Bennett DeBoisblanc, Ricardo Rodriguez, John Galeotti
https://arxiv.org/abs/2508.15635

Label Uncertainty for Ultrasound Segmentation
In medical imaging, inter-observer variability among radiologists often introduces label uncertainty, particularly in modalities where visual interpretation is subjective. Lung ultrasound (LUS) is a prime example-it frequently presents a mixture of highly ambiguous regions and clearly discernible structures, making consistent annotation challenging even for experienced clinicians. In this work, we introduce a novel approach to both labeling and training AI models using expert-supplied, per-pixe…