Tootfinder

The LAX Automated People Mover (APM) is a new, free, electric train system that connects airport terminals, parking, and public transportation.
After delays, it is expected to open for public use in January 2026,
with final testing concluding in June 2026.
The 2.25-mile elevated guideway has six stations, and trains will run 24/7, arriving every two minutes during peak hours

Testing Lens Models of PLCK G165.7 67.0 Using Lensed SN H0pe
Aadya Agrawal, J. D. R. Pierel, Gautham Narayan, B. L. Frye, Jose M. Diego, Nikhil Garuda, Matthew Grayling, Anton M. Koekemoer, Kaisey S. Mandel, M. Pascale, David Vizgan, Rogier A. Windhorst
https://arxiv.org/abs/2510.07637

Testing Lens Models of PLCK G165.7+67.0 Using Lensed SN H0pe
Supernova H0pe is a multiply-imaged Type Ia supernova (SN Ia) and the second lensed SN to yield a measurement of the Hubble constant by the time-delay cosmography method, finding $H_0 = 75.4^{+8.1}_{-5.5} \text{km s}^{-1} \text{Mpc}^{-1}$. We investigate the seven lens modeling approaches used to derive $H_0$, assessing their agreement with $Λ\text{CDM}$ constraints from SN Ia surveys through a purely observational comparison. While photometrically derived magnifications yield distance moduli …

Revisiting MFCCs: Evidence for Spectral-Prosodic Coupling
Vitor Magno de O. S. Bezerra, Gabriel F. A. Bastos, Jugurta Montalv\~ao
https://arxiv.org/abs/2510.05922 https://

Revisiting MFCCs: Evidence for Spectral-Prosodic Coupling
Mel-frequency cepstral coefficients (MFCCs) are an important feature in speech processing. A deeper understanding of their properties can contribute to the work that is being done with both classical and deep learning models. This study challenges the long-held assumption that MFCCs lack relevant temporal information by investigating their relationship with speech prosody. Using a null hypothesis significance testing framework, a systematic assessment is made about the statistical independence …

The radial acceleration relation at the EDGE of galaxy formation: testing its universality in low-mass dwarf galaxies
Mariana P. J\'ulio, Justin I. Read, Marcel S. Pawlowski, Pengfei Li, Daniel Vaz, Jarle Brinchmann, Martin P. Rey, Oscar Agertz, Tom Holmes
https://arxiv.org/abs/2510.06905

The radial acceleration relation at the EDGE of galaxy formation: testing its universality in low-mass dwarf galaxies
A tight correlation between the baryonic and observed acceleration of galaxies has been reported over a wide range of mass ($10^8 < M_{\rm bar}/{\rm M}_\odot < 10^{11}$) - the Radial Acceleration Relation (RAR). This has been interpreted as evidence that dark matter is actually a manifestation of some modified weak-field gravity theory. In this paper, we study the radially resolved RAR of 12 nearby dwarf galaxies, with baryonic masses in the range $10^4 < M_{\rm bar}/{\rm M}_\odot < 10^{7.5}$, …

European countries may have to start shooting down Russian aircraft and drones that violate NATO airspace if Moscow keeps testing the alliance's resolve,
Czech President Petr Pavel said in an interview with the Sunday Times of London published Dec. 7.
"I believe there will be a moment,
if these violations continue,
where we will have to use stronger measures,
including potentially shooting down a Russian airplane or drones,"
Pavel  told the T…

Czech president says Europe may need to shoot down Russian aircraft, drones violating NATO airspace
Czech President Petr Pavel warned that repeated Russian airspace violations may eventually force Europe to shoot down Russian aircraft and drones, and said European countries must be ready to fight and win a war on their own if the U.S. is tied up elsewhere.

Unsupervised Speech Enhancement using Data-defined Priors
Dominik Klement, Matthew Maciejewski, Sanjeev Khudanpur, Jan \v{C}ernock\'y, Luk\'a\v{s} Burget
https://arxiv.org/abs/2509.22942

Unsupervised Speech Enhancement using Data-defined Priors
The majority of deep learning-based speech enhancement methods require paired clean-noisy speech data. Collecting such data at scale in real-world conditions is infeasible, which has led the community to rely on synthetically generated noisy speech. However, this introduces a gap between the training and testing phases. In this work, we propose a novel dual-branch encoder-decoder architecture for unsupervised speech enhancement that separates the input into clean speech and residual noise. Adve…