Tootfinder

An interferometric mid-infrared study of the eruptive star binary Z CMa with MATISSE/VLTI. I. Imaging the protoplanetary disks during the 2023 outburst
F. Lykou, J. Varga, F. Cruz-Sa\'enz de Miera, P. \'Abrah\'am, \'A. K\'osp\'al, B. Lopez, T. Henning, S. Wolf, G. Weigelt, F. Millour, M. Hogerheijde, L. Chen, T. Ratzka, W. Danchi, P. Boley, J. -C. Augereau, P. Priolet

An interferometric mid-infrared study of the eruptive star binary Z CMa with MATISSE/VLTI. I. Imaging the protoplanetary disks during the 2023 outburst
The mid-infrared (MIR) emitting regions of the individual protoplanetary disks in the binary system Z CMa are resolved by MATISSE/VLTI. The observations were obtained during a serendipitous large outburst of the HBe star that lasted more than 100 days, while the FUor companion is presumed to be in quiescence. The size of the MIR-emitting disk region of the more massive HBe star increases toward longer wavelengths from $<14$ mas at 3.5$μm$ to $\ll 50$ mas at 11.5$μm$ . The lack of substructure…

Hm...
This sounds like something that needs to be changed...
... dunno if on the side of #PeerTube or #Mastodon.
https://

Wearable Music2Emotion : Assessing Emotions Induced by AI-Generated Music through Portable EEG-fNIRS Fusion
Sha Zhao, Song Yi, Yangxuan Zhou, Jiadong Pan, Jiquan Wang, Jie Xia, Shijian Li, Shurong Dong, Gang Pan
https://arxiv.org/abs/2508.04723

Wearable Music2Emotion : Assessing Emotions Induced by AI-Generated Music through Portable EEG-fNIRS Fusion
Emotions critically influence mental health, driving interest in music-based affective computing via neurophysiological signals with Brain-computer Interface techniques. While prior studies leverage music's accessibility for emotion induction, three key limitations persist: \textbf{(1) Stimulus Constraints}: Music stimuli are confined to small corpora due to copyright and curation costs, with selection biases from heuristic emotion-music mappings that ignore individual affective profiles. \text…

Revisiting Modeling and Evaluation Approaches in Speech Emotion Recognition: Considering Subjectivity of Annotators and Ambiguity of Emotions
Huang-Cheng Chou, Chi-Chun Lee
https://arxiv.org/abs/2510.05934

Revisiting Modeling and Evaluation Approaches in Speech Emotion Recognition: Considering Subjectivity of Annotators and Ambiguity of Emotions
Over the past two decades, speech emotion recognition (SER) has received growing attention. To train SER systems, researchers collect emotional speech databases annotated by crowdsourced or in-house raters who select emotions from predefined categories. However, disagreements among raters are common. Conventional methods treat these disagreements as noise, aggregating labels into a single consensus target. While this simplifies SER as a single-label task, it ignores the inherent subjectivity of…

Mean-Variance Stackelberg Games with Asymmetric Information
Yu-Jui Huang, Shihao Zhu
https://arxiv.org/abs/2509.03669 https://arxiv.org/pdf/2509.03669

Mean-Variance Stackelberg Games with Asymmetric Information
This paper considers two investors who perform mean-variance portfolio selection with asymmetric information: one knows the true stock dynamics, while the other has to infer the true dynamics from observed stock evolution. Their portfolio selection is interconnected through relative performance concerns, i.e., each investor is concerned about not only her terminal wealth, but how it compares to the average terminal wealth of both investors. We model this as Stackelberg competition: the partiall…

A Calculus of Variations Approach to Stochastic Control
Matthew Lorig
https://arxiv.org/abs/2509.01744 https://arxiv.org/pdf/2509.01744

A Calculus of Variations Approach to Stochastic Control
We use classical tools from calculus of variations to formally derive necessary conditions for a Markov control to be optimal in a standard finite time horizon stochastic control problem. As an example, we solve the well-known Merton portfolio optimization problem.

Let's be honest. I've been a strong supporter of #OpenPGP (or #PGP in general) for a long time. And I still can't think of any real alternative that exists right now. And I kept believing it's not "that hard" — but it doesn't seem like it's getting any easier. The big problem with standards like that are tools.
#WebOfTrust is hard, and impractical for a lot of people. It doesn't really help how many tools implement trust. I mean, I sometimes receive encrypted mail via #EvolutionMail — and Evolution makes it really hard for me to reply encrypted without permanently trusting the sender!
The whole SKS keyserver mess doesn't help PGP at all. Nowadays finding someone's key is often hard. If you're lucky, WKD will work. If you're not, you're up for searching a bunch of keyservers, GitHub, or perhaps random websites. And it definitely doesn't help that some of these may hold expired keys, with people uploading their new key only to a subset of them or forgetting to do it.
On top of that, we have interoperability issues. Definitely doesn't speak well when GnuPG can't import keys from popular keyservers over lack of UIDs. And that's just the tip of the iceberg.
Now with diverging OpenPGP standards around the corner, we're a step ahead from true interoperability problems. Just imagine convincing someone to use OpenPGP, only to tell them afterwards that they've used non-portable tool / settings, and their key doesn't work for you.
That's really not how you advocate for #encryption.

Turbulence and dust fragility in protoplanetary discs
Simin Tong, Richard Alexander, Giovanni Rosotti
https://arxiv.org/abs/2509.24818 https://arxiv.org/pd…

Turbulence and dust fragility in protoplanetary discs
Dust growth from micron- to planet-size in protoplanetary discs involves multiple physical processes, including dust growth and fragmentation, the streaming instability, and pebble accretion. Disc turbulence and dust fragility matter at almost every stage. Previous studies typically vary one of them while fixing the other, failing to provide a complete picture. Here, we use analytical models and numerical dust evolution models DustPy to study the combinations of gas turbulence and dust fragilit…

Parallel Nested Slice Sampling for Gravitational Wave Parameter Estimation
David Yallup, Metha Prathaban, James Alvey, Will Handley
https://arxiv.org/abs/2509.24949 https://

Parallel Nested Slice Sampling for Gravitational Wave Parameter Estimation
Inferring parameters and testing hypotheses from gravitational wave signals is a computationally intensive task central to modern astrophysics. Nested sampling, a Bayesian inference technique, has become an established standard for this in the field. However, most common implementations lack the ability to fully utilize modern hardware acceleration. In this work, we demonstrate that when nested sampling is reformulated in a natively vectorized form and run on modern GPU hardware, we can perform…

#PrettyFlyForAWiFi