Tootfinder

A Be star-black hole binary with a wide orbit from LAMOST time-domain survey
Qian-Yu An, Yang Huang, Wei-Min Gu, Yong Shao, Zhi-Xiang Zhang, Tuan Yi, B. D. Lailey, T. A. A. Sigut, Kyle Akira Rocha, Meng Sun, Seth Gossage, Shi-Jie Gao, Shan-Shan Weng, Song Wang, Bowen Zhang, Xinlin Zhao, Senyu Qi, Shilong Liao, Jianghui Ji, Junfeng Wang, Jianfeng Wu, Mouyuan Sun, Xiang-Dong Li, Jifeng Liu

A Be star-black hole binary with a wide orbit from LAMOST time-domain survey
Binary systems consisting of an early type star and a black hole (BH) are crucial for understanding various astrophysical phenomena, particularly the origins of detected gravitational wave sources. Be binary systems are expected to represent a key evolutionary stage in hosting BHs. However, while hundreds of Be X-ray binaries are known, the only confirmed BH candidate in a Be binary remains highly controversial. We report the discovery of ALS 8814, a Be star-BH binary with a moderately eccentri…

Une fois de plus, ma sélection de lecture n’est pas rationnelle. Si je vois un titre comme “Autodafé, comment les livres ont gâché ma vie” dans une librairie, mon sang ne fait qu’un tour. Autodafé, putain de merde, il va falloir se mettre en branle et réagir.
Après cette première réaction, ma raison reprend le dessus...
#livre

Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning
Xiaofeng Pan, Jing Chen, Haitong Zhang, Menglin Xing, Jiayi Wei, Xuefeng Mu, Zhongqian Xie
https://arxiv.org/abs/2505.23298

Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning
Recent works of music representation learning mainly focus on learning acoustic music representations with unlabeled audios or further attempt to acquire multi-modal music representations with scarce annotated audio-text pairs. They either ignore the language semantics or rely on labeled audio datasets that are difficult and expensive to create. Moreover, merely modeling semantic space usually fails to achieve satisfactory performance on music recommendation tasks since the user preference spac…

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning
Esra Adiyeke, Tianqi Liu, Venkata Sai Dheeraj Naganaboina, Han Li, Tyler J. Loftus, Yuanfang Ren, Benjamin Shickel, Matthew M. Ruppert, Karandeep Singh, Ruogu Fang, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti
https://

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning
Traditional methods of surgical decision making heavily rely on human experience and prompt actions, which are variable. A data-driven system generating treatment recommendations based on patient states can be a substantial asset in perioperative decision-making, as in cases of intraoperative hypotension, for which suboptimal management is associated with acute kidney injury (AKI), a common and morbid postoperative complication. We developed a Reinforcement Learning (RL) model to recommend opti…

Jazzaria – Lost Insight
#acoustic

Jazzaria – Tilting Saints
#abstract

Jazzaria – All The Notes Go Up
#acoustic

Jazzaria – Fire and Forget
#byncnd

Trajet du jour entre Genève et Renens ou comment joindre l'utile Š l'agréable.
La bise est présente, j'espère aussi pour le retour.