Tootfinder

"""
In melancholy, the spirits are carried away by an agitation, but a weak agitation that lacks power or violence, a sort of impotent upset that follows neither a particular path nor the aperta opercula [open ways], but traverses the cerebral matter constantly creating new pores. Yet the spirits do not wander far on the new paths they create, and their agitation dies down rapidly, as their strength is quickly spent and motion comes to a halt: ‘non longe perveniunt’ [they do not reach far]. A trouble of this nature, common to all delirium, does not have the power to produce on the surface of the body the violent movements or the cries to be observed in mania and frenzy. Melancholy never attains frenzy; it is a madness always at the limits of its own impotence. That paradox is explained by the secret alterations in the spirits. Ordinarily, they travel with the speed and instantaneous transparency of rays of light, but in melancholy they become weighed down with night, becoming ‘obscure, thick and dark’, and the images of things that they bring before consciousness are ‘in a shadow, or covered with darkness’. As a result they move more slowly, and are more like a dark, chemical vapour than pure light. This chemical vapour is acid in nature, rather than sulphurous or alcoholic, for in acid vapours the particles are mobile and incapable of repose, but their activity is weak and without consequence. When they are distilled, all that remains in the still is a kind of insipid phlegm. Acid vapours, therefore, are taken to have the same properties as melancholy, whereas alcoholic vapours, which are always ready to burst into flames, are more related to frenzy, and sulphurous vapours bring on mania, as they are agitated by continuous, violent movement. If the ‘formal reason and causes’ of melancholy were to be sought, it made sense to look for them in the vapours that rose up from the blood to the head, and which had degenerated into ‘an acetous or sharp distillation’. A cursory glance seems to indicate that a melancholy of spirits and a whole chemistry of humours lies behind Willis’ analyses, but in fact his guiding principle mostly reflects the immediate qualities of the melancholic illness: an impotent disorder, and the shadow that comes over the spirit with an acrid acidity that slowly corrodes the heart and the mind. The chemistry of acids is not an explanation of the symptoms, but a qualitative option: a whole phenomenology of melancholic experience.
"""
(Michel Foucault, History of Madness)

Gibraltar celebrates its return to Europe
After nearly a decade in limbo and years of negotiations,
a treaty announced in June and set to come into effect over coming months,
will scrap most barriers to travel and trade that went up after Britain’s divorce from the E.U. became official at the end of 2020.

Some 40,000 Gibraltarians will regain what millions of traveling Brits miss most:
the ability to wander unfettered, without passports or time limits, througho…

The Brits who beat Brexit: Gibraltar celebrates its return to Europe
Nearly a decade after Britain quit the E.U., British residents of Gibraltar on the southern tip of Spain, will regain travel and commercial access under a treaty.

VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability
S. Satheesh Sheeba, R. J. Assef, T. Anguita, P. S\'anchez-S\'aez, R. Shirley, T. T. Ananna, F. E. Bauer, A. Bobrick, C. G. Bornancini, S. E. I. Bosman, W. N. Brandt, D. De Cicco, B. Czerny, M. Fatovi\'c, K. Ichikawa, D. Ili\'c, A. B. Kova\v{c}evi\'c, G. Li, M. Liao, A. Rojas-Lilay\'u, M. Marculewicz, D. Marsango, C. Mazzucchelli, T. Mkrtchyan, S. Panda, A. Peca, B. Rani, C. Ricci, G. T. …

VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability
The Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/optical/NIR monitoring of a significant fraction of these objects. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshifts estimates which are traditionally much less reliable for AGN than fo…

Survey of Surveys. II. Stellar parameters for 23 millions of stars
A. Turchi, E. Pancino, A. Avdeeva, F. Rossi, M. Tsantaki, P. M. Marrese, S. Marinoni, N. Sanna, G. Fanari, D. Alvarez Garay, M. Echeveste, S. Nedhath, S. Rani, E. Reggiani, S. Saracino, L. Steinbauer, G. Thomas, F. Gran, G. Guiglion
https://arxiv.org/abs/2507.059…

Survey of Surveys. II. Stellar parameters for 23 millions of stars
In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a project to critically compile survey results in a single catalogue, facilitating the scientific use of the available information. In this second release, we present two new catalogs of stellar parameters (Teff, logg, and [Fe/H]). To build the first catalog, SoS-Sp…

Turbulent wind thrust control to reduce pitch motion of floating wind platforms with improved rotor operation
Yi Zhang, Peter Stansby, David Apsley, Hannah Mullings
https://arxiv.org/abs/2509.11707

Turbulent wind thrust control to reduce pitch motion of floating wind platforms with improved rotor operation
For the dynamic analysis of floating offshore wind turbines (FOWTs) in realistic operating environment, this paper develops a coupled aero-hydro-mooring-servo model applicable to turbulent wind and irregular sea states with high computational efficiency. A modified rotor control strategy with platform motion feedback is proposed with a novel gain-scheduling technique to mitigate the negative damping effect on platform motions and decouple the rotor dynamics from the platform dynamics for better…

Towards Multimodal Understanding via Stable Diffusion as a Task-Aware Feature Extractor
Vatsal Agarwal, Matthew Gwilliam, Gefen Kohavi, Eshan Verma, Daniel Ulbricht, Abhinav Shrivastava
https://arxiv.org/abs/2507.07106

Towards Multimodal Understanding via Stable Diffusion as a Task-Aware Feature Extractor
Recent advances in multimodal large language models (MLLMs) have enabled image-based question-answering capabilities. However, a key limitation is the use of CLIP as the visual encoder; while it can capture coarse global information, it often can miss fine-grained details that are relevant to the input query. To address these shortcomings, this work studies whether pre-trained text-to-image diffusion models can serve as instruction-aware visual encoders. Through an analysis of their internal re…

A survey of diversity quantification in natural language processing: The why, what, where and how
Louis Est\`eve, Marie-Catherine de Marneffe, Nurit Melnik, Agata Savary, Olha Kanishcheva
https://arxiv.org/abs/2507.20858

A survey of diversity quantification in natural language processing: The why, what, where and how
The concept of diversity has received increased consideration in Natural Language Processing (NLP) in recent years. This is due to various motivations like promoting and inclusion, approximating human linguistic behavior, and increasing systems' performance. Diversity has however often been addressed in an ad hoc manner in NLP, and with few explicit links to other domains where this notion is better theorized. We survey articles in the ACL Anthology from the past 6 years, with "diversity" or "d…

The Nineteenth Data Release of the Sloan Digital Sky Survey
SDSS Collaboration, Gautham Adamane Pallathadka, Mojgan Aghakhanloo, James Aird, Andr\'es Almeida, Singh Amrita, Friedrich Anders, Scott F. Anderson, Stefan Arseneau, Consuelo Gonz\'alez Avila, Shir Aviram, Catarina Aydar, Carles Badenes, Jorge K. Barrera-Ballesteros, Franz E. Bauer, Aida Behmard, Michelle Berg, F. Besser, Christian Moni Bidin, Dmitry Bizyaev, Guillermo Blanc, Michael R. Blanton, Jo Bovy, William Niels…

The Nineteenth Data Release of the Sloan Digital Sky Survey
Mapping the local and distant Universe is key to our understanding of it. For decades, the Sloan Digital Sky Survey (SDSS) has made a concerted effort to map millions of celestial objects to constrain the physical processes that govern our Universe. The most recent and fifth generation of SDSS (SDSS-V) is organized into three scientific ``mappers". Milky Way Mapper (MWM) that aims to chart the various components of the Milky Way and constrain its formation and assembly, Black Hole Mapper (BHM),…

One More Glance with Sharp Eyes: Rethinking Lightweight Captioning as a Practical Visual Specialist
Junha Song, Yongsik Jo, So Yeon Min, Quanting Xie, Taehwan Kim, Yonatan Bisk, Jaegul Choo
https://arxiv.org/abs/2508.21451

One More Glance with Sharp Eyes: Rethinking Lightweight Captioning as a Practical Visual Specialist
Image captioning is fundamental for applications like video instruction systems and exploration robots, yet deploying such models on local devices is challenging due to the high computational demands of multimodal large language models (MLLMs). To address this, we first explore lightweight captioning by implementing a specialist based on a 125M-parameter language model, 56 times smaller than LLaMA-7B, and evaluating its performance on both single-sentence and detailed captioning tasks. Surprisi…

Synthesizing Sheet Music Problems for Evaluation and Reinforcement Learning
Zhilin Wang, Zhe Yang, Yun Luo, Yafu Li, Haoran Zhang, Runzhe Zhan, Derek F. Wong, Jizhe Zhou, Yu Cheng
https://arxiv.org/abs/2509.04059

Synthesizing Sheet Music Problems for Evaluation and Reinforcement Learning
Enhancing the ability of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) to interpret sheet music is a crucial step toward building AI musicians. However, current research lacks both evaluation benchmarks and training data for sheet music reasoning. To address this, we propose the idea of synthesizing sheet music problems grounded in music theory, which can serve both as evaluation benchmarks and as training data for reinforcement learning with verifiable rewards (RLVR…