Tootfinder

Vielleicht sollten die Bauern statt für billigen Agrardiesel einfach mal für sinnvolle Klimaschutzmaßnahmen demonstrieren?
https://www.saechsische.de/lokales/dresden/erst-zu-trocken-jetzt-z…

Erst zu trocken, jetzt zu viel Regen: Dresdner Landwirt beklagt Wetterextreme
Für die Ernte von Raps und Weizen brauchen die Bauern im Schönfelder Hochland in Dresden trockene Tage. Doch diese sind erstmal nicht in Sicht. Weshalb sich die Landwirte sorgen.

Fully mixed virtual element schemes for steady-state poroelastic stress-assisted diffusion
Isaac Bermudez, Bryan Gomez-Vargas, Andres E. Rubiano, Ricardo Ruiz-Baier
https://arxiv.org/abs/2510.12307

Fully mixed virtual element schemes for steady-state poroelastic stress-assisted diffusion
We propose a fully mixed virtual element method for the numerical approximation of the coupling between stress-altered diffusion and linear elasticity equations with strong symmetry of total poroelastic stress (using the Hellinger--Reissner principle). A novelty of this work is that we introduce a less restrictive assumption on the stress-assisted diffusion coefficient, requiring an analysis of the perturbed diffusion equation using Banach spaces. The solvability of the continuous and discrete …

So the 40th something 2023 #NFLdraft pick Brian Amani Branch out of Tyrone, Georgia, a former Bama #CrimsonTide team member decided to rudely brush past 5 time #SuperBowl QB

Network-Specific Models for Multimodal Brain Response Prediction
Andrea Corsico, Giorgia Rigamonti, Simone Zini, Luigi Celona, Paolo Napoletano
https://arxiv.org/abs/2508.06499 …

Network-Specific Models for Multimodal Brain Response Prediction
In this work, we present a network-specific approach for predicting brain responses to complex multimodal movies, leveraging the Yeo 7-network parcellation of the Schaefer atlas. Rather than treating the brain as a homogeneous system, we grouped the seven functional networks into four clusters and trained separate multi-subject, multi-layer perceptron (MLP) models for each. This architecture supports cluster-specific optimization and adaptive memory modeling, allowing each model to adjust tempo…

Filtering for Creativity: Adaptive Prompting for Multilingual Riddle Generation in LLMs
Duy Le, Kent Ziti, Evan Girard-Sun, Sean O'Brien, Vasu Sharma, Kevin Zhu
https://arxiv.org/abs/2508.18709

Filtering for Creativity: Adaptive Prompting for Multilingual Riddle Generation in LLMs
Multilingual riddle generation challenges large language models (LLMs) to balance cultural fluency with creative abstraction. Standard prompting strategies -- zero-shot, few-shot, chain-of-thought -- tend to reuse memorized riddles or perform shallow paraphrasing. We introduce Adaptive Originality Filtering (AOF), a prompting framework that filters redundant generations using cosine-based similarity rejection, while enforcing lexical novelty and cross-lingual fidelity. Evaluated across three LL…

Mysteries of Capotauro - investigating the puzzling nature of an extreme F356W-dropout
Giovanni Gandolfi, Giulia Rodighiero, Marco Castellano, Adriano Fontana, Paola Santini, Mark Dickinson, Steven Finkelstein, Michele Catone, Antonello Calabr\`o, Emiliano Merlin, Laura Pentericci, Laura Bisigello, Andrea Grazian, Lorenzo Napolitano, Benedetta Vulcani, Anthony J. Taylor, Pablo Arrabal Haro, Allison Kirkpatrick, Bren E. Backhaus, Benne W. Holwerda, Marika Giulietti, Nikko J. Cleri, Eman…

Mysteries of Capotauro - investigating the puzzling nature of an extreme F356W-dropout
JWST has uncovered a diverse population of extreme near-infrared dropouts, including ultra high-redshift ($z>15$) galaxy candidates, dust-obscured galaxies challenging dust production theories, sources with strong Balmer breaks - possibly compact AGN in dense environments - and cold, sub-stellar Galactic objects. This work presents Capotauro, a F356W-dropout in the CEERS survey with F444W AB magnitude of $\sim27.68$ and a sharp $>3$ mag flux drop between $3.5{-}4.5\,μ$m, undetected below $3.5\…

The Shape of Surprise: Structured Uncertainty and Co-Creativity in AI Music Tools
Eric Browne
https://arxiv.org/abs/2509.25028 https://arxiv.org/pdf/2509.2…

The Shape of Surprise: Structured Uncertainty and Co-Creativity in AI Music Tools
Randomness plays a pivotal yet paradoxical role in computational music creativity: it can spark novelty, but unchecked chance risks incoherence. This paper presents a thematic review of contemporary AI music systems, examining how designers incorporate randomness and uncertainty into creative practice. I draw on the concept of structured uncertainty to analyse how stochastic processes are constrained within musical and interactive frameworks. Through a comparative analysis of six systems - Musi…

A deep dive down the broad-line region: permitted OI, CaII and FeII emission in an AGN Little Red Dot at z=5.3
Roberta Tripodi, Maru\v{s}a Brada\v{c}, Francesco D'Eugenio, Nicholas Martis, Gregor Rihtar\v{s}i\v{c}, Chris Willott, Laura Pentericci, Yoshihisa Asada, Antonello Calabr\`o, Giordano Felicioni, Gaia Gaspar, Anthony H. Gonzalez, Anishya Harshan, Xihan Ji, Jon Jude\v{z}, Brian C. Lemaux, Vladan Markov, Rosa M. Merida, Lorenzo Napolitano, G\"ael Noirot, Massimiliano Par…

A deep dive down the broad-line region: permitted OI, CaII and FeII emission in an AGN Little Red Dot at z=5.3
We present a spectroscopic analysis of a broad-line active galactic nucleus (AGN) selected as little red dot at $z = 5.3$ behind the Bullet cluster (Bz5.3), based on JWST/NIRCam and NIRSpec data. The detection of strong FeII, OI, and CaII triplet emission lines, along with the evidence of broad Balmer lines, provides unambiguous evidence of a broad-line region (BLR) and an accreting supermassive black hole. Notably, we report the first detection of the $\lambda1304$ bump (i.e., blend of OI$λ$1…

Fast and Scalable Gene Embedding Search: A Comparative Study of FAISS and ScaNN
Mohammad Saleh Refahi, Gavin Hearne, Harrison Muller, Kieran Lynch, Bahrad A. Sokhansanj, James R. Brown, Gail Rosen
https://arxiv.org/abs/2507.16978

Fast and Scalable Gene Embedding Search: A Comparative Study of FAISS and ScaNN
The exponential growth of DNA sequencing data has outpaced traditional heuristic-based methods, which struggle to scale effectively. Efficient computational approaches are urgently needed to support large-scale similarity search, a foundational task in bioinformatics for detecting homology, functional similarity, and novelty among genomic and proteomic sequences. Although tools like BLAST have been widely used and remain effective in many scenarios, they suffer from limitations such as high com…