Tootfinder

Protoplanetary disc population synthesis I. Constraining disc parameters to reproduce disc observations
Jose L. Gomez, Octavio M. Guilera, Marcelo M. Miller Bertolami, Elisa Castro-Mart\'inez, Mar\'ia Paula Ronco
https://arxiv.org/abs/2510.06978

Protoplanetary disc population synthesis I. Constraining disc parameters to reproduce disc observations
Context. Protoplanetary discs are the birthplaces of planets. Recent studies highlight the role of stellar mass sampling in determining disc lifetimes from the observed fraction of stars with discs. Low-mass stars tend to host longer-lived discs, allowing planet formation via solid accretion. Observations also reveal a strong correlation between stellar (and substellar) mass and accretion rate, typically following $\dot{M}\propto M_\star^2$. Aims. We aim to identify the optimal parameters of a …

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Rui Guo, Yi Zhang, Yhonatan Kvich, Tianyao Huang, Maokun Li, Yonina C. Eldar
https://arxiv.org/abs/2509.04860

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Electromagnetic (EM) imaging is an important tool for non-invasive sensing with low-cost and portable devices. One emerging application is EM stroke imaging, which enables early diagnosis and continuous monitoring of brain strokes. Quantitative imaging is achieved by solving an inverse scattering problem (ISP) that reconstructs permittivity and conductivity maps from measurements. In general, the reconstruction accuracy is limited by its inherent nonlinearity and ill-posedness. Existing methods…

Decoupled Entity Representation Learning for Pinterest Ads Ranking
Jie Liu, Yinrui Li, Jiankai Sun, Kungang Li, Han Sun, Sihan Wang, Huasen Wu, Siyuan Gao, Paulo Soares, Nan Li, Zhifang Liu, Haoyang Li, Siping Ji, Ling Leng, Prathibha Deshikachar
https://arxiv.org/abs/2509.04337

Decoupled Entity Representation Learning for Pinterest Ads Ranking
In this paper, we introduce a novel framework following an upstream-downstream paradigm to construct user and item (Pin) embeddings from diverse data sources, which are essential for Pinterest to deliver personalized Pins and ads effectively. Our upstream models are trained on extensive data sources featuring varied signals, utilizing complex architectures to capture intricate relationships between users and Pins on Pinterest. To ensure scalability of the upstream models, entity embeddings are …

A Sentinel-3 foundation model for ocean colour
Geoffrey Dawson, Remy Vandaele, Andrew Taylor, David Moffat, Helen Tamura-Wicks, Sarah Jackson, Rosie Lickorish, Paolo Fraccaro, Hywel Williams, Chunbo Luo, Anne Jones
https://arxiv.org/abs/2509.21273

A Sentinel-3 foundation model for ocean colour
Artificial Intelligence (AI) Foundation models (FMs), pre-trained on massive unlabelled datasets, have the potential to drastically change AI applications in ocean science, where labelled data are often sparse and expensive to collect. In this work, we describe a new foundation model using the Prithvi-EO Vision Transformer architecture which has been pre-trained to reconstruct data from the Sentinel-3 Ocean and Land Colour Instrument (OLCI). We evaluate the model by fine-tuning on two downstrea…

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services
Farid Zaredar, Morteza Amini
https://arxiv.org/abs/2508.14703 https://

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services
The emergence of smart grids and advanced metering infrastructure (AMI) has revolutionized energy management. Unlike traditional power grids, smart grids benefit from two-way communication through AMI, which surpasses earlier automated meter reading (AMR). AMI enables diverse demand- and supply-side utilities such as accurate billing, outage detection, real-time grid control, load forecasting, and value-added services. Smart meters play a key role by delivering consumption values at predefined …

I'm starting to play with an Epson HX-20; interesting little portable from the early 80s.
I've just figured out the tape has a file from August 1984. It's a basic file called TILL, now if I can get the serial working reliably I can dump it, but I'm having a problem of it complaining about battery voltage which seems common on it. Some playing needed.
#retrocomputing

Variable selection for minimum-variance portfolios
Guilherme V. Moura, Andr\'e P. Santos, Hudson S. Torrent
https://arxiv.org/abs/2508.14986 https://ar…

Variable selection for minimum-variance portfolios
Machine learning (ML) methods have been successfully employed in identifying variables that can predict the equity premium of individual stocks. In this paper, we investigate if ML can also be helpful in selecting variables relevant for optimal portfolio choice. To address this question, we parameterize minimum-variance portfolio weights as a function of a large pool of firm-level characteristics as well as their second-order and cross-product transformations, yielding a total of 4,610 predicto…

Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
Victor-Alexandru P\u{a}durean, Tung Phung, Nachiket Kotalwar, Michael Liut, Juho Leinonen, Paul Denny, Adish Singla
https://arxiv.org/abs/2509.10647

Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses that fail to accommodate the diverse needs of students and do not reflect the style of human-written feedback from tutors or peers. In this study, we…

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Paola Pinilla, Anibal Sierra, Nicolas T. Kurtovic, Rossella Anania, Sean Andrews, John Carpenter, Osmar Guerra-Alvarado, Feng Long, Sebastian Marino, Miguel Vioque, Ke Zhang
https://arxiv.org/abs/2509.19442

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Protoplanetary discs in the Upper Scorpius star-forming region are excellent laboratories to investigate late stages of planet formation. In this work, we analyse the morphology of the dust continuum emission of 121 discs from an ALMA Band 7 survey of the Upper Scorpius region. This analysis is done in the visibility plane, to measure the flux, geometry and characterise potential structures. We compare the results with state-of-the art gas and dust evolution models that include external photoev…

Evidence For Turbulent Concentration In Particle-Laden Midplane Layers of Planet-Forming Disks
Orkan M. Umurhan, Debanjan Sengupta, Paul R. Estrada
https://arxiv.org/abs/2508.05858

Evidence For Turbulent Concentration In Particle-Laden Midplane Layers of Planet-Forming Disks
In this study we investigate the axisymmetric, weakly turbulent state of settled particle layers in a localized model of a protoplanetary disk. We focus on conditions in which the large-scale axisymmetric filaments typically associated with the streaming instability (SI) either cannot form or have not yet developed. Under these circumstances, we observe small-scale particle clumping consistent with turbulent concentration (TC), in which short particle filaments collect along regions of high gas…