Tootfinder

“The Michigan doctor is Bernie’s true heir.” 🔥
It’s Dr. Abdul El-Sayed
– epidemiologist, former Detroit Health Director, and wrote the book on Medicare for All. 
𝗜’𝗺 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝘁𝗼 𝗯𝗲 𝗠𝗶𝗰𝗵𝗶𝗴𝗮𝗻’𝘀 𝗻𝗲𝘅𝘁 𝗨.𝗦. 𝗦𝗲𝗻𝗮𝘁𝗼𝗿. In public service,
I’ve seen how broken politics puts profits over people.
That’s why I led the effort to cancel $700 million in medical debt for 300,000 Michiganders
— 𝘣𝘦𝘤𝘢𝘶𝘴𝘦 𝘯𝘰 𝘰𝘯𝘦 𝘴𝘩𝘰𝘶𝘭𝘥 𝘨𝘰 𝘣𝘳𝘰𝘬𝘦 𝘫𝘶𝘴𝘵 𝘧𝘰𝘳 𝘨𝘦𝘵𝘵𝘪𝘯𝘨 𝘴𝘪𝘤𝘬.
Our campaign is prou…

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I’ve been mulling my own WCAG3 post, but my TL;DR on Karl’s post is essentially the same as I would have written:
“WCAG 3 is not ready for you to use as a compliance framework. Not even close.”
https://afixt.com/why-now-is-not-the-time-to-think-about-wcag-3/…

Why Now Is Not the Time to Think About WCAG 3 - AFixt
If you work in accessibility or are responsible for compliance at your organization, you’ve probably heard about WCAG 3.0. The W3C has been developing it for years, and the most recent Working Draft was released in September 2025. At first glance, it feels like a big leap forward: a standard that promises to address gaps […]

Support-Projected Petz Monotone Geometry of Two-Qubit Families: Three-Channel Identity and Non-Reduction of Curvatures
Gunhee Cho, Jeongwoo Jae
https://arxiv.org/abs/2509.14578 …

Support-Projected Petz Monotone Geometry of Two-Qubit Families: Three-Channel Identity and Non-Reduction of Curvatures
We investigate the information geometry of pure two-qubit variational families by pulling back arbitrary Petz monotone quantum metrics to circuit-defined submanifolds and making them intrinsic via support projection onto the active numerical range of the quantum Fisher information tensor. This framework strictly generalizes the symmetric logarithmic derivative (SLD/Bures) case and includes, as special examples, the Wigner-Yanase and Bogoliubov-Kubo-Mori metrics among many others. Our first main…

Indoor Airflow Imaging Using Physics-Informed Background-Oriented Schlieren Tomography
Arjun Teh, Wael H. Ali, Joshua Rapp, Hassan Mansour
https://arxiv.org/abs/2509.14442 https…

Indoor Airflow Imaging Using Physics-Informed Background-Oriented Schlieren Tomography
We develop a framework for non-invasive volumetric indoor airflow estimation from a single viewpoint using background-oriented schlieren (BOS) measurements and physics-informed reconstruction. Our framework utilizes a light projector that projects a pattern onto a target back-wall and a camera that observes small distortions in the light pattern. While the single-view BOS tomography problem is severely ill-posed, our proposed framework addresses this using: (1) improved ray tracing, (2) a physi…

1Q: First-Generation Wireless Systems Integrating Classical and Quantum Communication
Petar Popovski, \v{C}edomir Stefanovi\'c, Beatriz Soret, Israel Leyva-Mayorga, Shashi Raj Pandey, Ren\'e B{\o}dker Christensen, Jakob Kaltoft S{\o}ndergaard, Kristian Skafte Jensen, Thomas Garm Pedersen, Angela Sara Cacciapuoti, Lajos Hanzo
https://

1Q: First-Generation Wireless Systems Integrating Classical and Quantum Communication
We sketch out the concept of 1Q, the first wireless generation of integrated classical and quantum communication. The 1Q framework features quantum base stations (QBSs) that support entanglement distribution via free-space optical links alongside traditional radio communications. Key new components include quantum cells, quantum user equipment (QUEs), and hybrid resource allocation spanning classical time-frequency and quantum entanglement domains. Several application scenarios are discussed an…

Dez Bryant envisions big things for one Raiders rookie wide receiver https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/dez-bryant-envisions-big-things-raiders-rookie-wide-receiver/7ef8c9553d26…

BIPOLAR: Polarization-based granular framework for LLM bias evaluation
Martin Pavl\'i\v{c}ek, Tom\'a\v{s} Filip, Petr Sos\'ik
https://arxiv.org/abs/2508.11061 https:…

BIPOLAR: Polarization-based granular framework for LLM bias evaluation
Large language models (LLMs) are known to exhibit biases in downstream tasks, especially when dealing with sensitive topics such as political discourse, gender identity, ethnic relations, or national stereotypes. Although significant progress has been made in bias detection and mitigation techniques, certain challenges remain underexplored. This study proposes a reusable, granular, and topic-agnostic framework to evaluate polarisation-related biases in LLM (both open-source and closed-source). …

Generative Co-Design of Antibody Sequences and Structures via Black-Box Guidance in a Shared Latent Space
Yinghua Yao, Yuangang Pan, Xixian Chen
https://arxiv.org/abs/2508.11424

Generative Co-Design of Antibody Sequences and Structures via Black-Box Guidance in a Shared Latent Space
Advancements in deep generative models have enabled the joint modeling of antibody sequence and structure, given the antigen-antibody complex as context. However, existing approaches for optimizing complementarity-determining regions (CDRs) to improve developability properties operate in the raw data space, leading to excessively costly evaluations due to the inefficient search process. To address this, we propose LatEnt blAck-box Design (LEAD), a sequence-structure co-design framework that opt…

Dez Bryant envisions big things for one Raiders rookie wide receiver https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/dez-bryant-envisions-big-things-raiders-rookie-wide-receiver/7ef8c9553d26…

Counterfactual Survival Q Learning for Longitudinal Randomized Trials via Buckley James Boosting
Jeongjin Lee, Jong-Min Kim
https://arxiv.org/abs/2508.11060 https://

Counterfactual Survival Q Learning for Longitudinal Randomized Trials via Buckley James Boosting
We propose a Buckley James (BJ) Boost Q learning framework for estimating optimal dynamic treatment regimes under right censored survival data, tailored for longitudinal randomized clinical trial settings. The method integrates accelerated failure time models with iterative boosting techniques, including componentwise least squares and regression trees, within a counterfactual Q learning framework. By directly modeling conditional survival time, BJ Boost Q learning avoids the restrictive propor…