Tootfinder

i am unreasonably upset about this it feels like i erased the odometer on an old reliable car 😭

I went downstairs, filled the kettle, waited for it boil, and poured the water into my mug.
I then popped back upstairs for 5 minutes to let it brew. Went back down to the kitchen, gave it a stir. "Hmm this looks a bit weak".
I'd only forgotten to put a bloody tea bag in the mug at the start of the exercise, hadn't I.
Obviously I have now contacted the government and arranged to hand in my British passport.
#Tea #FAIL

Upstream competition and exclusive content provision in media markets
Kiho Yoon
https://arxiv.org/abs/2506.15063 https://arxiv.org/pd…

Upstream competition and exclusive content provision in media markets
With a multilateral vertical contracting model of media markets, we examine upstream competition and contractual arrangements in content provision. We analyze the trade of content by the Nash bargaining solution and the downstream competition by the Hotelling location model. We characterize the equilibrium outcomes and the contractual arrangements for various vertical structures. We show that the possibility of exclusive contracts rises when the value of the premium content increases, the degre…

Fancy interior of the Piollet mansion in Wysox, PA which is now the home of a Dandy Mini Mart
#pennsylvania #photo #photography

DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning
Kunal Swami, Debtanu Gupta, Amrit Kumar Muduli, Chirag Jaiswal, Pankaj Kumar Bajpai
https://arxiv.org/abs/2506.14709

DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning
Depth estimation is crucial for intelligent systems, enabling applications from autonomous navigation to augmented reality. While traditional stereo and active depth sensors have limitations in cost, power, and robustness, dual-pixel (DP) technology, ubiquitous in modern cameras, offers a compelling alternative. This paper introduces DiFuse-Net, a novel modality decoupled network design for disentangled RGB and DP based depth estimation. DiFuse-Net features a window bi-directional parallax atte…

Bold predictions from Fantasy Football Today you need to know before your 2025 drafts

https://www.cbssports.com/fantasy/football

Enhancing photon-axion conversion probability with squeezed coherent states
Taiki Ikeda, Sugumi Kanno, Jiro Soda
https://arxiv.org/abs/2506.14354 https://

Enhancing photon-axion conversion probability with squeezed coherent states
In particle physics, axions and axion-like particles are ubiquitous. Remarkably, ultra-light axions could constitute dark matter or dark energy. Therefore, it is important to detect axions experimentally. In the presence of a magnetic field, a photon can be converted into an axion, and vice versa. Utilizing the conversion phenomenon, several methods for detecting axions have been proposed. To improve detectability, it is desirable to use quantum sensing. However, since the conversion process is…

Universal Rates of ERM for Agnostic Learning
Steve Hanneke, Mingyue Xu
https://arxiv.org/abs/2506.14110 https://arxiv.org/pdf/2506.14…

Universal Rates of ERM for Agnostic Learning
The universal learning framework has been developed to obtain guarantees on the learning rates that hold for any fixed distribution, which can be much faster than the ones uniformly hold over all the distributions. Given that the Empirical Risk Minimization (ERM) principle being fundamental in the PAC theory and ubiquitous in practical machine learning, the recent work of arXiv:2412.02810 studied the universal rates of ERM for binary classification under the realizable setting. However, the ass…

Fractal dimensions of complex networks: advocating for a topological approach
Rayna Andreeva, Hayde\'e Contreras-Peruyero, Sanjukta Krishnagopal, Nina Otter, Maria Antonietta Pascali, Elizabeth Thompson
https://arxiv.org/abs/2506.15236

Fractal dimensions of complex networks: advocating for a topological approach
Topological Data Analysis (TDA) uses insights from topology to create representations of data able to capture global and local geometric and topological properties. Its methods have successfully been used to develop estimations of fractal dimensions for metric spaces that have been shown to outperform existing techniques. In a parallel line of work, networks are ubiquitously used to model a variety of complex systems. Higher-order interactions, i.e., simultaneous interactions between more than …

Anomalous diffusion for mass transport phenomena I: Analytic solutions to time fractional diffusion
Nathaniel G. Hermann, M. Shane Hutson
https://arxiv.org/abs/2506.14043

Anomalous diffusion for mass transport phenomena I: Analytic solutions to time fractional diffusion
Mass transport problems are ubiquitous in diverse fields of physics and engineering. With the development of fractional calculus, many have taken to studying problems of fractional mass transport either through numerical simulations or through complex mathematical structures (e.g. Fox-H functions). Here, we present a set of analytic solutions to common time fractional diffusion problems, written in terms of Mittag-Leffler and M-Wright functions, as well as generalized fractional error and compl…