Tootfinder

Federal agencies now only have one more day to patch React2Shell bug https://therecord.media/react2shell-vulnerability-cisa-shortens-patch-deadline

Federal agencies now only have one more day to patch React2Shell bug https://therecord.media/react4shell-vulnerability-cisa-shortens-patch-deadline

#coding #debugging

from my link log —
GHC: from bug to merge.
http://neilmitchell.blogspot.com/2018/12/ghc-from-bug-to-merge.html
saved 2018-12-12 ht…

Dual-primal Isogeometric Tearing and Interconnecting Solvers for adaptively refined multi-patch configurations
Stefan Takacs, Stefan Tyoler
https://arxiv.org/abs/2510.08148 http…

Dual-primal Isogeometric Tearing and Interconnecting Solvers for adaptively refined multi-patch configurations
Isogeometric Analysis is a variant of the finite element method, where spline functions are used for the representation of both the geometry and the solution. Splines, particularly those with higher degree, achieve their full approximation power only if the solution is sufficiently regular. Since solutions are usually not regular everywhere, adaptive refinement is essential. Recently, a multi-patch-based adaptive refinement strategy based on recursive patch splitting has been proposed, which na…

phpc.social is now running Mastodon 4.5.0, released a little over three days ago. Thanks for your patience on this upgrade, which went a fair bit smoother thn the last non-patch-release bump. Have fun quoting folks! #mastoadmin

Vision-Language Alignment from Compressed Image Representations using 2D Gaussian Splatting
Yasmine Omri, Connor Ding, Tsachy Weissman, Thierry Tambe
https://arxiv.org/abs/2509.22615

Vision-Language Alignment from Compressed Image Representations using 2D Gaussian Splatting
Modern vision language pipelines are driven by RGB vision encoders trained on massive image text corpora. While these pipelines have enabled impressive zero shot capabilities and strong transfer across tasks, they still inherit two structural inefficiencies from the pixel domain: (i) transmitting dense RGB images from edge devices to the cloud is energy intensive and costly, and (ii) patch based tokenization explodes sequence length, stressing attention budgets and context limits. We explore 2D…

Patch-Based Diffusion for Data-Efficient, Radiologist-Preferred MRI Reconstruction
Rohan Sanda, Asad Aali, Andrew Johnston, Eduardo Reis, Jonathan Singh, Gordon Wetzstein, Sara Fridovich-Keil
https://arxiv.org/abs/2509.21531

Patch-Based Diffusion for Data-Efficient, Radiologist-Preferred MRI Reconstruction
Magnetic resonance imaging (MRI) requires long acquisition times, raising costs, reducing accessibility, and making scans more susceptible to motion artifacts. Diffusion probabilistic models that learn data-driven priors can potentially assist in reducing acquisition time. However, they typically require large training datasets that can be prohibitively expensive to collect. Patch-based diffusion models have shown promise in learning effective data-driven priors over small real-valued datasets,…

Series A, Episode 08 - Duel
MUTOID: Time Distort Six.
TRAVIS: Minimum scan, their sensors mustn't register the beam.
MUTOID: Scan complete, identification confirmed.
https://blake.torpidity.net/m/108/12 B7B5

The moving patch model with fractional diffusion
Sebasti\'an Flores-Sep\'ulveda, Gabrielle Nornberg, Alexander Quaas
https://arxiv.org/abs/2509.22234 https://

The moving patch model with fractional diffusion
In this paper we study the following one-dimensional reaction-diffusion problem $$ u_t+(-Δ)^s u=f(x-c t, u) \;\:\textrm{ in } \mathbb{R}\times (0,+\infty), $$ where $s>\frac{1}{2}$, $c \in \mathbb{R}$ is a prescribed velocity, and $f$ is of KPP type, which describes the evolution of a population in an advective environment subjected to nonlocal diffusion. We suppose the environment is such that it is only advantageous in a bounded ``patch", outside of which the species dies at an asymptoticall…

When will I learn? "Patch the firewall real quick like". It rebooted mid applying something and now it boots and says my bootloader is too old, And then hands here. *Face palm*

A Scalable AI Driven, IoT Integrated Cognitive Digital Twin for Multi-Modal Neuro-Oncological Prognostics and Tumor Kinetics Prediction using Enhanced Vision Transformer and XAI
Saptarshi Banerjee, Himadri Nath Saha, Utsho Banerjee, Rajarshi Karmakar, Jon Turdiev
https://arxiv.org/abs/2510.05123

A Scalable AI Driven, IoT Integrated Cognitive Digital Twin for Multi-Modal Neuro-Oncological Prognostics and Tumor Kinetics Prediction using Enhanced Vision Transformer and XAI
Neuro-oncological prognostics are now vital in modern clinical neuroscience because brain tumors pose significant challenges in detection and management. To tackle this issue, we propose a cognitive digital twin framework that combines real-time EEG signals from a wearable skullcap with structural MRI data for dynamic and personalized tumor monitoring. At the heart of this framework is an Enhanced Vision Transformer (ViT++) that includes innovative components like Patch-Level Attention Regulari…

Deep Learning-Based Cross-Anatomy CT Synthesis Using Adapted nnResU-Net with Anatomical Feature Prioritized Loss
Javier Sequeiro Gonz\'alez, Arthur Longuefosse, Miguel D\'iaz Benito, \'Alvaro Garc\'ia Mart\'in, Fabien Baldacci
https://arxiv.org/abs/2509.22394

Deep Learning-Based Cross-Anatomy CT Synthesis Using Adapted nnResU-Net with Anatomical Feature Prioritized Loss
We present a patch-based 3D nnUNet adaptation for MR to CT and CBCT to CT image translation using the multicenter SynthRAD2025 dataset, covering head and neck (HN), thorax (TH), and abdomen (AB) regions. Our approach leverages two main network configurations: a standard UNet and a residual UNet, both adapted from nnUNet for image synthesis. The Anatomical Feature-Prioritized (AFP) loss was introduced, which compares multilayer features extracted from a compact segmentation network trained on To…