Tootfinder

Another passenger plane is lost in Russia.
This is the third since the war began. The other two were the Malaysia Airlines plane shot down over Ukraine and the Azerbaijan Airlines plane shot full of shrapnel over Grozny.
Can’t imagine why today’s plane would have been shot at considering it was in the Far East… but we’ll see.
Not sure why anyone would take the risk to fly to a Russian airport these days.
#russiaUkraineWar #russia #airtravel
https://www.khaleejtimes.com/world/russian-rescuers-find-missing-plane

@… I’m very much in the same boat, but given that there’s Akrapovič, well-known manufacturer of exhaust systems for motorcycles and performance cars, I could very well imagine someone saying, “bro, I had an Akropovič exhaust fitted to my Kosmaczewski MX-100, it’s so freaking fast now, gotta install Piotrowski brakes!”

@… I’m very much in the same boat, but given that there’s Akrapovič, well-known manufacturer of exhaust systems for motorcycles and performance cars, I could very well imagine someone saying, “bro, I had an Akropovič exhaust fitted to my Kosmaczewski MX-100, it’s so freaking fast now, gotta install Piotrowski brakes!”

You know what the most amazing thing about chatbots? They are agreeable? Imagine if we all supported each other in our theories and flights of fancy? It would be an interesting experience if nothing else,

Proportional Sensitivity in Generative Adversarial Network (GAN)-Augmented Brain Tumor Classification Using Convolutional Neural Network
Mahin Montasir Afif, Abdullah Al Noman, K. M. Tahsin Kabir, Md. Mortuza Ahmmed, Md. Mostafizur Rahman, Mufti Mahmud, Md. Ashraful Babu
https://arxiv.org/abs/2506.17165

Proportional Sensitivity in Generative Adversarial Network (GAN)-Augmented Brain Tumor Classification Using Convolutional Neural Network
Generative Adversarial Networks (GAN) have shown potential in expanding limited medical imaging datasets. This study explores how different ratios of GAN-generated and real brain tumor MRI images impact the performance of a CNN in classifying healthy vs. tumorous scans. A DCGAN was used to create synthetic images which were mixed with real ones at various ratios to train a custom CNN. The CNN was then evaluated on a separate real-world test set. Our results indicate that the model maintains hig…

Interface on demand: Towards AI native Control interfaces for 6G
Abhishek Dandekar, Prashiddha D. Thapa, Ashrafur Rahman, Julius Schulz-Zander
https://arxiv.org/abs/2508.15595 h…

Interface on demand: Towards AI native Control interfaces for 6G
Traditional standardized network interfaces face significant limitations, including vendor-specific incompatibilities, rigid design assumptions, and lack of adaptability for new functionalities. We propose a multi-agent framework leveraging large language models (LLMs) to generate control interfaces on demand between network functions (NFs). This includes a matching agent, which aligns required control functionalities with NF capabilities, and a code-generation agent, which generates the necess…

Inertial Imaging of Dual Mass Distributions on a Graphene Nanodrum: A Computational Study
Adhinarayan Naembin Ashok, Sanjam Bedi, Taha Ashraf Ali Shaikh, Jai Aadhithya Ramesh, Adarsh Ganesan
https://arxiv.org/abs/2508.02099

Inertial Imaging of Dual Mass Distributions on a Graphene Nanodrum: A Computational Study
This paper presents the possibility for inertial imaging of spatially patterned annular mass distributions of a circular graphene nanodrum resonator. By placing two distinct analytes in concentric annular regions, we harness the vibrational mode-specific sensitivities of the nanodrum to estimate their respective mass densities. An analytical formulation based on the Rayleigh-Ritz principle is developed to relate radial mass loading to modal frequency shifts. Finite element simulations are perfo…

Revealing the Void-Size Distribution of Silica Glass using Persistent Homology
Achraf Atila, Yasser Bakhouch, Zhuocheng Xie
https://arxiv.org/abs/2507.05484

Revealing the Void-Size Distribution of Silica Glass using Persistent Homology
Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on the ring statistics as a metric for the medium-range structure, which, however, provides an incomplete picture of the glassy structure. Here, we use atomistic simulations and state-of-the-art topological analysis tools, namely persistent homology (PH), to analyze the medium-range structure of the archetypal oxide g…