Tootfinder

Cool that @… got mentioned in the "Pick of the week!" section of this "Smashing Security" podcast https://www.smashingsecurity.com/423-opera

423: Operation Endgame, deepfakes, and dead slugs
In this episode, Graham unravels Operation Endgame - the surprisingly stylish police crackdown that is seizing botnets, mocking malware authors with anime videos, and taunting cybercriminals via Telegram. Meanwhile, Carole exposes the AI-generated remote hiring threat. Could your next coworker be a

Boolean-network simplification and rule fitting to unravel chemotherapy resistance in non-small cell lung cancer
Alonso Espinoza, Eric Goles, Marco Montalva-Medel
https://arxiv.org/abs/2506.02525

Boolean-network simplification and rule fitting to unravel chemotherapy resistance in non-small cell lung cancer
Boolean networks are powerful frameworks for capturing the logic of gene-regulatory circuits, yet their combinatorial explosion hampers exhaustive analyses. Here, we present a systematic reduction of a 31-node Boolean model that describes cisplatin- and pemetrexed-resistance in non-small-cell lung cancer to a compact 9-node core that exactly reproduces the original attractor landscape. The streamlined network shrinks the state space by four orders of magnitude, enabling rapid exploration of cri…

Topological Machine Learning for Protein-Nucleic Acid Binding Affinity Changes Upon Mutation
Xiang Liu, Junjie Wee, Guo-Wei Wei
https://arxiv.org/abs/2505.22786

Topological Machine Learning for Protein-Nucleic Acid Binding Affinity Changes Upon Mutation
Understanding how protein mutations affect protein-nucleic acid binding is critical for unraveling disease mechanisms and advancing therapies. Current experimental approaches are laborious, and computational methods remain limited in accuracy. To address this challenge, we propose a novel topological machine learning model (TopoML) combining persistent Laplacian (from topological data analysis) with multi-perspective features: physicochemical properties, topological structures, and protein Tran…

Localization and splitting of a quantum droplet by immersing a heavy impurity
F. Bristy, G. A. Bougas, G. C. Katsimiga, S. I. Mistakidis
https://arxiv.org/abs/2506.19132

Localization and splitting of a quantum droplet by immersing a heavy impurity
We unravel the existence and nonequilibrium response of one-dimensional harmonically trapped droplet configurations in the presence of a central repulsive or attractive potential well mimicking the effect of a heavy impurity. For fixed negative chemical potentials, it is shown that droplets fragment into two for increasing repulsive potential heights, a process that occurs faster for larger widths. However, atoms from the droplet accumulate at the attractive potential, especially for wider ones…

Unraveling the Potential of Diffusion Models in Small Molecule Generation
Peining Zhang, Daniel Baker, Minghu Song, Jinbo Bi
https://arxiv.org/abs/2507.08005

Unraveling the Potential of Diffusion Models in Small Molecule Generation
Generative AI presents chemists with novel ideas for drug design and facilitates the exploration of vast chemical spaces. Diffusion models (DMs), an emerging tool, have recently attracted great attention in drug R\&D. This paper comprehensively reviews the latest advancements and applications of DMs in molecular generation. It begins by introducing the theoretical principles of DMs. Subsequently, it categorizes various DM-based molecular generation methods according to their mathematical and ch…