Tootfinder

Half of North Korea's first missile shipment to Russia exploded in mid-air — now they strike Ukrainian targets with deadly precision - Euromaidan Press
https://euromaidanpress.com/2025/06/10/half-of-north-koreas-first-missile-shipment-to-russia-exploded-in-mid-air-now-they-strike-ukrainian-targets-with-deadly-precision/

Good news! Iskander short-range ballistic missiles are used a lot against civilian targets in Ukraine.
https://kyivindependent.com/ukraine-strikes-russian-missile-base-in-bryansk-oblast-damages-…

Ukraine strikes Russian missile base in Bryansk Oblast, damages Iskander launchers, Ukrainian military says
The strike reportedly destroyed one Iskander missile launcher and seriously damaged two others.

A structural nested rate model for estimating the effects of time-varying exposure on recurrent event outcomes in the presence of death
Daniel Mork, Robert L. Strawderman, Michelle Audirac, Francesca Dominici, Ashkan Ertefaie
https://arxiv.org/abs/2506.07910

A structural nested rate model for estimating the effects of time-varying exposure on recurrent event outcomes in the presence of death
Assessing the causal effect of time-varying exposures on recurrent event processes is challenging in the presence of a terminating event. Our objective is to estimate both the short-term and delayed marginal causal effects of exposures on recurrent events while addressing the bias of a potentially correlated terminal event. Existing estimators based on marginal structural models and proportional rate models are unsuitable for estimating delayed marginal causal effects for many reasons, and furt…

A characterization of all graphs cospectral to the double star $P_2(1,n)$
Emily Barranca, Michael D. Barrus
https://arxiv.org/abs/2506.06934 https://

A characterization of all graphs cospectral to the double star $P_2(1,n)$
We examine the adjacency spectrum of trees with diameter three, also referred to as double stars. Using $P_2(a,b)$ to denote a double star with $ a$ and $b$ leaves at its respective endpoints, we discuss graphs which are cospectral to double stars for various parameters $a$ and $b$. In particular, we give constructions for graphs cospectral to $P_2(1,2k)$ for integers $k$. Lastly, we show that the double star $P_2(1,n)$ is determined by its spectrum when $n$ is odd. That is, if a graph $G$ cosp…

Neural Responses to Affective Sentences Reveal Signatures of Depression
Aditya Kommineni, Woojae Jeong, Kleanthis Avramidis, Colin McDaniel, Myzelle Hughes, Thomas McGee, Elsi Kaiser, Kristina Lerman, Idan A. Blank, Dani Byrd, Assal Habibi, B. Rael Cahn, Sudarsana Kadiri, Takfarinas Medani, Richard M. Leahy, Shrikanth Narayanan
https://

Neural Responses to Affective Sentences Reveal Signatures of Depression
Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core functions such as emotional and self-referential processing are affected. We investigate how depression alters the temporal dynamics of emotional processing by measuring neural responses to self-referential affective sentences using surface electroencephalography (EEG) in healthy and depressed individuals. Our results r…

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study
Leon Mayer, Tim R\"adsch, Dominik Michael, Lucas Luttner, Amine Yamlahi, Evangelia Christodoulou, Patrick Godau, Marcel Knopp, Annika Reinke, Fiona Kolbinger, Lena Maier-Hein
https://arxiv.org/abs/2506.06232

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study
While traditional computer vision models have historically struggled to generalize to endoscopic domains, the emergence of foundation models has shown promising cross-domain performance. In this work, we present the first large-scale study assessing the capabilities of Vision Language Models (VLMs) for endoscopic tasks with a specific focus on laparoscopic surgery. Using a diverse set of state-of-the-art models, multiple surgical datasets, and extensive human reference annotations, we address t…

New Insights into the T Tauri Binary Separation Distribution
Caleb Eastlund, Maxwell Moe, Kaitlin M. Kratter, Marina Kounkel
https://arxiv.org/abs/2506.07938

New Insights into the T Tauri Binary Separation Distribution
For three decades, adaptive optic surveys have revealed an excess of T Tauri binaries across a = 10-100 au in nearby star-forming regions compared to the field population of main-sequence (MS) stars. Such an excess requires that most stars are born in dense clusters and subjected to significant dynamical processing that disrupts such binaries across intermediate separations. However, we demonstrate that the apparent excess is due to an observational selection bias. Close binaries within a < 100…

Exploration of features in the black hole mass spectrum inspired by non-parametric analyses of gravitational wave observations
Stefano Rinaldi, Yajie Liang, Gabriele Demasi, Michela Mapelli, Walter Del Pozzo
https://arxiv.org/abs/2506.05929

Exploration of features in the black hole mass spectrum inspired by non-parametric analyses of gravitational wave observations
Current gravitational-wave data reveal structures in the mass function of binary compact objects. Properly modelling and deciphering such structures is the ultimate goal of gravitational-wave population analysis: in this context, non-parametric models are a powerful tool to infer the distribution of black holes from gravitational waves without committing to any specific functional form. Here, we aim to quantitatively corroborate the findings of non-parametric methods with parametrised models in…

Execution-Aware Program Reduction for WebAssembly via Record and Replay
Doehyun Baek, Daniel Lehmann, Ben L. Titzer, Sukyoung Ryu, Michael Pradel
https://arxiv.org/abs/2506.07834 …

Execution-Aware Program Reduction for WebAssembly via Record and Replay
WebAssembly (Wasm) programs may trigger bugs in their engine implementations. To aid debugging, program reduction techniques try to produce a smaller variant of the input program that still triggers the bug. However, existing execution-unaware program reduction techniques struggle with large and complex Wasm programs, because they rely on static information and apply syntactic transformations, while ignoring the valuable information offered by the input program's execution behavior. We presen…

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Angel Bautista, Josh Susskind, Shuangfei Zhai
https://arxiv.org/abs/2506.06276

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
We present STARFlow, a scalable generative model based on normalizing flows that achieves strong performance in high-resolution image synthesis. The core of STARFlow is Transformer Autoregressive Flow (TARFlow), which combines the expressive power of normalizing flows with the structured modeling capabilities of Autoregressive Transformers. We first establish the theoretical universality of TARFlow for modeling continuous distributions. Building on this foundation, we introduce several key arch…