Tootfinder

messal_shale: Messel Shale food web (2014)
A network of feeling links among taxa based on the 48 million years old uppermost early Eocene Messel Shale. Edge property 'certainty' denotes the certainty of the edge. Metadata include evidence, habitat, and trophic roles. The edge direction goes from consumer to resource.
This network has 700 nodes and 6444 edges.
Tags: Biological, Food Web, Uncertain, Weighted, Metadata

Neural-MMGS: Multi-modal Neural Gaussian Splats for Large-Scale Scene Reconstruction
Sitian Shen, Georgi Pramatarov, Yifu Tao, Daniele De Martini
https://arxiv.org/abs/2509.17762

Neural-MMGS: Multi-modal Neural Gaussian Splats for Large-Scale Scene Reconstruction
This paper proposes Neural-MMGS, a novel neural 3DGS framework for multimodal large-scale scene reconstruction that fuses multiple sensing modalities in a per-gaussian compact, learnable embedding. While recent works focusing on large-scale scene reconstruction have incorporated LiDAR data to provide more accurate geometric constraints, we argue that LiDAR's rich physical properties remain underexplored. Similarly, semantic information has been used for object retrieval, but could provide valua…

This is the proper way to sell stuff online.

Taboola and Paramount Skydance launch a CTV product called Performance Multiplier, aiming to extend the reach of Paramount's small and medium-sized ad partners (Sara Fischer/Axios)
https://www.axios.com/2025/10/22/taboola-launches-ctv-product-with-paramount…

Taboola launches CTV product with Paramount
The tool leverages Taboola's Realize AI tech, which allows publishers to sell performance ads across the open web.

Optimization techniques for SQL ML queries: A performance analysis of real-time feature computation in OpenMLDB
Mashkhal A. Sidiq, Aras A. Salih, Samrand M. Hassan
https://arxiv.org/abs/2509.15529

Optimization techniques for SQL+ML queries: A performance analysis of real-time feature computation in OpenMLDB
In this study, we optimize SQL+ML queries on top of OpenMLDB, an open-source database that seamlessly integrates offline and online feature computations. The work used feature-rich synthetic dataset experiments in Docker, which acted like production environments that processed 100 to 500 records per batch and 6 to 12 requests per batch in parallel. Efforts have been concentrated in the areas of better query plans, cached execution plans, parallel processing, and resource management. The experim…

Extended k-u Fading Model in mmWave Communication: Statistical Properties and Performance Evaluations
Jiahuan Wu, Xinchun Yu, Xiao-Ping Zhang
https://arxiv.org/abs/2509.15681 ht…

Extended k-u Fading Model in mmWave Communication: Statistical Properties and Performance Evaluations
This study proposes a small-scale fading model, named the extended k-u model, which incorporates the imbalance of multipath clusters by adding a new parameter based on the original k-u model. The extended k-u model outperforms the k-u model in characterizing small-scale fading in the millimeter-wave (mmWave) band and has more accurate modeling capability than the extended n-u model in scenarios with line-of-sight (LoS) paths. And it is mathematically more tractable than the a-k-n-u model. Exper…

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Chao Yu, Yuanqing Wang, Zhen Guo, Hao Lin, Si Xu, Hongzhi Zang, Quanlu Zhang, Yongji Wu, Chunyang Zhu, Junhao Hu, Zixiao Huang, Mingjie Wei, Yuqing Xie, Ke Yang, Bo Dai, Zhexuan Xu, Xiangyuan Wang, Xu Fu, Zhihao Liu, Kang Chen, Weilin Liu, Gang Liu, Boxun Li, Jianlei Yang, Zhi Yang, Guohao Dai, Yu Wang

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Reinforcement learning (RL) has demonstrated immense potential in advancing artificial general intelligence, agentic intelligence, and embodied intelligence. However, the inherent heterogeneity and dynamicity of RL workflows often lead to low hardware utilization and slow training on existing systems. In this paper, we present RLinf, a high-performance RL training system based on our key observation that the major roadblock to efficient RL training lies in system flexibility. To maximize flexib…

WarpSpeed: A High-Performance Library for Concurrent GPU Hash Tables
Hunter McCoy, Prashant Pandey
https://arxiv.org/abs/2509.16407 https://arxiv.org/pdf/2…

WarpSpeed: A High-Performance Library for Concurrent GPU Hash Tables
GPU hash tables are increasingly used to accelerate data processing, but their limited functionality restricts adoption in large-scale data processing applications. Current limitations include incomplete concurrency support and missing compound operations such as upserts. This paper presents WarpSpeed, a library of high-performance concurrent GPU hash tables with a unified benchmarking framework for performance analysis. WarpSpeed implements eight state-of-the-art Nvidia GPU hash table design…

Does anyone know of a hosting company that sell at a fixed price (no first year sale)?
Preferably in Europe.
#hosting #selfhosting

Ion-scale Turbulence and Energy Cascade Rate in the Solar Corona and Inner Heliosphere
Eduard P. Kontar, A. Gordon Emslie, Daniel L. Clarkson, Alexander Pitna
https://arxiv.org/abs/2509.17861

Ion-scale Turbulence and Energy Cascade Rate in the Solar Corona and Inner Heliosphere
Plasma turbulence cascading from MHD to kinetic scales in the heliospheric plasma is believed to play a key role in coronal heating and fast solar wind acceleration, but the properties of the turbulence remain poorly constrained by observations. Here we compare the ion-scale density fluctuation levels inferred from the properties of solar radio bursts with the magnetic field fluctuation levels obtained through in-situ measurements in the inner heliosphere. We find that the observed magnetic and…