Tootfinder

Improving Surgical Risk Prediction Through Integrating Automated Body Composition Analysis: a Retrospective Trial on Colectomy Surgery
Hanxue Gu, Yaqian Chen, isoo Lee, Diego Schaps, Regina Woody, Roy Colglazier, Maciej A. Mazurowski, Christopher Mantyh
https://arxiv.org/abs/2506.11996

Improving Surgical Risk Prediction Through Integrating Automated Body Composition Analysis: a Retrospective Trial on Colectomy Surgery
Objective: To evaluate whether preoperative body composition metrics automatically extracted from CT scans can predict postoperative outcomes after colectomy, either alone or combined with clinical variables or existing risk predictors. Main outcomes and measures: The primary outcome was the predictive performance for 1-year all-cause mortality following colectomy. A Cox proportional hazards model with 1-year follow-up was used, and performance was evaluated using the concordance index (C-index…

Switzerland currently has hazard warnings for
- heavy rain
- flash floods
- strong wind
- droughts
- forest fires
and *drumroll*
- avalanches
The only thing missing is an earthquake.
But it would probably feel to much like Iceland then 😄
#climatechange #meteoswiss

Lattice Mismatch Driven In Plane Strain Engineering for Enhanced Upper Critical Fields in Mo2N Superconducting Thin Films
Aditya Singh, Divya Rawat, Victor Hjort, Abhisek Mishra, Arnaud le Febvrier, Subhankar Bedanta, Per Eklund, Ajay Soni
https://arxiv.org/abs/2506.04750

Lattice Mismatch Driven In Plane Strain Engineering for Enhanced Upper Critical Fields in Mo2N Superconducting Thin Films
Transition metal nitrides are a fascinating class of hard coating material that provide an excellent platform for investigating superconductivity and fundamental electron phonon interactions. In this work the structural morphological and superconducting properties have been studied for Mo2N thin films deposited via direct current magnetron sputtering on cplane Al2O3 and MgO substrates to elucidate the effect of internal strain on superconducting properties. High resolution X Ray diffraction and…

Shield AI has emerged as a lead contender in the increasingly crowded race against competitors like Anduril and AeroVironment
to outfit the U.S. military with killer drones.
The $5 billion-valued startup, founded in 2015 by brothers Ryan and Brandon Tseng,
sells a suite of hardware and products, including autonomous piloting software that has been used to fly fighter jets.
In March, it raised $240 million in a funding round led by Korean conglomerate Hanwha and Amer…

How A Grisly Injury Threw $5 Billion Drone Startup Shield AI Off Course
Shield AI executives overlooked its V-BAT drone’s safety hazards. With sales falling short and the CEO stepping down, the company is trying to win back military customers.

HighRateMOS: Sampling-Rate Aware Modeling for Speech Quality Assessment
Wenze Ren, Yi-Cheng Lin, Wen-Chin Huang, Ryandhimas E. Zezario, Szu-Wei Fu, Sung-Feng Huang, Erica Cooper, Haibin Wu, Hung-Yu Wei, Hsin-Min Wang, Hung-yi Lee, Yu Tsao
https://arxiv.org/abs/2506.21951

HighRateMOS: Sampling-Rate Aware Modeling for Speech Quality Assessment
Modern speech quality prediction models are trained on audio data resampled to a specific sampling rate. When faced with higher-rate audio at test time, these models can produce biased scores. We introduce HighRateMOS, the first non-intrusive mean opinion score (MOS) model that explicitly considers sampling rate. HighRateMOS ensembles three model variants that exploit the following information: (i) a learnable embedding of speech sampling rate, (ii) Wav2vec 2.0 self-supervised embeddings, (iii)…