Tootfinder

Adjusting Tissue Puncture Omnidirectionally In Situ with Pneumatic Rotatable Biopsy Mechanism and Hierarchical Airflow Management in Tortuous Luminal Pathways
Botao Lin, Tinghua Zhang, Sishen Yuan, Tiantian Wang, Jiaole Wang, Wu Yuan, Hongliang Ren
https://arxiv.org/abs/2506.03017

Adjusting Tissue Puncture Omnidirectionally In Situ with Pneumatic Rotatable Biopsy Mechanism and Hierarchical Airflow Management in Tortuous Luminal Pathways
In situ tissue biopsy with an endoluminal catheter is an efficient approach for disease diagnosis, featuring low invasiveness and few complications. However, the endoluminal catheter struggles to adjust the biopsy direction by distal endoscope bending or proximal twisting for tissue sampling within the tortuous luminal organs, due to friction-induced hysteresis and narrow spaces. Here, we propose a pneumatically-driven robotic catheter enabling the adjustment of the sampling direction without t…

Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Yang Zhou, Chrystie Wan Ning Quek, Jun Zhou, Yan Wang, Yang Bai, Yuhe Ke, Jie Yao, Laura Gutierrez, Zhen Ling Teo, Darren Shu Jeng Ting, Brian T. Soetikno, Christopher S. Nielsen, Tobias Elze, Zengxiang Li, Linh Le Dinh, Lionel Tim-Ee Cheng, Tran Nguyen Tuan Anh, Chee Leong Cheng, Tien Yin Wong, Nan Liu, Iain Beehuat Tan, Tony Kiat Hon Lim, Rick Siow Mong Goh, Yong Liu, Daniel Shu Wei Ting

Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulted in inconsistent clinical accuracy. Furthermore, training these models typically requires large, labour-intensive, well-labelled datasets. We developed MerMED-FM, a state-of-the-art multimodal, multi-specialty foundation model trained using self-supervised learning and a memory module. MerMED-FM was trained on 3.3 mi…

A Transformer-Based Neural Network for Optimal Deterministic-Allocation and Anonymous Joint Auction Design
Zhen Zhang, Luowen Liu, Wanzhi Zhang, Zitian Guo, Kun Huang, Qi Qi, Qiang Liu, Xingxing Wang
https://arxiv.org/abs/2506.02435

A Transformer-Based Neural Network for Optimal Deterministic-Allocation and Anonymous Joint Auction Design
With the advancement of machine learning, an increasing number of studies are employing automated mechanism design (AMD) methods for optimal auction design. However, all previous AMD architectures designed to generate optimal mechanisms that satisfy near dominant strategy incentive compatibility (DSIC) fail to achieve deterministic allocation, and some also lack anonymity, thereby impacting the efficiency and fairness of advertising allocation. This has resulted in a notable discrepancy between…

Probing the semiconductor-to-dirac semimetal transition in Na-Sb-Bi alloys with x-ray Compton scattering
Aki Pulkkinen, Veenavee Nipunika Kothalawala, Kosuke Suzuki, Bernardo Barbiellini, Johannes Nokelainen, Wei-Chi Chiu, Bahadur Singh, Hsin Lin, Alok K. Pandey, Naoaki Yabuuchi, Naruki Tsuji, Yoshiharu Sakurai, Hiroshi Sakurai, J\'an Min\'ar, Arun Bansil

Probing the semiconductor-to-dirac semimetal transition in Na-Sb-Bi alloys with x-ray Compton scattering
We discuss electron redistribution during the Semiconductor-to-Dirac Semimetal transition in Na-Sb-Bi alloys using x-ray Compton scattering experiments combined with first-principles electronic structure modeling. A robust signature of the semiconductor-to-Dirac semimetal transition is identified in the spherically averaged Compton profile. We demonstrate how the number of electrons involved in this transition can be estimated to provide a novel descriptor for quantifying the strength of spin-o…

it’s a lonely free lunch wednesday at the systems lab #alas

Tough Decisions Already Loom For New Raiders Regime Next Offseason https://raiderramble.com/2025/06/28/tough-decisions-already-loom-for-new-raiders-regime-next-offseason/

AAAAAAAAAAA I wanna cook but then I have way more stuff to wash compared to just ordering and I hate washing the dishes ;-;

Zasłyszane: "do przedszkola sprowadzili lamy, i teraz ta jedną lama chodzi, i pluje na dzieci."
#lama

Scout-Dose-TCM: Direct and Prospective Scout-Based Estimation of Personalized Organ Doses from Tube Current Modulated CT Exams
Maria Jose Medrano, Sen Wang, Liyan Sun, Abdullah-Al-Zubaer Imran, Jennie Cao, Grant Stevens, Justin Ruey Tse, Adam S. Wang
https://arxiv.org/abs/2506.24062

Scout-Dose-TCM: Direct and Prospective Scout-Based Estimation of Personalized Organ Doses from Tube Current Modulated CT Exams
This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level doses under tube current modulation (TCM) and compares its performance to two established methods. We analyzed contrast-enhanced chest-abdomen-pelvis CT scans from 130 adults (120 kVp, TCM). Reference doses for six organs (lungs, kidneys, liver, pancreas, bladder, spleen) were calculated using MC-GPU and TotalSegmentator. Based on these, we trained Scout-Dose-TCM, a deep learning model that predicts organ doses…