Tootfinder

Designing and Evaluating a Conversational Agent for Early Detection of Alzheimer's Disease and Related Dementias
Andrew G. Breithaupt, Nayoung Choi, James D. Finch, Jeanne M. Powell, Arin L. Nelson, Oz A. Alon, Howard J. Rosen, Jinho D. Choi
https://arxiv.org/abs/2509.11478

Designing and Evaluating a Conversational Agent for Early Detection of Alzheimer's Disease and Related Dementias
Early detection of Alzheimer's disease and related dementias (ADRD) is critical for timely intervention, yet most diagnoses are delayed until advanced stages. While comprehensive patient narratives are essential for accurate diagnosis, prior work has largely focused on screening studies that classify cognitive status from interactions rather than supporting the diagnostic process. We designed voice-interactive conversational agents, leveraging large language models (LLMs), to elicit narratives …

Great thread about #Git self-hosting options:
https://jawns.club/@skyfaller/114989129643625908

Dieses Projekt von Phew, Erika Kobayashi und Dieter Moebius, veranlasst durch Fukushima 2011, war mir bisher entgangen. Das Album, das 2012 unter einem anderen Titel erschienen war, wurde nun vom Label Bureau B als "Radium Girls" wiederaufgelegt,, aus chronologisch naheliegendem Grund. #sound

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…

Scaling High-Performance Nanoribbon Transistors with Monolayer Transition Metal Dichalcogenides
Tara Pe\~na, Anton E. O. Persson, Andrey Krayev, \'Ashildur Fri{\dh}riksd\'ottir, Kathryn Neilson, Zhepeng Zhang, Anh Tuan Hoang, Jerry A. Yang, Lauren Hoang, Andrew J. Mannix, Paul C. McIntyre, Eric Pop
https://arxiv.org/abs/2509.09964

Scaling High-Performance Nanoribbon Transistors with Monolayer Transition Metal Dichalcogenides
Nanoscale transistors require aggressive reduction of all channel dimensions: length, width, and thickness. While monolayer two-dimensional semiconductors (2DS) offer ultimate thickness scaling, good performance has largely been achieved only in micrometer-wide channels. Here, we demonstrate both $\it{n}$- and $\it{p}$-type nanoribbon transistors based on monolayer 2DS, fabricated using a multi-patterning process, reaching channel widths down to 25 nm and lengths down to 50 nm. 'Anchored' conta…

Constraint on ultralight Nelson-Barr dark matter from time-dependent nuclear decay
Chang-Jie Dai, Tong Li
https://arxiv.org/abs/2506.22081 https://

Constraint on ultralight Nelson-Barr dark matter from time-dependent nuclear decay
Many experiments have notably reported anomalies in radioactive decay rates with periodic variations and challenged the traditional belief of time-independent decays. This periodicity could potentially be explained by the presence of a periodic dark matter (DM) candidate. In this work, we investigate the impact of time-dependent nuclear decay rates on the ultralight scalar DM in Nelson-Barr solution to the strong CP problem. The light scalar DM field in this framework induces periodic modulatio…

First coordinated observations between Solar Orbiter and the Daniel K. Inouye Solar Telescope
Krzysztof Barczynski, Miho Janvier, Chris J. Nelson, T. Schad, A. Tritschler, Louise Harra, Daniel M\"uller, Susanna Parenti, Gherardo Valori, Gianna Cauzzi, Yingjie Zhu
https://arxiv.org/abs/2507.19198…

First coordinated observations between Solar Orbiter and the Daniel K. Inouye Solar Telescope
Solar Orbiter and the Daniel K. Inouye Solar Telescope (DKIST) are two of the newest facilities available to the solar physics community. The first coordinated observations of the Sun by these two facilities occurred over the course of one week in October 2022. The returned data are open-access and will provide a valuable resource to researchers in the field. We provide an overview of the datasets collected by Solar Orbiter and DKIST through this coordination and discuss their scientific pote…

Optical Emission-Line Properties of eROSITA-selected SDSS-V Galaxies
Nadiia G. Pulatova, Evgenii Rubtsov, Igor V. Chilingarian, Hans-Walter Rix, Mariia Demianenko, Kirill A. Grishin, Ivan Yu. Katkov, Donald P. Schneider, Catarina Aydar, Johannes Buchner, Mara Salvato, Andrea Merloni, Anton M. Koekemoer, Roberto J. Assef, Claudio Ricci, Dominika Wylezalek, Damir Gasymov, William Nielsen Brandt, Castalia Alenka Negrete Pe\~naloza, Sean Morrison, Scott F. Anderson, Franz E. Bauer, Hector …

Optical Emission-Line Properties of eROSITA-selected SDSS-V Galaxies
We present and discuss optical emission line properties obtained from the analysis of Sloan Digital Sky Survey (SDSS) spectra for an X-ray selected sample of 3684 galaxies (0.002 < z < 0.55), drawn from the eRASS1 catalog. We modeled SDSS-V DR19 spectra using the NBursts full spectrum fitting technique with E-MILES simple stellar populations (SSP) models and emission line templates to decompose broad and narrow emission line components for correlation with X-ray properties. We place the galaxie…

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning
Julia Machnio, Sebastian N{\o}rgaard Llambias, Mads Nielsen, Mostafa Mehdipour Ghazi
https://arxiv.org/abs/2506.22041

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning
White matter hyperintensities (WMH) are radiological markers of small vessel disease and neurodegeneration, whose accurate segmentation and spatial localization are crucial for diagnosis and monitoring. While multimodal MRI offers complementary contrasts for detecting and contextualizing WM lesions, existing approaches often lack flexibility in handling missing modalities and fail to integrate anatomical localization efficiently. We propose a deep learning framework for WM lesion segmentation a…

JWST ALMA reveal the build up of stellar mass in the cores of dusty star-forming galaxies at Cosmic Noon
Sarah Bodansky, Katherine E. Whitaker, Ayesha Abdullah, Jamie Lin, Pascal A. Oesch, Alexandra Pope, Mengyuan Xiao, Alba Covelo-Paz, Sam Cutler, Carlos Garcia Diaz, Minju M. Lee, Sinclaire M. Manning, Romain A. Meyer, Desika Narayanan, Erica Nelson, Irene Shivaei, Pieter van Dokkum
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