Tootfinder

Voltage-sensitive distribution factors for contingency analysis and topology optimization
Maurizio Titz, Dirk Witthaut, Joost van Dijk, Benjamin Petrick, Nico Westerbeck
https://arxiv.org/abs/2509.19976

Voltage-sensitive distribution factors for contingency analysis and topology optimization
Topology optimization is a promising approach for mitigating congestion and managing changing grid conditions, but it is computationally challenging and requires approximations. Conventional distribution factors like PTDFs and LODFs, based on DC power flow, fail to capture voltage variations, reactive power, and losses - limiting their use in detailed optimization tasks such as busbar splitting. This paper introduces generalized distribution factors derived from a voltage-sensitive linearizatio…

Quantitative imaging of 478-keV prompt gamma rays from boron neutron capture reactions
Tetsuya Mizumoto, Shotaro Komura, Atsushi Takada, Yoshinori Sakurai, Toru Tanimori
https://arxiv.org/abs/2509.00435

Quantitative imaging of 478-keV prompt gamma rays from boron neutron capture reactions
The accurate imaging and quantitative measurement of 478-keV prompt gamma rays are critical for advancing boron neutron capture therapy (BNCT), a promising cancer treatment. Although numerical simulations have indicated that such measurements are feasible, their practical application has proven challenging. This study introduces a gamma-ray imaging detector designed specifically for precise BNCT measurements. Using boron-rich phantom samples, we successfully imaged 478-keV gamma rays and establ…

SeHDR: Single-Exposure HDR Novel View Synthesis via 3D Gaussian Bracketing
Yiyu Li, Haoyuan Wang, Ke Xu, Gerhard Petrus Hancke, Rynson W. H. Lau
https://arxiv.org/abs/2509.20400

SeHDR: Single-Exposure HDR Novel View Synthesis via 3D Gaussian Bracketing
This paper presents SeHDR, a novel high dynamic range 3D Gaussian Splatting (HDR-3DGS) approach for generating HDR novel views given multi-view LDR images. Unlike existing methods that typically require the multi-view LDR input images to be captured from different exposures, which are tedious to capture and more likely to suffer from errors (e.g., object motion blurs and calibration/alignment inaccuracies), our approach learns the HDR scene representation from multi-view LDR images of a single …

Crosslisted article(s) found for physics.med-ph. https://arxiv.org/list/physics.med-ph/new
[1/1]:
- Quantitative imaging of 478-keV prompt gamma rays from boron neutron capture reactions
Tetsuya Mizumoto, Shotaro Komura, Atsushi Takada, Yoshinori Sakurai, Toru Tanimori