Tootfinder

Nitrogen-vacancy centre formation via local femto-second laser annealing of diamond
Davin Yue Ming Peng, Alexander J Healey, Rebecca Griffin, Benjamin Cumming, Hiroshi Abe, Takeshi Ohshima, Alastair Stacey, Brant C Gibson, Brett C Johnson, Philipp Reineck
https://arxiv.org/abs/2507.18027

Nitrogen-vacancy centre formation via local femto-second laser annealing of diamond
Emerging quantum technologies based on the nitrogen-vacancy (NV) centre in diamond require carefully engineered material with controlled defect density, optimised NV formation processes, and minimal crystal strain. The choice of NV generation technique plays a crucial role in determining the quality and performance of these centres. In this work, we investigate NV centre formation in nitrogen-doped diamond using femtosecond (fs) laser processing. We systematically examine the effect of laser pu…

"Nuclear waste could be a source of fuel in future reactors"
#NuclearPower #Energy
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Nuclear waste could be a source of fuel in future reactors
From electric cars to artificial intelligence (AI) data centers, the technologies people use every day require a growing need for electricity. In theory, nuclear fusion—a process that fuses atoms together, releasing heat to turn generators—could provide vast energy supplies with minimal emissions. But nuclear fusion is an expensive prospect because one of its main fuels is a rare version of hydrogen called tritium.

Using Artificial Intuition in Distinct, Minimalist Classification of Scientific Abstracts for Management of Technology Portfolios
Prateek Ranka, Fred Morstatter, Andrea Belz, Alexandra Graddy-Reed
https://arxiv.org/abs/2508.13182

Using Artificial Intuition in Distinct, Minimalist Classification of Scientific Abstracts for Management of Technology Portfolios
Classification of scientific abstracts is useful for strategic activities but challenging to automate because the sparse text provides few contextual clues. Metadata associated with the scientific publication can be used to improve performance but still often requires a semi-supervised setting. Moreover, such schemes may generate labels that lack distinction -- namely, they overlap and thus do not uniquely define the abstract. In contrast, experts label and sort these texts with ease. Here we d…

Hierarchical Maximum Likelihood Estimation for Time-Resolved NMR Data
Lennart H. Bosch, Pernille R. Jensen, Nico Striegler, Thomas Unden, Jochen Scharpf, Usman Qureshi, Philipp Neumann, Martin Gierse, John W. Blanchard, Stephan Knecht, Jochen Scheuer, Ilai Schwart, Martin B. Plenio
https://arxiv.org/abs/2508.14902

Hierarchical Maximum Likelihood Estimation for Time-Resolved NMR Data
Metabolic monitoring and reaction rate estimation using hyperpolarized NMR technology requires accurate quantitative analysis of multidimensional data scenarios. Currently, this analysis is often performed in a two-stage procedure, which is prone to errors in uncertainty propagation and estimation. We propose an approach derived from a Bayesian hierarchical model that intrinsically propagates uncertainties and operates on the full data to maximize the precision at minimal uncertainty. In an ana…

An Adversarial Quantum Key Distribution Project
Brian R. La Cour, Noah A. Davis
https://arxiv.org/abs/2507.13389 https://arxiv.org/pdf/2507.13389

An Adversarial Quantum Key Distribution Project
Quantum key distribution (QKD) is a popular introduction to quantum technologies used in education and public outreach, as very little background in quantum theory is needed and the practical applications are easily understood. There is considerably less exposure to the many real-world considerations of practical QKD, as access to the necessary hardware is quite limited. Here we describe a simple, simulation-based QKD project that can be implemented with only a minimal background in quantum con…

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Timothy B Mahoney, JingYang Liu, Huakun Xin, David B Grayden, Sam E John
https://arxiv.org/abs/2506.03452

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Individuals with severe physical disabilities often experience diminished quality of life stemming from limited ability to engage with their surroundings. Brain-Computer Interface (BCI) technology aims to bridge this gap by enabling direct technology interaction. However, current BCI systems require invasive procedures, such as craniotomy or implantation of electrodes through blood vessels, posing significant risks to patients. Sub-scalp electroencephalography (EEG) offers a lower risk alternat…

AI Magnetic Levitation (Maglev) Conveyor for Automated Assembly Production
Ray Wai Man Kong
https://arxiv.org/abs/2506.08039 https://…

AI Magnetic Levitation (Maglev) Conveyor for Automated Assembly Production
Efficiency, speed, and precision are essential in modern manufacturing. AI Maglev Conveyor system, combining magnetic levitation (maglev) technology with artificial intelligence (AI), revolutionizes automated production processes. This system reduces maintenance costs and downtime by eliminating friction, enhancing operational efficiency. It transports goods swiftly with minimal energy consumption, optimizing resource use and supporting sustainability. AI integration enables real-time monitorin…

$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models
Quanming Liu, Xupeng Bu, Zhichao Yan, Ru Li
https://arxiv.org/abs/2506.21211

$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models
Automatic Program Repair (APR) is a core technology in software development and maintenance, with aims to enable automated defect repair with minimal human intervention. In recent years, the substantial advancements in Large Language Models (LLMs) and the Chain-of-Thought (CoT) techniques have significantly enhanced the reasoning capabilities of these models. However, due to the complex logic and multi-step reasoning ability needed, the application of CoT techniques in the APR domain remains in…

Mathematical model of blood coagulation during endovenous laser therapy
Anna A. Andreeva (Moscow Institute of Physics and Technology), Konstantin A. Klochkov (Moscow Institute of Physics and Technology), Alexey I. Lobanov (Moscow Institute of Physics and Technology)
https://arxiv.org/abs/2507.20401…

Mathematical model of blood coagulation during endovenous laser therapy
Endovenous laser therapy (ELT) as a minimally invasive procedure for ablation of large superficial veins, nevertheless, can cause complications of thrombotic nature. In this regard, the study of the main patterns of thrombus formation during ELT and modelling of endovenous heat-induced thrombosis (EHIT) is relevant. Based on the assumption of diffusion limiting of biochemical processes occurring during the coagulation of blood, by recalculating the reaction rates according to the Stokes-Einstei…

Deep Learning Based Antenna Selection Technique for RIS-Empowered RQSM System
Burak Ahmet Ozden, Fatih Cogen, Erdogan Aydin
https://arxiv.org/abs/2507.05071

Deep Learning Based Antenna Selection Technique for RIS-Empowered RQSM System
Reconfigurable intelligent surface (RIS) technology has attracted considerable interest due to its ability to control wireless propagation with minimal power usage. Receive quadrature spatial modulation (RQSM) scheme transmits data bits in both in-phase ($I$) and quadrature ($Q$) channels, doubling the number of active receive antenna indices and improving spectral efficiency compared to the traditional receive spatial modulation (RSM) technique. Also, capacity-optimized antenna selection (COAS…