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Quantum Software Security Challenges within Shared Quantum Computing Environments
Samuel Ovaskainen, Majid Haghparast, Tommi Mikkonen
https://arxiv.org/abs/2507.17712 https://…

Quantum Software Security Challenges within Shared Quantum Computing Environments
The number of qubits in quantum computers keeps growing, but most quantum programs remain relatively small because of the noisy nature of the underlying quantum hardware. This might lead quantum cloud providers to explore increased hardware utilization, and thus profitability through means such as multi-programming, which would allow the execution of multiple programs in parallel. The adoption of such technology would bring entirely new challenges to the field of quantum software security. This…

Markov Chain-based Model of Blockchain Radio Access Networks
Vasileios Kouvakis, Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Hongwu Liu, Theodoros A. Tsiftsis, Octavia A. Dobre
https://arxiv.org/abs/2508.14519

Markov Chain-based Model of Blockchain Radio Access Networks
Security has always been a priority, for researchers, service providers and network operators when it comes to radio access networks (RAN). One wireless access approach that has captured attention is blockchain enabled RAN (B-RAN) due to its secure nature. This research introduces a framework that integrates blockchain technology into RAN while also addressing the limitations of state-of-the-art models. The proposed framework utilizes queuing and Markov chain theory to model the aspects of B-RA…

Advanced X-rays techniques for research-oriented high-resolution imaging of articular cartilage: a scoping review
Simone Fantoni (Medical Technology Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy), Luca Brombal (Department of Physics, University of Trieste, Trieste, Italy, INFN, Division of Trieste, Trieste, Italy), Paolo Cardarelli (INFN, Division of Ferrara, Ferrara, Italy), Fabio Baruffaldi (Medical Technology Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, It…

Advanced X-rays techniques for research-oriented high-resolution imaging of articular cartilage: a scoping review
Articular cartilage is a musculoskeletal soft tissue renowned for its unique mechanical properties. Understanding both its hierarchical structure and the interplay between its constituents could shed light on the mechanical competence of the tissue. Therefore, rheologic approaches based on high-resolution non-destructive imaging techniques are desired. In this context, X-ray imaging could ideally accomplish this task. Nevertheless, the nature of articular cartilage translates into poor contrast…

Observation of Anomalous Hall Effect in Bulk Single Crystals of n-type Cr-doped Sb$_{2}$Te$_{3}$ Magnetic Topological Insulator
Ali Sarikhani (Material Research Center, Missouri University of Science and Technology, Rolla, MO), Mathew Pollard (Department of Physics, Missouri University of Science and Technology, Rolla, MO), Jacob Cook (Department of Physics and Astronomy, University of Missouri, Columbia, MO), Sheng Qiu (Department of Physics, Missouri University of Science and Technol…

Observation of Anomalous Hall Effect in Bulk Single Crystals of n-type Cr-doped Sb$_{2}$Te$_{3}$ Magnetic Topological Insulator
The exploration of topological Dirac surface states is significant in the realms of condensed matter physics and future technological innovations. Among the materials garnering attention is Sb$_{2}$Te$_{3}$, a compound that theoretically exhibits topological insulating properties. However, its inherent p-type nature prevents the direct experimental verification of its Dirac surface state due to the Fermi level alignment with the valence band. In this study, by doping Cr atoms into Sb$_{2}$Te$_{…

This https://arxiv.org/abs/2505.22073 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents
Due to its general-purpose nature, Generative AI is applied in an ever-growing set of domains and tasks, leading to an expanding set of risks of harm impacting people, communities, society, and the environment. These risks may arise due to failures during the design and development of the technology, as well as during its release, deployment, or downstream usages and appropriations of its outputs. In this paper, building on prior taxonomies of AI risks, harms, and failures, we construct a taxon…

Impact of white noise on spatial navigation of people without visual cues https://www.nature.com/articles/s41598-025-03067-8 "significant implications for assistive technologies aimed at supporting mobility in individuals without vision";

Impact of white noise on spatial navigation of people without visual cues - Scientific Reports
The current study examines how multisensory cues-specifically, passive proprioception combined with white noise-affect navigation ability in the absence of visual input. The main goal was to investigate whether adding white noise, as a non-structured auditory stimulus, could enhance spatial learning and navigation in blindfolded sighted participants. Using a novel motion-tracking technology, SensFloor $$^\circledR$$ , participants completed navigation tasks under two conditions: a unisensory co…

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…

Spectrum Sensing with Deep Clustering: Label-Free Radio Access Technology Recognition
Ljupcho Milosheski, Mihael Mohor\v{c}i\v{c}, Carolina Fortuna
https://arxiv.org/abs/2508.01709

Spectrum Sensing with Deep Clustering: Label-Free Radio Access Technology Recognition
The growth of the number of connected devices and network densification is driving an increasing demand for radio network resources, particularly Radio Frequency (RF) spectrum. Given the dynamic and complex nature of contemporary wireless environments, characterized by a wide variety of devices and multiple RATs, spectrum sensing is envisioned to become a building component of future 6G, including as a component within O-RAN or digital twins. However, the current SotA research for RAT classific…

The role of preprints in open science: Accelerating knowledge transfer from science to technology
Zhiqi Wang, Yue Chen, Chun Yang
https://arxiv.org/abs/2506.20225

The role of preprints in open science: Accelerating knowledge transfer from science to technology
Preprints have become increasingly essential in the landscape of open science, facilitating not only the exchange of knowledge within the scientific community but also bridging the gap between science and technology. However, the impact of preprints on technological innovation, given their unreviewed nature, remains unclear. This study fills this gap by conducting a comprehensive scientometric analysis of patent citations to bioRxiv preprints submitted between 2013 and 2021, measuring and acces…

Extrinsic nature of the polarization in hafnia ferroelectrics
Binayak Mukherjee (Luxembourg Institute of Science and Technology), Natalya S. Fedorova (Luxembourg Institute of Science and Technology), Jorge \'I\~niguez-Gonz\'alez (Luxembourg Institute of Science and Technology, University of Luxembourg)
https://arxiv.org/abs/2508.00…

Extrinsic nature of the polarization in hafnia ferroelectrics
Hafnia and related fluorites defy our understanding of ferroelectricity, even if we restrict ourselves to the intrinsic properties of ideal crystals. Here we focus on a critical puzzle, namely, the sign of the electric polarization. Using first-principles simulations, we show that a polar hafnia layer with a fixed atomic configuration can give rise to depolarizing fields of either positive or negative sign, depending on the environment. This implies that (the sign of) the polarization in hafnia…

GPUnion: Autonomous GPU Sharing on Campus
Yufang Li (The Hong Kong University of Science,Technology), Yuanbo Zhang (Sun Yat-sen University), Hanlong Liao (National University of Defense Technology), Guoming Tang (The Hong Kong University of Science,Technology), Deke Guo (Sun Yat-sen University)
https://arxiv.org/abs/2507.18928

GPUnion: Autonomous GPU Sharing on Campus
A pronounced imbalance in GPU resources exists on campus, where some laboratories own underutilized servers while others lack the compute needed for AI research. GPU sharing can alleviate this disparity, while existing platforms typically rely on centralized oversight and persistent allocation models, conflicting with the voluntary and autonomous nature of academic resource ownership. We present GPUnion, a campus-scale GPU sharing platform enabling voluntary participation while preserving full …

Comparative molecular dynamics simulations of charged solid-liquid interfaces with different water models
Mahdi Tavakol, Kislon Vo\"itchovsky
https://arxiv.org/abs/2508.02170

Comparative molecular dynamics simulations of charged solid-liquid interfaces with different water models
Aqueous solid-liquid interfaces (SLI) are ubiquitous in nature and technology, often hosting molecular-level processes with macroscopic consequences. Molecular dynamics (MD) simulations offer a tool of choice to investigate interfacial phenomena with atomistic precision, but there exists a large number of water models, each optimised for a different purpose. Here we compare the ability of common water models to accurately simulate the interface between a charged silica surface and an aqueous so…

SPC to 3D: Novel View Synthesis from Binary SPC via I2I translation
Sumit Sharma, Gopi Raju Matta, Kaushik Mitra
https://arxiv.org/abs/2506.06890 https://

SPC to 3D: Novel View Synthesis from Binary SPC via I2I translation
Single Photon Avalanche Diodes (SPADs) represent a cutting-edge imaging technology, capable of detecting individual photons with remarkable timing precision. Building on this sensitivity, Single Photon Cameras (SPCs) enable image capture at exceptionally high speeds under both low and high illumination. Enabling 3D reconstruction and radiance field recovery from such SPC data holds significant promise. However, the binary nature of SPC images leads to severe information loss, particularly in te…

A Short-Term Integrated Wind Speed Prediction System Based on Fuzzy Set Feature Extraction
Yijun Geng, Jianzhou Wang, Jinze Li, Zhiwu Li
https://arxiv.org/abs/2507.05761

A Short-Term Integrated Wind Speed Prediction System Based on Fuzzy Set Feature Extraction
Wind energy has significant potential owing to the continuous growth of wind power and advancements in technology. However, the evolution of wind speed is influenced by the complex interaction of multiple factors, making it highly variable. The nonlinear and nonstationary nature of wind speed evolution can have a considerable impact on the overall power system. To address this challenge, we propose an integrated multiframe wind speed prediction system based on fuzzy feature extraction. This sys…

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication
Mohammad Ghassemi, Sara Farrag Mobarak, Han Zhang, Ali Afana, Akram Bin Sediq, Melike Erol-Kantarci
https://arxiv.org/abs/2506.09855

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication
Reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for enhancing wireless communication by dynamically controlling signal propagation in the environment. However, their efficient deployment relies on accurate channel state information (CSI), which leads to high channel estimation overhead due to their passive nature and the large number of reflective elements. In this work, we solve this challenge by proposing a novel framework that leverages a pre-trained open-sou…