Tootfinder

Distinguishing Fact from Fiction: Student Traits, Attitudes, and AI Hallucination Detection in Business School Assessment
Canh Thien Dang, An Nguyen
https://arxiv.org/abs/2506.00050

Distinguishing Fact from Fiction: Student Traits, Attitudes, and AI Hallucination Detection in Business School Assessment
As artificial intelligence (AI) becomes integral to the society, the ability to critically evaluate AI-generated content is increasingly vital. On the context of management education, we examine how academic skills, cognitive traits, and AI scepticism influence students' ability to detect factually incorrect AI-generated responses (hallucinations) in a high-stakes assessment at a UK business school (n=211, Year 2 economics and management students). We find that only 20% successfully identified …

Shill Bidding Prevention in Decentralized Auctions Using Smart Contracts
M. A. Bouaicha, G. Destefanis, T. Montanaro, N. Lasla, L. Patrono
https://arxiv.org/abs/2506.00282

Shill Bidding Prevention in Decentralized Auctions Using Smart Contracts
In online auctions, fraudulent behaviors such as shill bidding pose significant risks. This paper presents a conceptual framework that applies dynamic, behavior-based penalties to deter auction fraud using blockchain smart contracts. Unlike traditional post-auction detection methods, this approach prevents manipulation in real-time by introducing an economic disincentive system where penalty severity scales with suspicious bidding patterns. The framework employs the proposed Bid Shill Score (BS…

Observations of non complex organic molecules in the gas phase of the interstellar medium
Charlotte Vastel, Francesco Fontani
https://arxiv.org/abs/2506.02641

Observations of non complex organic molecules in the gas phase of the interstellar medium
The field of astrochemistry has seen major advances triggered by the completion of new powerful radio telescopes, with gains in sensitivity of receivers and in bandwidth. To date, about 330 molecular species are detected, in interstellar clouds, circumstellar shells and even extragalactic sources. The first interstellar molecules were first discovered through their electronic transitions in the visual and near UV regions of the spectra in the 1930s. Then the discovery of (pure) rotational trans…

This https://arxiv.org/abs/2409.10631 has been replaced.
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Spatially Resolved Kinematics of SLACS Lens Galaxies. I: Data and Kinematic Classification
We obtain spatially resolved kinematics with the Keck Cosmic Web Imager (KCWI) integral-field spectrograph for a sample of 14 massive (11 < log$_{10}$ M$_*$/M$_{\odot}$ < 12) lensing early-type galaxies at z~0.15-0.35 from the Sloan Lens ACS (SLACS) Survey. We integrate kinematic maps within the effective radius and examine rotational and dispersion velocities, showing that 11/14 are slow rotators. The dataset is unprecedented for galaxy-scale strong lenses in terms of signal-to-noise ratio (S/…

Study of the Turbulent/Non-turbulent Interface of Zero-Pressure-Gradient Turbulent Boundary Layer Using the Uniform Momentum Zone Concept
Bihai Sun, Callum Atkinson, Julio Soria
https://arxiv.org/abs/2505.23589

Study of the Turbulent/Non-turbulent Interface of Zero-Pressure-Gradient Turbulent Boundary Layer Using the Uniform Momentum Zone Concept
This paper investigates the turbulent--non-turbulent interface (TNTI) in a zero-pressure-gradient turbulent boundary layer (ZPG-TBL) using a novel, threshold-free method based on the uniform momentum zone (UMZ) concept. Requiring only planar streamwise velocity data, the method is directly applicable to experimental PIV and ensures consistent TNTI detection across simulations and experiments. Its performance is demonstrated using DNS data at $Re_τ= 1,000 - 2,000$. The TNTI height scales with t…

Coincident Learning for Beam-based RF Station Fault Identification Using Phase Information at the SLAC Linac Coherent Light Source
Jia Liang, William Colocho, Franz-Josef Decker, Ryan Humble, Ben Morris, Finn H. O'Shea, David A. Steele, Zhe Zhang, Eric Darve, Daniel Ratner
https://arxiv.org/abs/2505.16052

Coincident Learning for Beam-based RF Station Fault Identification Using Phase Information at the SLAC Linac Coherent Light Source
Anomalies in radio-frequency (RF) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC's Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining RF amplitude and beam-position monitor data. Due to the simplicity of the RF amplitude data, classical methods ar…

In silico tool for identification of colorectal cancer from cell-free DNA biomarkers
Kartavya Mathur (Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi, School of Biotechnology, Gautam Buddha University, Uttar Pradesh), Shipra Jain (Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi), Nisha Bajiya (Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi), Nishant Ku…

In silico tool for identification of colorectal cancer from cell-free DNA biomarkers
Colorectal cancer remains a major global health concern, with early detection being pivotal for improving patient outcomes. In this study, we leveraged high throughput methylation profiling of cellfree DNA to identify and validate diagnostic biomarkers for CRC. The GSE124600 study data were downloaded from the Gene Expression Omnibus, as the discovery cohort, comprising 142 CRC and 132 normal cfDNA methylation profiles obtained via MCTA seq. After preprocessing and filtering, 97,863 CpG sites w…