Tootfinder

Stellar Velocity Dispersion versus Age: Consistency across Observations and Simulations, with the Milky Way as an Outlier
Fiona McCluskey, Andrew Wetzel, Sarah Loebman, Jorge Moreno
https://arxiv.org/abs/2506.11840

Stellar Velocity Dispersion versus Age: Consistency across Observations and Simulations, with the Milky Way as an Outlier
Within disk galaxies, the velocity dispersion, $σ$, of stars increases with age, $τ$, as measured in the Milky Way (MW) and nearby galaxies. This relation provides a key window into galactic formation history, tracing both the kinematics of stars at birth and the dynamical heating of stars after birth. We compile and compare observational measurements of the MW, M31, M33, and 16 galaxies from the PHANGS survey. The MW exhibits significantly colder stellar kinematics, with 2-3 times lower $σ(…

Zo, dat is een lekker woke musical. Over rechtvaardigheid en zo, moet niet gekker worden.
Maar Trump houdt wel van een insurrection dus wie weet … misschien dat hij zich kan identificeren met Javert? Zijn we na afloop van deze musical van hem af.
Trump aanwezig bij première van musical Les Misérables

Trump aanwezig bij première van musical Les Misérables
Trump is woensdagavond aanwezig bij de première van de musical Les Misérables. Volgens persbureau Reuters zal de president worden vergezeld door first lady Melania Trump en vicepresident JD Vance.

Identifying Clean and Contaminated Atomic-Sized Gold Contacts under Ambient Conditions Using a Clustering Algorithm
Guillem Pellicer, Carlos Sabater
https://arxiv.org/abs/2506.09608

Identifying Clean and Contaminated Atomic-Sized Gold Contacts under Ambient Conditions Using a Clustering Algorithm
Molecular electronics studies have advanced from early, simple single-molecule experiments at cryogenic temperatures to complex and multifunctional molecules under ambient conditions. However, room-temperature environments increase the risk of contamination, making it essential to identify and quantify clean and contaminated rupture traces (i.e., conductance versus relative electrode displacement) within large datasets. Given the high throughput of measurements, manual analysis becomes unfeasib…

One #infosec example of the very many NSF funding awards being revoked:
"Hudson County Community College (HCCC) was awarded a $599,811 National Science Foundation (NSF) grant for its program, “Nurturing Resilience: Empowering the Next Generation of Cybersecurity Professionals with a Focus on Women.” The program goals are to recruit and retain more women in the HCCC Cybersecurity Prog…

Hudson County Community College Receives $600,000 National Science Foundation Grant to Expand Its Nationally Acclaimed Cybersecurity Program
The explosive demand for Cybersecurity is outpacing the supply of computer science professionals who assess threats and prevent attacks. Educational institutions, healthcare organizations, government, businesses, and individuals are increasingly vulnerable to evolving hazards including phishing, spoofing, malware, ransomware, and viruses.

Analysis of LLM Bias (Chinese Propaganda & Anti-US Sentiment) in DeepSeek-R1 vs. ChatGPT o3-mini-high
PeiHsuan Huang, ZihWei Lin, Simon Imbot, WenCheng Fu, Ethan Tu
https://arxiv.org/abs/2506.01814

Analysis of LLM Bias (Chinese Propaganda & Anti-US Sentiment) in DeepSeek-R1 vs. ChatGPT o3-mini-high
Large language models (LLMs) increasingly shape public understanding and civic decisions, yet their ideological neutrality is a growing concern. While existing research has explored various forms of LLM bias, a direct, cross-lingual comparison of models with differing geopolitical alignments-specifically a PRC-system model versus a non-PRC counterpart-has been lacking. This study addresses this gap by systematically evaluating DeepSeek-R1 (PRC-aligned) against ChatGPT o3-mini-high (non-PRC) for…

The Impact of Software Testing with Quantum Optimization Meets Machine Learning
Gopichand Bandarupalli
https://arxiv.org/abs/2506.02090 https://

The Impact of Software Testing with Quantum Optimization Meets Machine Learning
Modern software systems complexity challenges efficient testing, as traditional machine learning (ML) struggles with large test suites. This research presents a hybrid framework integrating Quantum Annealing with ML to optimize test case prioritization in CI/CD pipelines. Leveraging quantum optimization, it achieves a 25 percent increase in defect detection efficiency and a 30 percent reduction in test execution time versus classical ML, validated on the Defects4J dataset. A simulated CI/CD env…

This https://arxiv.org/abs/2412.09840 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

LAVA: Lifetime-Aware VM Allocation with Learned Distributions and Adaptation to Mispredictions
Scheduling virtual machines (VMs) on hosts in cloud data centers dictates efficiency and is an NP-hard problem with incomplete information. Prior work improved VM scheduling with predicted VM lifetimes. Our work further improves lifetime-aware scheduling using repredictions with lifetime distributions versus one-shot prediction. Our approach repredicts and adjusts VM and host lifetimes when incorrect predictions emerge. We also present novel approaches for defragmentation and regular system mai…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
Mohammad Saleh Torkestani, Taha Mansouri
https://arxiv.org/abs/2506.02046 https:…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
This paper presents a theoretical framework for addressing the challenges posed by generative artificial intelligence (AI) in higher education assessment through a machine-versus-machine approach. Large language models like GPT-4, Claude, and Llama increasingly demonstrate the ability to produce sophisticated academic content, traditional assessment methods face an existential threat, with surveys indicating 74-92% of students experimenting with these tools for academic purposes. Current respon…