Lightning Network’s Tightrope Walk: Stability and Centralization
A new analysis reveals the Lightning Network maintains surprising resilience over time, even as it becomes increasingly fragmented and concentrated in its structure.
Science
Steering with Intelligence: Magnetic Catheters Guided by AI
![A reinforcement learning system leverages an LSTM-modeled magnetic catheter-where state is defined by tip position [latex]X_{t},Y_{t}[/latex] and goal [latex]X_{g},Y_{g}[/latex]-to train an agent, employing either a Deep Q-Network or TD3, to select angular increments [latex]\Delta\theta_{1},\,\Delta\theta_{3}[/latex]-with [latex]\Delta\theta_{2}=\Delta\theta_{1}[/latex] due to coupling-and optimize a reward function balancing goal proximity with control effort, effectively establishing closed-loop control of the catheter’s tip.](https://arxiv.org/html/2512.21063v1/Overview2.png)
Researchers are leveraging the power of artificial intelligence to achieve unprecedented precision in navigating magnetically steered catheters within the body.
Digital Distress Signals: Tracking Mental Health on Reddit During COVID-19
A new analysis of online forum data reveals shifting trends in mental wellbeing throughout the pandemic, offering a unique window into population-level emotional states.
Forecasting the Skies: A New Approach to Predicting Rainfall
Researchers have developed a novel deep learning model that significantly improves the accuracy and realism of short-term precipitation forecasts.
Can AI Decode the Signals of Mental Health?
A new benchmark framework assesses the ability of foundation models to detect neuropsychiatric disorders from speech and text, revealing both promise and significant challenges.
Seeing Beyond Blockages: A New View of Heart Vessel Health
Researchers are leveraging advanced image analysis to better understand and diagnose subtle problems in the smallest blood vessels of the heart.
Guarding AI Perception: A New Defense Against Activity Recognition Hacks
Researchers have developed an autonomous agent that actively shields AI systems interpreting sensor data from malicious prompt injection attacks.
Smart Networks for Industry 4.0: Scaling Intent-Based Control with Federated Learning
A new framework harnesses the power of distributed AI to verify network policies and optimize performance in complex Industrial IoT deployments.
Future-Proofing 6G: A New Approach to Network Security
As 6G networks evolve, a fundamental shift in security paradigms is needed to address emerging threats and the dynamic nature of future connectivity.
Graphs Get a Social Boost: Improving Link Prediction with Community Structure
![A community-aware link prediction framework first establishes global node representations by identifying central nodes within communities-determined through community detection and [latex]PageRank[/latex] centrality-and then augments the graph structure with prior probabilities to address incompleteness, ultimately constructing robust edge representations by integrating local neighborhood features, path information, and cross-community collaboration.](https://arxiv.org/html/2512.21166v1/doc/Figure_2.png)
A new approach leverages the inherent community organization within networks to create richer graph representations and more accurately predict missing links.