China's People's Armed Forces Maritime Militia deployed thousands of fishing vessels in coordinated formations that could disrupt global shipping lanes, analysts warn.

GUIs development to enhance developers' productivity.

Topological data analysis (TDA) delivers invaluable and complementary information on the intrinsic properties of data inaccessible to conventional methods.

China launches new military exercises around Taiwan following record $11.1 billion U.S. arms sale, with warships conducting live-fire drills that could escalate toward war.

Concerns over the potential over-pathologization of generative AI (GenAI) use and the lack of conceptual clarity surrounding GenAI addiction call for empirical tools and theoretical refinement. This study developed and validated the PUGenAIS-9 (Problematic Use of Generative Artificial Intelligence Scale-9 items) and examined whether PUGenAIS reflects addiction-like patterns under the Internet Gaming Disorder (IGD) framework. Using samples from China and the United States (N = 1,508), we conducted confirmatory factor analysis and identified a robust 31-item structure across nine IGD-based dimensions. We then derived the PUGenAIS-9 by selecting the highest-loading items from each dimension and validated its structure in an independent sample (N = 1,426). Measurement invariance tests confirmed its stability across nationality and gender. Person-centered (latent profile analysis) and variable-centered (network analysis) approaches revealed a 5-10% prevalence rate, a symptom network structure similar to IGD, and predictive factors related to psychological distress and functional impairment. These findings indicate that PUGenAI shares features of the emotionally vulnerable subtype of IGD rather than the competence-based type. These results support using PUGenAIS-9 to identify problematic GenAI use and show the need to rethink digital addiction with an ICD (infrastructures, content, and device) model. This keeps addiction research responsive to new media while avoiding over-pathologizing.

GUIs development to enhance developers' productivity.

Topological data analysis (TDA) delivers invaluable and complementary information on the intrinsic properties of data inaccessible to conventional methods.

--Artificial intelligence (AI) and machine learning (ML) models are rapidly permeating the 5G Radio Access Network (RAN), powering beam management, channel state information (CSI) feedback, positioning, and mobility prediction. However, without a standardized life-cycle management (LCM) framework, challenges, such as model drift, vendor lock-in, and limited transparency, hinder large-scale adoption. Beginning with the Network Data Analytics Function (NWDAF) in Rel-16, subsequent releases introduced standardized interfaces for model transfer, execution, performance monitoring, and closed-loop control, culminating in Rel-20's two-sided CSI-compression Work Item and vendor-agnostic LCM profile. This article reviews the resulting five-block LCM architecture, KPI-driven monitoring mechanisms, and inter-vendor collaboration schemes, while identifying open challenges in resource-efficient monitoring, environment drift detection, intelligent decision-making, and flexible model training. These developments lay the foundation for AI-native transceivers as a key enabler for 6G. C.-H. Huang is with the Department of Electrical Engineering, National Taiwan University National Taiwan University, Taipei 10617, Taiwan, Email: chuhsianh@ntu.edu.tw. C.-K. Wen is with the Institute of Communications Engineering, National Sun Y at-sen University, Kaohsiung 80424, Taiwan, Email: chaokai.wen@mail.nsysu.edu.tw. Li is with the Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ London, U.K., Email: geoffrey.li@imperial.ac.uk. This work has been submitted to the IEEE for possible publication. RTIFICIAL intelligence (AI) and machine learning (ML) have demonstrated significant potential in enhancing radio access network (RAN) performance, particularly for nonlinear and analytically complex tasks, such as beam management [1], channel state information (CSI) feedback [2], [3], positioning [4], and mobility prediction [5].