diningIn recommender systems, online A/B testing is a crucial method for evaluating the performance of different models. However, conducting online A/B testing often presents significant challenges, including substantial economic costs, user experience degradation, and considerab…
Abstract We demonstrate that standard wafer fabrication can produce free-standing, mechanically stable, doubly-curved 3D structures with prescribed Gaussian curvature — a capability not previously achieved through semiconductor manufacturing. The stability of the deployed structu…
Metabolic dysfunction-associated steatotic liver disease (MASLD) has become one of the most prevalent chronic liver diseases worldwide. Its disease spectrum can progress from simple hepatic steatosis to metabolic dysfunction-associated steatohepatitis (MASH), liver fibrosis, cirr…
Carotid vulnerable plaques (CVPs) represent a major cause of ischemic stroke, yet current diagnostic methods lack sufficient precision for early detection. Spectral computed tomography (CT) enables detailed plaque characterization, but its clinical utility depends on advanced ana…
Machine learning has become an emerging paradigm for microrobotics, enabling autonomous micro-/nanorobot navigation in complex and highly disturbed environments without requirements of precise models. However, the state-of-the-art learning-based methods adopt “black-box” neural n…
Background and aims Ulcerative colitis (UC) is increasing worldwide, and dietary, lifestyle, and environmental exposures may contribute to disease susceptibility. This systematic review and meta-analysis evaluated the associations between these exposures and the risk of incident…
Abstract Intelligent vehicle path tracking is challenged by uncertain disturbances, such as modeling inaccuracies and external environmental influences, which will significantly compromise both the path tracking accuracy and stability. To address this, this paper proposes a fixed…
Photoplethysmography (PPG) is a non-invasive optical sensing modality that captures peripheral blood-volume dynamics related to cardiac activity and vascular function, making it useful for frequent cardiovascular monitoring with wearable devices. However, existing public PPG data…
Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing methods mainly follow two paradigms: reinforcement learning (RL) and on-policy distillation (OPD). However, RL relies on coarse-grained outcome supervision, resultin…
Mobile GUI agents increasingly face long-horizon tasks that require reading, updating, and reusing task-relevant data across pages and applications. Existing methods treat memory largely as passive storage, where past observations are accumulated and retrieved when needed. Yet re…
MLLM-based GUI grounding methods commonly formulate target localization as autoregressive coordinate generation, enabling models to leverage the strong instruction-following and semantic understanding capabilities of MLLMs. However, this formulation requires the model to retain r…
The use of electrostatically shielded loops for the near-field measurement of Shielding Effectiveness (SE) of planar conducting materials at frequencies above those covered by current standards is examined by simulation and measurement.The transverse wave impedances of the shield…