GenZ-ICP introduces an innovative iterative Closest Point (ICP) method that enhances LiDAR-based pose estimation by adaptively integrating point-to-plane and point-to-point error metrics, ensuring robust performance across diverse and degenerative environments. Key Highlights Adaptive Error Metric Integration – Combines point-to-plane and point-to-point error metrics, leveraging their complementary strengths for improved pose estimation accuracy. Planarity-Based Correspondence Classification… →
CONCLUSIONS: While distal TRA did not reduce the risk of RAO, procedural AC proved effective in all patients undergoing transradial CAG including those on pre-existing oral AC. (Strategies to Maintain Radial Artery Patency Following Diagnostic Coronary Angiography [RAPID] trial; ClinicalTrials.gov: NCT04301921 [RAPID-1] and NCT04362020 [RAPID-2]). →

CONCLUSION: RFA for the therapy of pulmonary GGN is safe and effective, without surgical scar, and is less traumatic to the body, which has a good application prospect. →

CONCLUSIONS: Lip-BPVC initially increased inflammatory markers postoperatively, but levels were comparable to BPVC by 72 hours. It provided superior pain control and reduced opioid use compared to standard BPVC in CABG patients, with similar safety and recovery outcomes. →

Coronary micro vascular dysfunction is attracting increasing attention, yet effective treatments remain inadequate. This study analysed the clinical efficacy and potential mechanisms of Xinbao pill in patients with microvascular angina (MVA). 200 MVA patients admitted from January 2020 to June 2021 were randomly divided into the control group (n = 100) and an observation group… →

A Step-by-Step Coding Guide to Building a Gemini-Powered AI Startup Pitch Generator Using LiteLLM Framework, Gradio, and FPDF in Google Colab with PDF Export Support In this tutorial, we built a powerful and interactive AI application that generates startup pitch ideas using Google’s Gemini Pro model through the versatile LiteLLM framework. is the backbone of… →

MMSearch-R1: End-to-End Reinforcement Learning for Active Image Search in LMMs Large Multimodal Models (LMMs) have demonstrated remarkable capabilities when trained on extensive visual-text paired data, advancing multimodal understanding tasks significantly. However, these models struggle with complex real-world knowledge, particularly long-tail information that emerges after training cutoffs or domain-specific knowledge restricted by privacy, copyright, or security… →
