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Effectiveness of Cardiac Rehabilitation in Enhancing Adherence and Improving Clinical Outcomes Post-Acute Coronary Syndrome: A Randomized Controlled Trial
CONCLUSION: Cardiac rehabilitation significantly enhances adherence to medical and lifestyle recommendations, reduces complications, and improves outcomes in ACS patients. These findings emphasize the critical role of structured rehabilitation in post-ACS management. →
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MiMo-VL-7B: A Powerful Vision-Language Model to Enhance General Visual Understanding and Multimodal Reasoning
MiMo-VL-7B: A Powerful Vision-Language Model to Enhance General Visual Understanding and Multimodal Reasoning Vision-language models (VLMs) are essential for multimodal AI systems, allowing autonomous agents to comprehend visual environments, reason across different content types, and interact with both digital and physical realms. The introduction of MiMo-VL-7B by researchers from Xiaomi marks a significant advancement in… →
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Reliable-loc: Robust Sequential LiDAR Global Localization in Large-Scale Street Scenes Based on Verifiable Cues
Reliable-loc introduces a resilient LiDAR-based global localization system for wearable mapping devices in complex, GNSS-denied street environments with sparse features and incomplete prior maps. Key Highlights: Dual-Stage Observation Model for MCL: Fuses global and local features into Monte Carlo Localization (MCL), using spectral matching and pose error metrics to refine particle weights in feature-poor scenes.… →
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Cost-Effectiveness of Personalised Nutrition in Adults With Overweight and Obesity: PREVENTOMICS Studies in Poland and the UK
CONCLUSIONS: The PREVENTOMICS interventions may offer a cost-effective approach to reduce weight and avoid its related complications in both countries. Future studies should be larger and/or longer to reduce uncertainty about effectiveness. →
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A randomized trial to evaluate the impact of breast density notification on anxiety, breast cancer worry, and perceived risk among Latinas at a federally qualified health center : Breast density notification and anxiety, breast cancer worry, and perceived risk among Latinas
CONCLUSION: This Latina cohort had high levels of anxiety and BC worry which persisted regardless of intervention received. Future work is needed to improve our understanding of factors that could lower anxiety and BC worry and improve BC risk perception in this population. →
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Evaluating the impact of various predictors on rapid maxillary expansion (RME) success
CONCLUSIONS: Patients with a higher stage of MSM and CVM had a greater risk of RME failure. Additionally, patients with a lower density ratio and shorter palate length had a better prognosis for conventional RME. →
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Effect of intermediate airway management on ventilation parameters in simulated paediatric out-of-hospital cardiac arrest: a multicentre randomised crossover trial
CONCLUSION: In a simulated paediatric out-of-hospital cardiac arrest model, immediate use of intermediate airway management did not show relevant differences compared to bag-valve-mask. Intermediate airway management devices cannot be recommended as first-line choice but may be considered when bag-valve-mask is challenging. Whichever device is used, the focus should remain on providing high-quality ventilations. →
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NVIDIA AI Introduces Fast-dLLM: A Training-Free Framework That Brings KV Caching and Parallel Decoding to Diffusion LLMs
NVIDIA AI Introduces Fast-dLLM: A Training-Free Framework That Brings KV Caching and Parallel Decoding to Diffusion LLMs Diffusion-based large language models (LLMs) are gaining traction as a viable alternative to traditional autoregressive models, owing to their potential for simultaneous multi-token generation. By employing bidirectional attention mechanisms, these models seek to enhance decoding speeds, theoretically offering… →
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Off-Policy Reinforcement Learning RL with KL Divergence Yields Superior Reasoning in Large Language Models
Off-Policy Reinforcement Learning with KL Divergence Yields Superior Reasoning in Large Language Models Policy gradient methods have significantly advanced the reasoning capabilities of large language models (LLMs), particularly through reinforcement learning (RL). A key tool in stabilizing these methods is Kullback-Leibler (KL) regularization, which discourages drastic changes between the current policy and the reference policy.… →