Low-load resistance training with blood flow restriction (LRT-BFR) has shown potential to improve muscle strength and mass in different populations; however, there remains limited evidence in sarcopenic people diagnosed with sarcopenia criteria. This study systematically compared the effectiveness of LRT-BFR and conventional high-intensity resistance training (CRT) on clinical muscle outcomes (muscle mass, strength and performance),… →
CONCLUSIONS: The investigated low-dose CBCT protocols could provide acceptable image quality for the evaluation of impacted M3Ms in most cases. When compared to standard-dose CBCT, these low-dose CBCT images did not significantly affect the assessments of the M3M-MC proximity, treatment strategies, and patient management decisions made by GPs and OMFSs. →
CONCLUSION: The synbiotic tested was shown to be efficacious in the management of infant colic. A significant improvement was observed after 7 days of intervention, which is much earlier than the expected decrease related to the natural evolution of infant colic. →
CONCLUSIONS: Heat-sensitive moxibustion combined with intrapleural infusion of cisplatin is superior to intrapleural infusion of cisplatin in the aspects of the amelioration of pleural effusion, daily-living activity and TCM syndromes in patients with MPE. This combined therapy presents the synergism by cooperating with chemotherapeutics and reduces the incidence of toxic and side effects implicated in… →
Planning and decision-making in complex, partially observed environments is a significant challenge in embodied AI. Traditionally, embodied agents rely on physical exploration to gather more information, which can be time-consuming and impractical, especially in large-scale, dynamic environments. For instance, autonomous driving or navigation in urban settings often demands the agent to make quick decisions based… →
Using large language models (LLMs) has revolutionized artificial intelligence applications, enabling breakthroughs in natural language processing tasks like conversational AI, content generation, and automated code completion. Often with billions of parameters, these models rely on massive memory resources to store intermediate computation states and large key-value caches during inference. These models’ computational intensity and growing… →
Log-based anomaly detection has become essential for improving software system reliability by identifying issues from log data. However, traditional deep learning methods often struggle to interpret the semantic details in log data, typically in natural language. LLMs, like GPT-4 and Llama 3, have shown promise in handling such tasks due to their advanced language comprehension.… →
Effective lesson structuring remains a critical challenge in educational settings, particularly when conversations and tutoring sessions need to address predefined topics or worksheet problems. Educators face the complex task of optimally allocating time across different problems while accommodating diverse student learning needs. This challenge is especially pronounced for novice teachers and those managing large student… →