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Twin delayed deep deterministic (TD3) policy gradient has several limitations when applied in planning a path in environment with a number of dilemmas according to our experiment, due to the complexity of the robot path planning task, the rate of convergence of TD3 algorithm is slow and the rate of collision is high. To address this problem, deep dense dueling twin delayed deep deterministic (D3-TD3) architecture is proposed, a method that preserves important information from cross-layer inputs through dense connections and divides the network into a value function and a dominance function, thus, allowing for faster convergence when solving complex tasks. Finally, a spatial model based on three-dimension (3D) point cloud is built, and simulation experimental results show that in static environment, the algorithm proposed in the paper has 40.6% fewer collisions compared to TD3, 30% fewer collisions compared to TD3-BC, 19.2% fewer collisions compared to Dueling TD3 and 17.4% fewer collisions compared to deep dense TD3. In dynamic and static environment, the algorithm proposed in the paper has 34.4% fewer collisions compared to TD3, 24% fewer collisions compared to TD3-BC, 6% fewer collisions compared to Dueling TD3 and 25% fewer collisions compared to deep dense TD3. [ABSTRACT FROM AUTHOR]

Background: To investigate the clinical relevance of cytokine levels in assessment of the severity of mycoplasma pneumoniae pneumonia (MPP) in children., Methods: A retrospective study was conducted on 150 pediatric cases of MPP admitted to a local hospital in China from November 1, 2022 to October 31, 2023. These MPP cases were divided into mild (n=100) and severe (n=50) groups according to the severity of the disease. Cytokine levels, including Interferon-γ (IFN-γ), Tumor Necrosis Factor-α (TNF-α), C-reactive protein (CRP), Interleukin-6 (IL-6), Interleukin-2 (IL-2), and D-Dimer (D-D), were compared between the two groups. The diagnostic efficacy of each cytokine in assessing the severity of MPP was analyzed through Receiver Operating Characteristic (ROC) curves, and correlation between cytokine levels and disease severity was assessed using Pearson's correlation coefficient., Results: The IL-2 level was significantly lower, while TNF-α, IL-6, and IFN-γ levels were significantly higher in the severe group compared to the mild group (all P<0.05). TNF-α, IFN-γ, IL-2, IL-6, CRP, and D-D were identified as factors influencing the severity of MPP (all P<0.05). The ROC curve analysis showed that the areas under the curve (AUCs) of TNF-α, IL-2, IL-6, IFN-γ, CRP, and D-D were 0.864, 0.692, 0.874, 0.949, 0.814, and 0.691, respectively (all P<0.001), indicating their diagnostic value in assessing the severity of MPP. There exists a positive correlation between IL-2 and the percentage of normal lung density on Computed Tomography (CT) scan (P<0.05), while TNF-α, IL-6, IFN-γ, CRP, and D-D showed negative correlations with the percentage of normal lung density (P<0.05)., Conclusion: Cytokines such as TNF-α, IL-2, IL-6, IFN-γ, CRP, and D-D are aberrantly expressed in children with MPP and are associated with the severity of the disease. These cytokines have high diagnostic value and can serve as reference indicators for clinical, especially prognostic assessment of the severity of (pediatric) MPP., Competing Interests: None., (AJTR Copyright © 2024.)