人工智能与信息通信网络的深入融合被普遍认为是未来通信网络系统发展的重要趋势之一。尽管人工智能已经在自然语言、图像与视频处理及生成等方面展现出卓越的性能,然而在通信网络领域的应用仍处于初始阶段。具体而言,虽然5G从R15版本...人工智能与信息通信网络的深入融合被普遍认为是未来通信网络系统发展的重要趋势之一。尽管人工智能已经在自然语言、图像与视频处理及生成等方面展现出卓越的性能,然而在通信网络领域的应用仍处于初始阶段。具体而言,虽然5G从R15版本就已引入网络数据分析功能(NWDAF,Network Data Analytics Function)模块处理网络中传输和产生的各类数据,但仍然与全自治网络相去甚远。此外,所谓网络“内生智能”的具体实现路径与理论方法也尚未形成共识。造成上述困境的原因主要有两个方面。首先,从通信网络技术角度,由于隐私保护等原因,通信网络中传输和处理的数据一般已在源端进行过压缩和加密处理,因此其源数据内部的结构特征已被减弱或完全消除;同时,不同应用和设备对数据的处理和加密方式及格式也有所不同,导致网络中的数据存在高度异构性和随机性等特点,因此难以直接应用现有以模式识别和特征提取为主的人工智能算法与模型进行处理。展开更多
This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high bl...This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.展开更多
文摘人工智能与信息通信网络的深入融合被普遍认为是未来通信网络系统发展的重要趋势之一。尽管人工智能已经在自然语言、图像与视频处理及生成等方面展现出卓越的性能,然而在通信网络领域的应用仍处于初始阶段。具体而言,虽然5G从R15版本就已引入网络数据分析功能(NWDAF,Network Data Analytics Function)模块处理网络中传输和产生的各类数据,但仍然与全自治网络相去甚远。此外,所谓网络“内生智能”的具体实现路径与理论方法也尚未形成共识。造成上述困境的原因主要有两个方面。首先,从通信网络技术角度,由于隐私保护等原因,通信网络中传输和处理的数据一般已在源端进行过压缩和加密处理,因此其源数据内部的结构特征已被减弱或完全消除;同时,不同应用和设备对数据的处理和加密方式及格式也有所不同,导致网络中的数据存在高度异构性和随机性等特点,因此难以直接应用现有以模式识别和特征提取为主的人工智能算法与模型进行处理。
文摘This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.
