基于人工神经网络的智能化架空线路应变快速解调方法北大核心

为了提高智能化光纤复合架空线路态势感知的实时性,将人工神经网络方法应用于光纤沿线应变解调,确定了神经网络的结构。编程实现了基于洛伦兹模型的最小二乘谱拟合方法和神经网络方法,采用不同信噪比和布里渊频移的布里渊谱训练神经网络,将它们应用于某光纤复合架空线路沿线光纤应变的测量,从不同角度比较了两种方法的计算结果。计算结果表明,神经网络方法能有效获得光纤沿线的布里渊频移进而获得应变,具有与谱拟合方法相似的准确性,但应变解调时间仅约为谱拟合方法的1/20000。研究结果为提高智能光纤复合架空线路态势感知的实时性提供了参考。     

双功能催化剂上四氢萘加氢裂化生成单环芳烃的反应网络研究

Conversion of LCO (light cycle oil) to BTX (benzene, toluene, and xylene) is an economically valuable method for refineries. However, this approach still faces difficulties as the main reactions are not clearly understood. Here we study the detailed hydrocracking pathway of typical reactants, 1-methylnaphthalene and tetralin, through molecular simulations and experiments to improve our understanding of the conversion process of LCO to BTX. Molecular simulations demonstrate that the rate-determining step is the isomerization pathway of six-membered ring to five-membered ring in tetralin as its activation energy (ΔEa) is the highest among all the reactions and the order of ΔEa of reactions is isomerization > ring-opening ≈ side-chain cleavage. The results of experiments show that with the increase in reaction depth, i.e., through a high temperature (350 – 370 °C) and low LHSV (4.5 – 6.0 h−1), isomerization, ring-opening, and side-chain  cleavage reactions occurred, thus improving the selectivity and yield of alkyl aromatics.     

基于平均飞行航迹的CCO减噪效用研究

近年来，通过优化飞行程序降低机场飞机噪声影响成为机场环境保护的重要研究方向。文章首先建立了基于飞机“噪声-功率-距离”数据的噪声计算模型，介绍了平均飞行航迹以及连续爬升运行(Continuous Climb Opera-tion, CCO)离场程序的相关理论，最后以大型国际机场为实例，使用飞机平均飞行航迹进行噪声预测，运用综合噪声模型计算出噪声影响面积并绘制噪声影响等值线图，比较了CCO离场相对常规的标准仪表离场(Standard Instru-ment Departure, SID)的降噪效果。结果表明，CCO离场程序可有效降低机场噪声影响，在高噪声级影响区域的降噪效果更佳。     

Comparative analysis of the determinants of fees charged by fee-based homes for the elderly in urban and suburban areas

This study contributes to establishing the payment function of fee-based homes for the elderly. Disclosure statements from such homes for the elderly in selected urban and suburban cities in Fukuoka Prefecture, Japan—considered a typical prefecture with adjoining urban and suburban areas—were examined. The study compared the determinants of the amounts charged by the homes based on the distinct geographic features of urban and suburban areas. The hedonic price model was combined with a two-stage least squares regression to determine the determinants of lump-sum and monthly payments. We found that the factors that influence monthly payments in urban areas include distance to a park, distance to the coast, meals offered, number of care staff, and initial lump-sum payment. In contrast, factors such as room size, distance to a bus stop, distance to a park, and the number of night staff influence monthly payments in suburban areas. We conclude that the surrounding landscape has a greater influence on monthly payments in urban areas than in suburban areas. Moreover, in suburban areas, the number of night staff has a substantial impact on monthly payments. The results can help provide investment suggestions in certain cases depending on the amount of investment capital.