平溃散对实验性胃溃疡模型的影响

作者观察了平溃散对多种实验性胃溃疡模型的作用。结果表明：平溃散可非常显著的对抗束缚应激法和消炎痛加乙醇所致的小鼠胃溃疡；对幽门结扎法及ＨＣｌ损伤法所致大鼠胃溃疡模型也有明显对抗作用。各组分研究表明：平溃散基础方组、全方组、绞股蓝组和沙棘组均有显著的抗溃疡作用，但以全方组抗溃疡作用最佳。     

局域光纤IP电话的性能研究

提出并分析了基于光纤网络的IP电话系统，针对IP电话网中的时延，抖动，数据包丢失等关键问题分别进行分析。找出了取消网关，路由器和采用光纤化等解决方法，比较基于H．232协议的IP电话与基于SIP协议的光纤IP电话系统，发现利用光纤网能很好补偿时延和改善数据包丢失等问题，提高系统的抗干扰能力，使IP电话系统的性能得到很大提高，采用排队论进行了流量分析，证明以上方法是有效的。     

基于利益相关者理论的城市轨道交通项目需求分析

城市轨道交通项目的定位及其价值的实现,是建立在项目各方的利益需求得到平衡与满足的基础之上,因此全面识别与城市轨道交通项目紧密相关的单位或群体,并分析其各自的利益需求,对城市轨道交通项目的定位及其价值的实现显得至关重要。此文基于利益相关者理论,通过对城市轨道交通项目利益相关者的识别、核心相关者的确定及其利益需求分析,以期为城市轨道交通项目建设工作提供帮助。     

轻轨线路平面最小曲线半径探讨

轻轨系统作为一种中运量的城市轨道交通系统具有广阔的应用空间,轻轨线路的平面曲线半径对线路的适用性、投资大小、换乘方便程度、施工难易程度、旅客乘坐的舒适性以及养护维修工作量等均有重要影响,因此选择合适的平面最小曲线半径具有重要意义.结合轻轨线路的特点,分析确定线路平面最小曲线半径的基本原理,讨论影响线路平面曲线半径大小的...     

罗尔斯-罗伊斯AQM US 205-255系列舵桨滑差离合器浅析

本文主要介绍Rolls-Royce公司全回转推进系统滑差离合器液压及控制系统工作原理,常见故障及其处理方法,存在的缺陷及缺陷整改方案。     

汽车前照灯水汽凝聚现象的瞬态CFD预测

汽车前照灯光品质是衡量汽车照明系统安全性的一项重要指标.通过商用计算流体力学(Computational Fluid Dynamics,CFD)软件Star-CCM+对汽车前照灯内部的流动情况、热力学特性以及起雾/除雾过程进行了模拟.研究表明,雾层厚度与分布主要与湿度、流动条件以及换热条件相关.探索了完整的大灯起雾仿真...     

喷嘴内燃油空化及影响因素的实验研究

柴油机燃油喷射雾化过程除受湍流和环境气体的空气动力学效应影响外,还与喷孔内空化有关,因此对喷孔内燃油空化和影响因素的研究有重要的意义。本文中设计了透明喷孔代替原柴油机喷油器的喷孔,采用高速数码相机和高放大倍数、高分辩率的长距离显微成像技术和纳秒级闪光灯作为相机曝光光源,获得了较高分辩率和清晰度的实验图像。对柴油机喷孔内燃油空化产生、发展和分布状态进行显微观测,直观展现喷孔内燃油空化及影响规律,获得了燃油空化过程的直观认识。结果表明,柴油机喷孔内空化流动情况比较复杂,影响因素较多,其中喷孔几何结构对喷嘴内空化过程影响最显著,喷孔内空化首先出现在压力室针阀附近,随后空化区域向喷孔出口处扩散、延伸,对于渐缩喷孔,空化形成受到抑制,而渐扩喷孔则有利于空化形成;减小喷孔直径,不利于空化形成。环境压力对空化起到抑制的作用,环境压力增大,也不利于空化形成。此外还对喷孔内空化强度进行量化描述,通过空化强度对实验获得的图像进行量化分析。     

On a link-based day-to-day traffic assignment model

In this paper, we perform a rigorous analysis on a link-based day-to-day traffic assignment model recently proposed in He et al. (2010). Several properties, including the invariance set and the constrained stability, of this dynamical process are established. An extension of the model to the asymmetric case is investigated and the stability result is also established under slightly more restrictive assumptions. Numerical experiments are conducted to demonstrate the findings.     

An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

Developing an integrated scobit-based activity participation and time allocation model to explore influence of childcare on women’s time use behaviour

Focusing on the influence of childcare on women’s time use behaviour, this paper develops an integrated model of activity participation and time allocation, where the former is represented based on a scobit model and the latter based on a multi-linear utility function under the utility-maximizing principle. The integration of the scobit model with the time allocation model is done by applying Lee’s transformation. Especially, the scobit model is adopted to relax the assumption, made in the Logit or Probit model, that individuals having indifferent preferences over participation and non-participation are most sensitive to changes in explanatory variables. Using a large-scale time use data (66,839 persons) collected in Japan, the effectiveness of the proposed integrated model is empirically confirmed. It is revealed that the probabilities of participating in compulsory-contracted activities and discretionary activities with the highest sensitivity to changes in explanatory variables are 65 and 81%, respectively. Variances of social childcare variables explain about half of the total variance of the time use for discretionary activities; however, for compulsory-contracted activities, social childcare variables explain only less than 1% of the total variance of activity participation and less than 10% of total variable of time allocation.