经直肠豚鼠志贺菌痢疾模型的改良

目的改良经直肠途径建立豚鼠志贺菌痢疾动物模型的方法。方法 20只受试豚鼠根据感染前24 h禁食或不禁食处理分为2组,8只非禁食组参照文献经直肠灌注致病性福氏志贺菌sf301菌株,12只禁食组经直肠分别灌注PBS(5只)和sf301菌株(7只),观察受试豚鼠的感染症状,通过组织病理学方法证实其发病与否。结果非禁食组豚鼠仅有1只(1/8)在感染后24 h内表现出明显的体重减轻、发热等典型的菌痢症状。禁食组经直肠灌注sf301菌株的豚鼠(6/7)在感染后24 h内有显著的发热症状,体重减轻则发生在感染后的24~48 h内;灌注PBS的豚鼠(0/5)无异样症状。组织病理学结果显示,发病豚鼠结肠末端的黏膜以及黏膜下层遭到明显的破坏,肠壁增厚,出现水肿、糜烂、大量中性粒细胞浸润等。结论成功建立了改良的经直肠豚鼠志贺菌痢疾动物模型。     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Emergence of cooperation in congested road networks using ICT and future and emerging technologies: A game-based review

Information and communications technologies (ICT) and future and emerging technologies (FET) are expected to revolutionize transportation in the next generation. Travelers’ behavioral adaptation is a key to their success. We discuss the notion of managing traffic congestion by enhancing cooperation in road networks enabled with ICT and FET. Cooperation is an emergent social state related to the dynamics and complexity of road traffic and reinforced learning. Game theory and research in behavioral economics show that cooperation can be leveraged to efficiently solve social dilemmas similar to traffic congestion. We review the applicability of behavioral economics and game theory concepts to route, mode and departure time choice problems. Beyond advancing theory, research on cooperation in the context of transportation is still in its infancy. We discuss state-of-the-art methodologies and their weaknesses and review the unexplored opportunities inherent in game-based methodologies. A behavioral-technological research agenda for FET is also discussed.     

基于相对变形的大变形隧道地应力反算

针对复杂地质条件下高地应力大变形隧道地应力复杂多变的特点，为满足该类隧道动态设计对地应力资料的要求，提出基于上台阶开挖后拱腰水平收敛与拱顶下沉的相对比值并结合开挖揭示的围岩情况，建立二维数值模型反算地应力的方法。以丽江至香格里拉铁路中义隧道为例，对该方法进行详细说明。研究表明所述方法具有无需地应力测试、计算方便的优点，施工期间可用于地应力分析、预测。中义隧道典型区段地应力反算结果表明： 1）隧道出口及2号横洞工区的地应力分布特点并不相同； 2）围岩及埋深差别不大的区段，隧道水平收敛变形出现较大差异主要是由于地应力侧压力系数不同引起的。     

水工模型试验的流速测量方法与数据处理程序

在水工模型试验中,基础数据的准确度与精确度直接关系到科研成果的质量。流速是模型试验中观测的主要数据之一。模型流速的测量方法有许多种,如示踪物法、光电法、声学多普勒法等。光电法是目前水工模型试验中应用最多的流速测量方法。文章所述的模型测杆流速处理程序实现的功能就是计算流速测杆采集流速的平均值并直观地以流速过程线图显示。通过应用于上海国际航运中心洋山港区整体物理模型试验的实践表明,程序采用微调方法,解决了判断涨落潮时存在的问题,提高了水工模型试验工作的精度和效率,为科学决策提供了依据。     

舰船水下爆炸鞭状运动中的阻尼效应

舰船在水下爆炸气泡脉动压力作用下将产生鞭状运动冲击响应。为了掌握冲击响应的衰减规律,建立了舰船结构、设备、水舱内流体和外部流体等在振动和晃荡过程中的阻尼效应动力学模型,并编写程序对是否考虑上述阻尼效应的舰船鞭状运动响应进行了数值计算。研究结果表明,对于具有相对较大质量的内部设备和水舱的舰船来说,上述阻尼效应对舰船水下爆炸鞭状运动的衰减起到重要的作用,如不予以考虑有可能造成对舰船鞭状运动响应幅值的高估。     

浅路基沉降模型研究

被广泛应用于路基工程中的土工合成材料具有较好的抗拉性能，可以提高路基整体稳定性，减小路基整体位移变形。对经典加固土模型进行了回顾，旨在说明不同模型对应的实际组分。通过路基结构稳定性的量化分析，得到了材料抗拉性能及其他属性对路基沉降的影响。并通过经典模型与实际工程的参数化联系，解决实际工程问题。     

微型桩-香根草协同护坡试验与计算研究

单一的香根草护坡或微型桩护坡在边坡加固与防护工程中均得到了广泛应用，但针对两者协同护坡的研究和相关工程应用相对较少。边坡安全系数作为评判边坡稳定性的重要依据之一，其计算分析结果的准确程度高，可提升滑坡灾害的预测水平，从而降低损失。通过室外大比例尺模型试验，采用坡顶分级堆载对植被与微型桩协同护坡的效果进行试验，并对采用多种理论与数值方法求得的边坡安全系数进行了比较，分析了香根草及微型桩对边坡安全系数的影响。试验与计算结果表明：采用三维有限元分析得到的安全系数略高于二维有限元分析；相比于素土边坡，微型桩-香根草协同护坡能极大地提高边坡安全系数，有效提高坡体稳定性，而且能够提高边坡承受荷载能力，研究结果可为生态防护与工程加固措施协同护坡工程设计提供理论依据。