应用FPS进行大型有限元程序移植的探讨

探讨应用Fortrand powerStation V4．0进行大型有限元程序移植的几个问题,提出了相应的解决办法,并进行了SAAX程序的移植。     

MARPOL73/78附则IV的历届修正及其相关PSC检查

文中对MARPOL73／78附则1V的历届修正及最新发展进行了介绍，其中对于2007年2月2日对我国生效的经MEPC．115（51）决议修订的MARPOL73／78附则IV的主要修订进行了详细分析，提出了我们在PSC检查中对生活污水处理装置的公约符合性检查要点，     

胎盘组织中Human Annexin V的表达及与HBV感染的关系

目的观察Human AnnexinV(HAV)在胎盘组织中的表达,并探讨其在乙型肝炎病毒(HBV)感染胎盘中的可能作用。方法用免疫荧光染色法检测早孕绒毛,中孕和足月胎盘绒毛中HAV的表达;用免疫荧光双重染色法观察HBV感染的胎盘组织HBsAg和HAV的分布及相互关系。结果①所有的标本绒毛滋养层细胞、绒毛间质细胞、毛细血管内皮细胞都有HAV的存在。②HBV感染的胎盘绒毛中只要是HBsAg阳性的部位同时一定有HAV的表达,阳性信号存在于滋养层细胞、绒毛间质细胞、绒毛毛细血管内皮细胞中。结论HAV可能作为HBsAg的特异性受体介导了HBV与胎盘组织各层细胞的粘附、内化等过程并最终导致了HBV对胎盘的感染。     

25G型客车DC 600 V供电系统漏电流分析及解决方案

分析了现有铁路客车DC600 V供电系统漏电流产生的原因,并从抑制共模干扰的角度出发,介绍了一种简单可靠的解决假"漏电"问题的方法。     

CD44V6,Bcl-2在宫颈癌中的表达及临床意义

目的　探讨黏附分子CD44V6和原癌基因Bcl 2在宫颈癌中的表达及临床意义。方法　应用免疫组化S P法检测 153例宫颈癌、正常宫颈上皮组织和宫颈不典型增生 (CIN)中CD44V6和Bcl 2的表达 ,并分析其与临床病理间关系。结果　①CD44V6表达在宫颈癌中最高 ,其次为CIN ,在正常宫颈组织最低 ,差异有显著性 (P <0 .0 5) ;随临床分期越晚 ,组织学分级越高 (CD44V6)表达率越高 ,并与组织学分级显著相关 (P <0 .0 5) ;淋巴结转移组 (CD44V6)表达率明显高于无淋巴结转移组 (P <0 .0 5) ;②Bcl 2表达在CIN中最高 ,其次宫颈癌 ,在正常宫颈组织不表达 ,差异有显著性 (P <0 .0 5) ;Bcl 2表达与临床分期、组织学分级呈负相关 ,且差异均有显著性 (P <0 .0 5) ;淋巴结转移组Bcl 2表达率低于无淋巴结转移组但差异无显著性 (P >0 .0 5)。③CD44V6和Bcl 2在宫颈癌中表达不相关。结论　CD44V6、Bcl 2表达与宫颈癌的发生 ,发展及转移密切相关 ,可作为预测宫颈癌预后的辅助指标     

基于车联网BSM数据与路侧视频融合的港口集装箱卡车碰撞危险辨识方法

大型港口集装箱码头运输车辆调度频繁,堆场过道和交换区等区域视距狭窄,容易导致港口集装箱卡车与设施、作业人员和车辆发生擦碰事故。为提高智能集装箱卡车在港口密集区域的轨迹跟踪精度和行车安全感知能力,提出了一种车联网条件下融合车载终端基本安全消息（Basic Safety Messages,BSM）数据和路侧视频数据的集装箱卡车碰撞风险辨识方法。采用YOLOv5s算法提取视频监控范围内的目标车辆和作业人员,根据目标集卡大尺寸特点设计非极大值抑制锚框来提高目标识别准确度。运用透视变换原理将目标像素坐标转换成地理坐标,并应用Deep-SORT算法匹配每帧图像的车辆轨迹信息。应用交互式多模型方法（interactive multi-model,IMM）融合视频轨迹信息和车载单元（on-board units,OBU）定位数据,减小了目标机动过程中的观测误差。基于集卡融合轨迹结果,提出了1种新型的轨迹冲突风险评估模型,能够根据目标集卡与周围目标轨迹的相对运动状态实时感知车辆碰撞危险,该碰撞危险检测结果在实际场景中可通过路侧设备对车载终端和作业人员终端实时播发预警信息。针对集卡跟踪误差的实验结果表明：IMM自适应跟踪轨迹的平均均方根误差为0.29 m,比集卡自主跟踪轨迹误差提升81.05%;融合路侧监控视频与车载终端定位数据能够克服车辆自主定位系统在密集堆场环境下的误差增大问题。集卡碰撞危险辨识的结果表明：车辆碰撞危险识别结果（预设ETTC阈值为2 s）的召回率、精确度和准确度相对集卡自主感知分别提升了7.39%,4.27%,2.50%,更准确地辨识出了视线遮挡情况下的轨迹冲突风险。     

基于数据驱动的人机混驾多车协同控制算法

针对多车协同控制系统中,传统控制算法需要准确获取系统中与驾驶员驾驶行为相关的参数以及与车辆系统动力学相关参数等问题,提出基于数据驱动的自适应动态规划控制算法。以有人与无人驾驶车辆混行的多车协同控制系统为研究对象,通过分析系统的横纵向控制模型,推导出系统状态方程,采用递推数值方法在线逼近最优解,并通过对最优反馈控制矩阵进行优化求解,得到最优控制输入。该算法简化了系统的控制输入参数,仅仅利用V2X通信获得的车辆的前轮转角以及车辆期望的纵向加速度作为控制输入,即可实现无人驾驶车辆的优化控制。基于Carsim和Simulink进行联合仿真测试验证,结果表明,该算法控制参数简单、收敛速度快、控制精度高、适应性强,能够控制无人驾驶车辆在多车系统中保持期望的车速并且与前车保持期望的车间距,同时在任意曲率道路上行驶时与车道中心线之间的横向误差趋于0。     

Analytical model for information flow propagation wave under an information relay control strategy in a congested vehicle-to-vehicle communication environment

Vehicular traffic congestion in a vehicle-to-vehicle (V2V) communication environment can lead to congestion effects for information flow propagation. Such congestion effects can impact whether a specific information packet of interest can reach a desired location, and if so, in a timely manner to influence the traffic system performance. Motivated by the usefulness and timeliness of information propagation, this paper aims to characterize the information flow propagation wave (IFPW) for an information packet in a congested V2V communication environment under an information relay control strategy. This strategy seeks to exclude information that is dated in the communication buffer under a first-in, first-out queue discipline, from being relayed if the information flow regime is congested. It trades off the need to enable the dissemination of every information packet as far as possible, against the congestion effects that accrue because of the presence of multiple information packets. A macroscopic two-layer model is proposed to characterize the IFPW. The upper layer is formulated as integro-differential equations to characterize the information dissemination in space and time under this control strategy. The lower layer adopts the Lighthill-Whitham-Richards model to capture the traffic flow dynamics. Based on the upper layer model, a necessary condition is derived which quantifies the expected time length that needs to be reserved for broadcasting the information packet of interest so as to ensure the formation of an IFPW under a given density of V2V-equipped vehicles. When the necessary condition is satisfied under homogeneous conditions, it is shown that the information packet can be propagated at an asymptotic speed whose value can be derived analytically. Besides, under the proposed control strategy, only a proportion of vehicles (labeled asymptotic density of informed vehicles) can receive the specific information packet, which can be estimated by solving a nonlinear equation. The asymptotic IFPW speed, the asymptotic density of informed vehicles, and the necessary condition for the IFPW, help in evaluating the timeliness of information propagation and the influence of traffic dynamics on information propagation. In addition, the proposed model can be used to numerically estimate the IFPW speed for heterogeneous conditions, which can aid in the design of traffic management strategies built upon the timely propagation of information through V2V communication.     

Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

Currently autonomous or self-driving vehicles are at the heart of academia and industry research because of its multi-faceted advantages that includes improved safety, reduced congestion, lower emissions and greater mobility. Software is the key driving factor underpinning autonomy within which planning algorithms that are responsible for mission-critical decision making hold a significant position. While transporting passengers or goods from a given origin to a given destination, motion planning methods incorporate searching for a path to follow, avoiding obstacles and generating the best trajectory that ensures safety, comfort and efficiency. A range of different planning approaches have been proposed in the literature. The purpose of this paper is to review existing approaches and then compare and contrast different methods employed for the motion planning of autonomous on-road driving that consists of (1) finding a path, (2) searching for the safest manoeuvre and (3) determining the most feasible trajectory. Methods developed by researchers in each of these three levels exhibit varying levels of complexity and performance accuracy. This paper presents a critical evaluation of each of these methods, in terms of their advantages/disadvantages, inherent limitations, feasibility, optimality, handling of obstacles and testing operational environments.Based on a critical review of existing methods, research challenges to address current limitations are identified and future research directions are suggested so as to enhance the performance of planning algorithms at all three levels. Some promising areas of future focus have been identified as the use of vehicular communications (V2V and V2I) and the incorporation of transport engineering aspects in order to improve the look-ahead horizon of current sensing technologies that are essential for planning with the aim of reducing the total cost of driverless vehicles. This critical review on planning techniques presented in this paper, along with the associated discussions on their constraints and limitations, seek to assist researchers in accelerating development in the emerging field of autonomous vehicle research.     

V型天窗中的接触网感应电压的分析与计算

以接触网V型天窗为背景,提出了复线接触网中,在一侧停电的情况下静电感应电压和电磁感应电压的计算方法,并对带回流线的直接供电方式下的电磁感应电压进行了分析与计算。在假设的工况下,计算出了相应的静电感应电压和电磁感应电压。