THE EXPERIMENTAL STUDY ON THE CELL APOPTOSIS AND EXPRESSION OF BCL-2 PROTEIN IN INTRACEREBRAL HEMORRHAGE IN MODEL OF RATS

Intra-cerebral hemorrhage is a common clinicaldisease,with a high mortality and morbidity.So itis one of the clinical hot topics.It has been foundinrecent years that there is a close relationship bet weenthe cell apoptosis and the course or prognosis of in-tra-cerebral hemorrhage.Bcl-2,as the apoptosis-adjusted gene,plays ani mportant role in the courseof cell apoptosis,but the mechanis min the cell ap-optosis in intra-cerebral hemorrhage remains un-clear.In this experi ment,with the model bui…     

FA—2JPLC自动控制程序设计方法——移位寄存器设计法

叙述了FA－2J型可编程序控制器（Programmable Logic Controller，简称PLC）自动控制程度设计方法－移位寄存器设计法，并举例说明。     

Bayesian network for red-light-running prediction at signalized intersections

Abstract

Red-light-running (RLR) is an important reason for the large number of intersection-related fatalities, injuries, and other losses. The accurate RLR prediction can effectively reduce crashes caused by RLR behavior. The RLR prediction is usually composed of two parts: the vehicle’s stop-or-go behavior and the arrival time when the vehicle reaches the stop line. Previous stop-or-go prediction models are usually based on embedded traffic sensors using machine learning algorithms. While based on the continuous trajectories collected by radar sensors, RLR prediction can be conducted more effectively. In this paper, a probabilistic stop-or-go prediction model based on the Bayesian network (BN) is proposed for RLR prediction. We extend the deterministic output into the probabilistic output, which provides decision-makers with greater autonomy. The causality of BN improves the interpretability of the prediction model. The BN model is calibrated and tested by the continuous trajectories data measured by radar sensors installed at a signalized intersection. We not only consider the movement measurements of individual vehicles (e.g., speed and acceleration), but also take into account the car-following behavior. As a comparison, different machine learning models and the model based on the inductive loop detection (ILD) are adopted. The results show that the proposed BN model has a high prediction accuracy and performs better in the feature interpretation. This paper provides a new way for probabilistic RLR prediction based on continuous trajectories, which will significantly improve traffic safety of signalized intersections.     

轻型车燃用生物柴油瞬态工况排放特性的研究

通过对轻型车燃用生物柴油和0#柴油尾气排放的测量和分析,研究瞬态工况有害排放物模态特性。试验结果表明,与0#柴油相比,轻型车燃用生物柴油可显著改善冷启动过程的HC和CO排放,其HC、CO和PM比排放分别降低76．9％、45．7％和52．8％,但NOx比排放增加5．8％。燃料在燃烧转变为CO2和H2O释放出化学能的同时也将空气中的N2氧化成NOx,因而可用NOx／CO2来描述NOx排放随运行工况的变化规律。     

FLAC3D进行土钉支护变形及支护参数分析

用FLAC^3D对基坑土钉支护进行数值模拟,对分步开挖支护时的不平衡力、土钉轴力、土体塑性区、竖向及水平位移进行研究,初步探讨了土钉支护参数对土钉轴力、基坑土体变形的影响,得到一些有参考价值的分析结果,为土钉支护优化设计提供了重要依据。     

浅析路面模量反演的修正迭代法

该文介绍了路面模量反演的修正迭代法。以目前国际上普遍使用的落锤式弯沉仪（FWD：Falling Weight Deflectometer）的弯沉检测数据为依据,通过预估模量的初值、建立弯沉值对模量的导数矩阵、不断修正初始模量值的方法,开发了路面模量反演的修正迭代法。通过理论和试验证明：该算法具有收敛速度快、精度高、稳定性好的优点。     

自抗扰控制在前轮主动转向控制中的应用

为进一步提高前轮主动转向的性能,采用自抗扰控制算法来实现前轮主动转向控制.在对车辆动力学方程进行规范化的基础上,设计了二阶自抗扰控制算法.在双移线工况和对开路面加速工况下,对该算法的控制效果进行了硬件在环的仿真试验研究.结果表明,自抗扰控制算法能够有效地实现前轮主动转向控制,控制效果优于P1D控制,具有更高的抗扰动能力...     

基于路网可达的15分钟社区生活圈便利度研究

从居民日常生活需求出发,社区生活圈被认为是助力城市向精明增长方向转型的关键抓手和有效路径.基于POI、道路网、DEM等多源数据,构造基于路网可达的15分钟社区生活圈模型.搭建包含7项一级指标、20项二级指标的生活圈便利度指标体系,从设施总量、设施有无、设施空间相关性三个方面开展生活圈便利度评价.选取青岛市东岸城区作为实...     

CFG桩复合地基设计参数对地基沉降影响的数值分析

高速铁路对路基的工后沉降提出了严格的要求,因此正确选择能满足高速铁路技术标准要求的合理的地基处理方案和设计参数,是一项迫切需要解决的课题.针对CFG桩加固京沪高速铁路某一松软土地基试验段,采用数值计算方法,分析了桩筏复合地基和桩(帽)网复合地基两种方案、不同桩间距、有无桩帽和桩帽大小等设计参数对地基沉降的影响,为CFG桩复合地基在松软土地基上的设计优化提供了依据.     

DWL-48连续走行捣固稳定车控制系统分析

对DWL-48连续捣固稳定车的捣固装置控制系统进行分析,认为控制策略的滞后是导致设备现场使用故障的重要原因。以捣固架提升与下降控制为例,提出基于BP神经网络的捣固装置控制系统的设计思路。